Smart HVAC rooftop units with integrated ai and thermal imaging for enhanced operational control

Abstract

Improved apparatus and methods for a Smart Rooftop Unit (SRTU) incorporating infrared (IR) thermal imaging and artificial intelligence (AI) for enhanced HVAC performance are disclosed. The SRTU integrates multiple IR cameras positioned strategically on, around, or within the unit to capture comprehensive thermal images, enabling real-time monitoring and predictive maintenance. An AI-driven control system analyzes the thermal images to optimize defrost cycles, heating and cooling loads, and overall system efficiency. The control system interfaces with building management systems (BMS) for dynamic adjustments based on occupancy, air quality, and weather conditions. The modular design of the SRTU facilitates easy assembly, maintenance, and component upgrades. Advanced sensors and environmental monitors provide continuous data to ensure optimal operation and energy efficiency. The methods include steps for data acquisition, AI analysis, and system adjustments to maintain peak performance and extend the lifespan of the SRTU components.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 676,283, filed Jul. 26, 2024, and entitled SMART HVAC ROOFTOP UNITS WITH INTEGRATED AI AND THERMAL IMAGING FOR ENHANCED OPERATIONAL CONTROL, the entire contents of which are incorporated herein by reference.FIELD OF THE DISCLOSURE

[0002] The present invention relates to methods and apparatus for enhancing the efficiency and performance of heating, ventilation, and air conditioning (HVAC) systems. More specifically, the present invention pertains to a rooftop unit (RTU) equipped with infrared thermal imaging and automated processes for real-time monitoring, predictive maintenance, and optimized defrosting processes. The invention provides for the use of thermal imaging technology, such as, for example, infrared (IR) imaging, to generate thermal profiles and monitor, and / or predict thermal loads of RTU components. By leveraging these thermal profiles, the system optimizes the operation of RTU components, providing more efficient and effective heating, cooling, and ventilation.BACKGROUND OF THE DISCLOSURE

[0003] Rooftop units (RTUs) are widely used in commercial and industrial buildings to provide heating, ventilation, and air conditioning. Traditional RTUs, however, often suffer from several limitations that can affect their performance, efficiency, and reliability. Key issues include the inability to accurately monitor component temperatures, lack of real-time data analysis, inefficient defrosting processes, and reactive rather than proactive maintenance strategies.

[0004] Conventional RTUs typically rely on discrete sensors to monitor the temperature of critical components such as compressors, coils, and fans. These sensors can only provide point-specific data, which may not accurately represent the overall thermal condition of the components. Additionally, physical contact sensors can be prone to wear and tear, leading to inaccurate readings and potential failures.

[0005] Defrosting is a critical process in RTUs, particularly in regions with cold climates where frost accumulation on evaporator coils can severely impact performance. Traditional defrosting methods often involve periodic shutdowns and manual interventions, leading to energy inefficiency, increased wear on components, and potential disruptions in climate control.

[0006] Maintenance of RTUs is typically reactive, addressing issues only after they have caused operational problems. This approach can result in unexpected downtime, costly repairs, and reduced lifespan of the unit. Predictive maintenance strategies, which rely on continuous monitoring and data analysis to anticipate failures, are not commonly integrated into traditional RTUs.

[0007] Further, buildings account for a considerable portion of the total energy consumption, especially in developed countries. This energy consumption includes energy used in building construction in the manufacture of equipment that is incorporated into a building deployed for operation.

[0008] Consequently, the construction industry has an opportunity to improve its impact on the degradation of the environment. Standards such as LEED (Leadership in Energy and Environmental Design) encourage the construction industry to adopt sustainable practices that can mitigate its environmental impact. LEED is a green building certification program developed by the U.S. Green Building Council (USGBC). LEED includes a set of rating systems for the design, construction, operation, and maintenance of green buildings, homes, and communities.

[0009] Buildings may earn different levels of certification based on a number of points the building achieves in various categories. Various LEED designations include, for example, one or more of: Certified: based upon a building earning 40-49 points; Silver: based upon a building earning 50-59 points; Gold: based upon a building earning 60-79 points; and Platinum: based upon a building earning 80+ points.

[0010] The categories in which these points can be achieved include one or more of: Sustainable Sites; Water Efficiency; Energy and Atmosphere; Materials and Resources; Indoor Environmental Quality; Innovation in Design; and Regional Priority.

[0011] LEED promotes sustainability by encouraging designs that: use less water and energy; reduce greenhouse gas emissions; improve indoor environmental quality; and create a healthier and safer environment for occupants.

[0012] Energy involved in the manufacture, transportation, and installation on the top of a commercial building of such large heavy, galvanized steel items, such as a Roof Top Unit (RTU), involves a significant amount of energy and a consequential carbon footprint. The structural strength that is required to support the heavy weight of a traditional RTU is also significant and may further add to detrimental aspects of a LEED rating.

[0013] There is a need within the industry to develop and implement solutions that not only minimize environmental impact but also align with the evolving sustainability standards like LEED. The focus is increasingly shifting towards creating materials and systems that are not only efficient in their use but also contribute to the overall reduction of the carbon footprint of buildings. This shift includes rethinking the materials and design of building components such as HVAC systems, particularly Roof Top Units (RTUs), to make them more eco-friendly.SUMMARY OF THE DISCLOSURE

[0014] The present invention addresses these gaps by introducing a Smart Rooftop Unit (SRTU) with integrated infrared thermal imaging and AI. The system may provide continuous, real-time monitoring of component temperatures, proactive defrosting management, and predictive maintenance capabilities. The SRTU leverages detailed thermal imaging data, analyzed by AI, to optimize HVAC operations, enhance energy efficiency, reduce downtime, and extend the lifespan of critical components.

[0015] A Rooftop Unit (RTU) is a type of HVAC (Heating, Ventilation, and Air Conditioning) system that is typically mounted outside of a commercial building, such as on a roof of the commercial building. RTUs can provide heating, cooling, and ventilation to the space below. RTU is typically housed in its own metal housing or casing (or cabinet) that is specifically constructed to withstand external environmental conditions since it's located on a building's roof. The housing or casing contains major components of the HVAC system and protects the major components from weather, debris, and potential damage. The housing or casing of an RTU is typically manufactured from galvanized steel or other heavy material with an energy-intensive manufacturing process. The galvanized steel often includes multiple panels and may be fashioned into several compartments. The housing will have air intake portions and outlet portions.

[0016] According to the present invention, a SRTU is capable of converting thermal images into digital value patterns, generate heat maps, and dynamically adjust defrost parameters based on real-time data and AI analysis on SRTU components. Such analysis SRTU operating at optimal performance levels, maintaining a comfortable indoor environment while minimizing energy consumption and maintenance costs.

[0017] In some embodiments of the invention, the SRTU may be equipped with an advanced infrared thermal imaging system integrated with artificial intelligence (AI) to provide continuous, real-time monitoring of critical components such as compressors, coils, fans, and electrical circuits. The infrared thermal imaging system captures the thermal radiation emitted by these components and converts it into high-resolution thermal images. These images are digitized and analyzed by the Controller and / or AI engine, which uses machine learning algorithms to identify temperature anomalies, analyze trends, and correlate the thermal data with other operational variables like defrost cycles and power usage. The AI system can predict potential issues, such as overheating or component failures, and recommend maintenance actions before these issues cause significant downtime or damage.

[0018] Additionally, the SRTU may utilize the infrared thermal imaging system to generate real-time heat maps, highlighting areas with excessive frost accumulation. This may enable the system to direct defrost airflow precisely to the affected areas using adjustable louvers, jets, and multiple fans, optimizing the defrosting process and improving energy efficiency. The Controller and / or AI engine continuously adjusts the RTU's operation based on real-time data, providing optimal performance and preventing thermal stress. Users can monitor the system through a user-friendly interface that displays thermal images and operational data, receiving alerts and maintenance recommendations via mobile devices. The SRTU may also be constructed to adapt to varying environmental conditions and operational demands by incorporating data on geographic location, seasonal trends, and weather predictions, providing reliable and efficient operation in diverse settings.

[0019] In some embodiments of the invention, multiple infrared (IR) cameras may be strategically installed around the SRTU on the roof to provide comprehensive coverage from all directions. This arrangement may ensure that the entire surface of the SRTU is monitored for heat variations, allowing for a detailed analysis of temperature distribution and thermal behavior. The IR cameras capture high-resolution thermal images, which are then processed and analyzed by the AI system. By continuously monitoring the thermal patterns across the SRTU, the AI system can detect anomalies, such as unexpected hot spots or uneven heat distribution, which may indicate potential inefficiencies or emerging issues with the unit's operation. This data enables the AI to predict component failures, optimize performance, and recommend proactive maintenance actions.

[0020] The AI system may use the thermal data to control the SRTU dynamically, adjusting parameters such as cooling load, fan speeds, and defrost cycles to ensure optimal efficiency. For example, if the cameras detect an area of the SRTU that is consistently overheating, the AI can increase cooling to that specific region or recommend cleaning or servicing to remove any obstructions or faults causing the issue. Similarly, by monitoring the heat patterns during defrost cycles, the AI can fine-tune the process to target areas with the most frost accumulation, thereby improving the overall energy efficiency of the unit.

[0021] Furthermore, the system can provide detailed recommendations to maintenance personnel through a user interface, displaying thermal images, highlighting areas of concern, and suggesting specific actions, such as replacing a component, adjusting settings, or scheduling a thorough inspection. These recommendations are based on both real-time data and historical trends, allowing for a predictive maintenance approach that reduces downtime and extends the lifespan of the SRTU. Additionally, by continuously learning from the thermal data, the AI system can improve its predictive accuracy over time, making the SRTU smarter and more efficient. This comprehensive thermal monitoring and AI-driven analysis ensure that the SRTU operates at peak performance, providing reliable and efficient climate control while minimizing energy consumption and maintenance costs.

[0022] In some embodiments, the present invention also provides methods and apparatus for reducing one or both of: the weight and carbon footprint associated with an RTU suitable to contain HVAC components on the roof area of a large building. In some embodiments of the invention, the SRTU's housing may primarily be constructed from Polypropylene Random Copolymer (PPR), a material chosen for its lightweight yet robust characteristics. To fortify this, the PPR may be coated with a protective layer, which may be either galvanized steel or a high-grade impervious plastic. This outer coating is constructed to withstand adverse weather conditions, such as heavy rainfall, snow, intense sunlight, and temperature extremes. In some configurations, the SRTU unit may further benefit from a dual-layered approach where the PPR is sandwiched between two such protective coatings. This design not only offers an external shield against environmental factors but also enhances the internal stability of the unit. For example, the outer layer may be a corrosion-resistant alloy in coastal areas to combat saltwater damage, while an inner layer of UV-reflective material may be used in sunnier climates to prevent degradation due to UV exposure. Additionally, the outer surface may also feature a textured finish to minimize dust and debris accumulation, maintaining the unit's efficiency and reducing cleaning requirements.

[0023] In some embodiments of the invention, the SRTU may be equipped with smart technology interfaces. These interfaces allow for remote monitoring and control of the unit, enabling users to optimize performance based on real-time data. This technology can adjust settings for energy efficiency, monitor the health of the unit, and provide alerts for maintenance needs. Such integration with IoT (Internet of Things) devices enhances user experience and operational efficiency. This remote accessibility is particularly advantageous for large buildings or complexes where on-site management of each unit can be logistically challenging. This smart technology goes beyond mere remote control; it may enable the SRTU to deliver real-time data about its performance and condition. This feature may be instrumental in optimizing the unit's performance for energy efficiency. Users can adjust settings such as temperature and airflow, based on real-time feedback, ensuring the unit operates at peak efficiency while minimizing energy consumption. This adaptability not only leads to cost savings but also aligns with environmental sustainability goals. This may continuously analyze the functioning of the SRTU, detecting potential issues before they escalate into major problems. Users receive alerts for regular maintenance or urgent repair needs, enabling proactive management of the unit. This pre-emptive approach to maintenance enables the SRTU to operate reliably over its lifespan, reducing downtime and avoiding costly emergency repairs. The integration of smart technology interfaces transforms the SRTU into a highly intelligent, responsive, and efficient system. This integration may also represent a significant stride toward the future of smart building management, where convenience, efficiency, and sustainability converge.

[0024] Some implementations include an SRTU constructed with a core layer made from Polypropylene Random Copolymer (PPR), chosen for its durability and versatility. Affixed to this core layer is at least one protective layer, which can be a metallic layer composed of materials like aluminum or galvanized steel, a non-metallic UV-resistant polymer, high-grade impervious plastic, or a nanocomposite coating constructed for enhanced durability and reflectivity. In some embodiments, the SRTU features a sandwich structure, where a first protective layer is applied to one side of the PPR core and a second, potentially different, protective layer is applied to the other side.

[0025] The unit's modularity can be a key aspect, with components configured for easy assembly, disassembly, and maintenance. Such a design approach allows for quick servicing and potential future upgrades. The modular components may include detachable panels with standardized connectors for efficient installation and servicing, and they are constructed to be interchangeable to cater to specific building requirements.

[0026] The SRTU may also comprise an integrated control system equipped with a Controller and / or AI engine and various sensors, including, but not limited to, temperature, pressure, humidity, and air-quality sensors. This system can operate in conjunction with a building management system (BMS), enhancing the overall efficiency and responsiveness of the HVAC setup. The control system is also capable of wireless connectivity for remote monitoring and control, adding a layer of convenience and advanced functionality.

[0027] Additional features of the SRTU may include an economizer for utilizing outside air for indoor temperature control, an integrated solar panel system for auxiliary power generation, and a rainwater harvesting system. These features may contribute to the unit's energy efficiency and environmental sustainability. A condensate drain may also be included to manage moisture from the cooling process, and a thermal insulation system adaptable to varying climatic conditions optimizes operational efficiency.

[0028] For enhanced user comfort and structural compatibility, the SRTU may include a sound attenuation system within the protective layers to reduce operational noise and a vibration-damping mechanism to minimize the transmission of vibrations to the building structure. The protective layer may also comprise a self-cleaning surface, reducing maintenance requirements.

[0029] In some embodiments of the invention, the SRTU may be enhanced with a layer of adaptive insulation, which intelligently alters its thermal resistance based on real-time temperature readings. This innovative insulation layer employs materials that can expand or contract, or otherwise change their insulating properties, in response to external temperature shifts. Such smart materials enable the SRTU to maintain optimal internal temperatures more efficiently by reducing the need for additional heating or cooling when external conditions are favorable. This dynamic adjustment capability makes the SRTU more energy-efficient, potentially leading to lower operational costs and a reduced environmental footprint. The adaptive insulation layer can be integrated during the manufacturing process or retrofitted into existing units, providing a versatile solution for new and upgraded HVAC systems.

[0030] In some embodiments of the invention, the modular components may be constructed from biodegradable or compostable materials. These environmentally conscious materials may be selected to minimize the ecological footprint upon the end of the unit's service life, ensuring that components break down naturally without harming the ecosystem. This approach not only contributes to sustainable manufacturing practices but also aligns with green building certifications, potentially enhancing the overall environmental performance rating of the buildings where these units are installed.

[0031] In some embodiments of the invention, the SRTU may be enhanced with smart surface coatings on its outermost protective layer. These advanced coatings may be engineered to change color or texture in response to fluctuations in temperature. This thermochromic feature provides a visual cue to the unit's operating condition, allowing for easy and immediate surface condition monitoring without the need for complex sensors or equipment. Such smart coatings not only serve as a diagnostic tool for maintenance personnel but also offer a way to visually ensure that the unit is functioning within its optimal temperature range, thus contributing to proactive maintenance and energy efficiency.

[0032] In some embodiments of the invention, the SRTU may feature a modular design that allows for customizable configuration of its components. This modularity enables the unit to be tailored to specific building needs, such as varying roof sizes or shapes. The ability to customize the layout of components like air intakes, exhausts, and service panels enables the SRTU to be adapted to a wide range of architectural designs.

[0033] Some embodiments may incorporate vibration-damping materials and designs to minimize operational noise and structural impact. This feature is particularly important in residential areas or buildings where noise reduction is a priority. The vibration damping is achieved through the strategic placement of materials within the unit's structure, ensuring that the unit operates quietly while maintaining its efficiency and durability.

[0034] In certain embodiments, the SRTU may be constructed with an aerodynamic shape to minimize wind resistance and load on the building structure. This design is especially beneficial in high-wind areas or tall buildings, where wind load can be a significant factor. The aerodynamic design also contributes to the overall efficiency of the unit, reducing potential energy loss due to wind resistance.

[0035] Some versions of the SRTU may integrate a heat recovery system, which captures and reuses waste heat from the HVAC process. This system enhances the overall energy efficiency of the unit, reducing the energy needed to heat or cool the building. The heat recovery system is constructed to be compatible with the modular nature of the SRTU, allowing for easy integration into different unit configurations.

[0036] In another embodiment, the SRTU may include an advanced humidity control system. This system is constructed to maintain optimal indoor humidity levels, which is critical for comfort and health. The humidity control is particularly beneficial in regions with high humidity or arid climates. It works in tandem with the HVAC system to ensure a comfortable and healthy indoor environment, further enhancing the SRTU's appeal in diverse climatic conditions.BRIEF DESCRIPTION OF THE DRAWINGS

[0037] FIG. 1 illustrates an exemplary overview of an SRTU installed on a building roof comprising multiple IR cameras to capture thermal images of the SRTU.

[0038] FIG. 1A illustrates an exemplary SRTU system integrating SRTU control system, IR cameras and BMS in accordance with some embodiments of the present invention.

[0039] FIG. 1B illustrates exemplary fields of view for multiple IR cameras to capture thermal images of an SRTU.

[0040] FIG. 1C illustrates multiple thermal images combined to form a single thermal image for AI analysis.

[0041] FIG. 2 illustrates an exemplary embodiment of an SRTU.

[0042] FIG. 2A illustrates a schematic representation of SRTU integration with the building HVAC system.

[0043] FIG. 3 illustrates an exemplary embodiment of a modular SRTU under supervision of multiple thermal cameras.

[0044] FIGS. 4 and 4A illustrate an exemplary SRTU control system providing automated design suggestions for the SRTU to improve its performance.

[0045] FIG. 5 illustrates an exemplary SRTU system integrating with an IR camera and BMS in accordance with some embodiments of the present invention.

[0046] FIG. 5A illustrates an exemplary embodiment of an SRTU system in accordance with the present invention.

[0047] FIG. 6 illustrates an exemplary embodiment of an SRTU with an internal component's layout.

[0048] FIG. 7 illustrates an internal view of the SRTU with emphasis on airflow dampers and corresponding temperature distribution on SRTU surface.

[0049] FIG. 8 illustrates an SRTU cross-section highlighting an exemplary multistage filtration process and temperature distribution related to the filters.

[0050] FIG. 9 illustrates SRTU temperature modulation components featuring heating and cooling coils and their respective temperature distributions on top surface of the SRTU.

[0051] FIG. 10 illustrates the SRTU's centrifugal EC fan, associated airflow mechanics and IR camera installed within the SRTU to monitor heat signatures of the internal SRTU components.

[0052] FIG. 11 illustrates operational dynamics of the SRTU with an open damper for air recirculation.

[0053] FIG. 12 illustrates an SRTU air management system with a closed damper and fresh air intake.

[0054] FIG. 13 illustrates an exemplary block diagram of an SRTU system for an HVAC system.

[0055] FIGS. 14, 14A, and 14B illustrate an exemplary flow chart of method steps that may be performed in some embodiments of the present invention.

[0056] FIG. 15 illustrates an exemplary block diagram of an LRTU system for an HVAC system.

[0057] FIG. 16 illustrates a schematic diagram of a controller.

[0058] FIG. 17 illustrates a schematic diagram of an RTU based upon Magnetocaloric Technology.DETAILED DESCRIPTION

[0059] The present invention provides a system, apparatus and methods for a Smart Roof Top Unit (SRTU) that integrates advanced infrared (IR) temperature monitoring to enhance its operational efficiency and reliability. The system utilizes IR cameras strategically placed on or around the SRTU unit to continuously capture thermal images or video feed of the SRTU. These thermal images are useful for identifying temperature variations and detecting potential issues such as overheating or frost accumulation.

[0060] The captured IR thermal images may be converted into digital value patterns, allowing for precise quantitative analysis by a Controller and / or AI engine. Each pixel in the thermal image corresponds to a specific temperature value, which is digitized to form a detailed thermal map of the SRTU. This digital representation of thermal data is essential for the subsequent analysis and control processes managed by the Controller and / or AI engine integrated within the SRTU or on a cloud server.

[0061] The Controller and / or AI engine may assess the digital value patterns by mapping them against other variable trends such as defrost cycles, power usage, and efficiency metrics. For defrost cycles, the AI analyzes the thermal data to detect frost build-up on the evaporator coils. When frost accumulation is identified, the AI initiates the defrost cycle and monitors the process to ensure effective and efficient frost removal. The Controller and / or AI engine also evaluates power usage trends, optimizing the operation to reduce energy consumption by adjusting settings based on real-time thermal data and historical performance. Efficiency may further be enhanced by minimizing wear and tear on components, reducing the maintenance load, and extending the lifespan of the unit.

[0062] To achieve maximum performance, the Controller and / or AI engine enables the SRTU to operate at peak efficiency, providing maximum cooling capacity when needed. This may include fast transitions between different operating states to respond promptly to changes in cooling or heating demands. When the system receives a command for additional cooling, the AI anticipates the resulting temperature map based on the expected load increase. This proactive adjustment may allow the SRTU to meet the new cooling or heating demands efficiently without overburdening the system.

[0063] The Controller and / or AI engine continuously monitors ambient conditions within the building spaces to be cooled, using data from various sensors integrated in the Building Management System (BMS) of the building. These sensors measure temperature, humidity, and airflow within the controlled space, providing comprehensive real-time environmental data. Additionally, infrared imaging is used to assess the current state of the HVAC equipment and historical trends, identifying whether the equipment is operating under normal conditions or experiencing high stress that can lead to potential failures. The system can also assess the number of occupants in specific areas, using this information to adjust HVAC demand dynamically.

[0064] Predictive HVAC demand may also be calculated based on several factors, including the day of the week, time of year, historical data, and geographic location. For example, the system may anticipate higher cooling demands on workdays and adjust the operation accordingly. Seasonal adjustments and comparisons between historical and current ambient data further refine the demand predictions, providing optimal performance and energy efficiency.

[0065] During defrost cycles, the system receives ambient conditions of the airflow used for defrosting. The Controller and / or AI engine can adjust the temperature and humidity of the defrost airflow to optimize the defrost process. A detailed heat map of the area to be defrosted is generated, indicating regions with excessive frost accumulation. Based on the heat map, the Controller and / or AI engine directs the defrost flow to specific areas using louvers, high-velocity jets, and / or multiple fans, providing targeted and efficient defrosting.

[0066] The Controller and / or AI engine also determines the optimum defrost state by defining specific criteria such as the most cooling power, most energy efficiency, and most responsiveness. By continuously analyzing the thermal data and adjusting the defrost parameters, the system enables the SRTU to operate efficiently, minimize energy consumption, and maintain optimal performance.

[0067] The present invention also provides an improved HVAC RTU design and construction, featuring a Smart RTU (SRTU) predominantly constructed from synthetic materials like Polypropylene Random Copolymer (PPR). The SRTU is further fortified with a weather-resistant surface coating, meticulously engineered to resist the external environmental elements it encounters atop a building's roof. The robust housing or casing of the SRTU safeguards the HVAC system's core components against weather, debris, and potential harm. The weather-resistant surface coating of the SRTU, which may include materials such as galvanized steel or other metallic or impervious plastic coatings, provides a shield against the adverse physical impacts of various weather conditions.

[0068] The SRTU is preferably formed by multiple disparate portions that may be configured to a size and shape specific to deployment suitable for a particular building, or portion of a building. It is noted that in some embodiments, different portions may be manufactured using different modalities of manufacturing processes. For example, larger portions may be extruded PPR onto a thin coating of galvanized steel, and smaller portions of intricate shapes may be injection molded or 3D printed and coated with a metallic coating.

[0069] In some embodiments of the invention, a novel design for Polypropylene Random Copolymer (PPR) Smart Roof Top Units (SRTUs) may be tailored for outdoor installations to conserve precious indoor space and address the environmental shortcomings of traditional HVAC materials. Recognizing that conventional construction materials for RTUs carry a substantial carbon footprint, the invention proposes a comparatively lightweight, eco-friendly alternative that significantly reduces the structural demands on buildings and the associated energy consumption during transport and installation.

[0070] The SRTU's primary structure is crafted from PPR due to its favorable attributes-being both lightweight and less taxing on the environment. However, to ensure longevity and resistance to the harshness of direct sunlight and weather conditions, the PPR requires additional protection. To this end, the invention incorporates a sheeting of PPR with a thin metallic or non-metallic barrier (protective layer), such as, but not limited to, stainless steel, galvanized steel, or aluminum. This layer offers structural integrity while providing a shield against the elements, effectively decreasing the volume of heavier metallic materials traditionally used.

[0071] The embodiment may contemplate a metallic or non-metallic layer that may be applied solely to the exterior or may envelop both sides of the PPR, essentially encapsulating the plastic core. This metallic protection can be achieved through a bonding process of PPR to metallic sheets or by spraying a metallic coating onto the PPR sheet, which may be produced via extrusion or 3D printing techniques.

[0072] The SRTU design significantly mitigates environmental impact not only due to the more sustainable manufacturing process of PPR compared to steel but also because the unit's comparatively lightweight nature demands less energy for transportation. A preferred cylindrical design of the SRTU is suggested, which can be realized by rolling PPR / metal composite materials into shape. This may involve constructing the SRTU from panels that are cut and assembled, or using portions of PPR protected with metallic coating alongside portions that are solely metallic, depending on the needs.

[0073] The SRTUs are non-corrosive and suitable for retrofitting applications that demand higher hygiene standards. The installation process is expedited, leading to reduced labor costs and time. With a higher R-value, these SRTUs provide better insulation, leading to energy savings. The flexible supply chain for PPR and metallic materials contributes to the SRTU's adaptability in production and distribution.

[0074] Monitoring the health of the SRTU is facilitated by measurements across the metallic portions, where stresses may be assessed via changes in electrical resistance. Furthermore, the design supports sustainability by allowing for the regrinding of plastic components and the recycling of steel, thereby contributing to a circular economy in HVAC system production.

[0075] In some embodiments, building upon the innovative design of the SRTU, further enhancements may be made to optimize its functionality and environmental compatibility. One such enhancement may involve the integration of an energy recovery ventilator (ERV) system within the SRTU. This system may capture the energy from exhaust air to precondition incoming fresh air, significantly improving energy efficiency, especially in extreme weather conditions. This ERV integration may be particularly beneficial in maintaining indoor air quality while reducing the energy load on the HVAC system. Additionally, considering the growing focus on sustainable energy sources, the SRTU may incorporate photovoltaic solar fabric, a flexible and lightweight material, over portions of its surface. This solar fabric may also serve as an additional power source besides acting as an extra protective layer, contributing more to the unit's overall energy efficiency, and reducing its reliance on traditional energy sources.

[0076] Other embodiments may enhance the SRTU's adaptability and maintenance case through the incorporation of smart diagnostic sensors. These sensors may continuously monitor the unit's performance and health, providing real-time data analytics for predictive maintenance and early detection of potential issues. The use of such advanced diagnostics may extend the lifespan of the SRTU and optimize its performance.

[0077] Furthermore, in some embodiments, for the outer weather-resistant coating or layer, the use of nano-coatings may offer superior protection. Implementing such a coating may significantly enhance the unit's resilience and longevity. Nano-coatings, at the forefront of material technology, are composed of nanoparticles that, when applied to a surface, create an incredibly thin yet highly effective protective layer. These coatings are renowned for their exceptional durability and their resistance to a wide array of environmental stressors, including UV rays, moisture, and extreme temperature fluctuations. The application of nano-coatings on the SRTU's outer surface may impart several significant advantages. Firstly, with the resistance to UV radiation, the unit's material does not degrade or weaken over time due to prolonged sun exposure, a common issue on rooftops. This feature is particularly important in maintaining the structural integrity and appearance of the unit. Secondly, the hydrophobic nature of many nano-coatings makes the SRTU resistant to moisture, preventing issues such as corrosion, mold growth, and water damage, which are common in outdoor environments. This moisture resistance further extends the unit's operational lifespan and reduces maintenance needs.

[0078] Moreover, nano-coatings are adept at handling extreme temperature variations, protecting the SRTU from the thermal expansion and contraction that can occur in fluctuating climates. This adaptability enables the unit to remain structurally sound and functional regardless of seasonal temperature shifts. Another noteworthy aspect of nano-coatings is their self-cleaning properties. Due to their unique surface characteristics, dirt and debris are less likely to adhere to the coated surface, meaning the SRTU remains cleaner without requiring frequent manual cleaning, thus reducing maintenance efforts and costs.

[0079] Nano-coatings, characterized by their molecular-level precision and robust protective qualities, encompass a diverse range of materials, each tailored for specific applications. One prominent example is Titanium Dioxide (TiO2) nano-coatings, widely used for their photocatalytic properties and UV protection, making them ideal for outdoor applications like HVAC units. Another example is Silicon Dioxide (SiO2) or silica-based nano-coatings, renowned for their hydrophobic (water-repellent) qualities, which effectively protect surfaces from moisture and reduce dirt accumulation. Additionally, Zinc Oxide (ZnO) nano-coatings are noted for their antimicrobial properties and UV protection, often used in medical and outdoor equipment. Carbon nanotubes, though more specialized, offer exceptional strength and thermal conductivity, which can be advantageous in heat-intensive environments. Moreover, graphene, a single layer of carbon atoms arranged in a hexagonal lattice, is gaining attention for its remarkable strength, electrical conductivity, and thinness, making it a groundbreaking material in nano-coatings. Lastly, Polyurethane nano-coatings are utilized for their flexibility and durability, providing a resilient protective layer against physical abrasions and environmental wear and tear. Each of these nano-coating materials offers unique benefits, from UV protection and hydrophobicity to antimicrobial properties and structural strength, thus providing versatile solutions for enhancing the durability and functionality of various applications, including HVAC systems.

[0080] In some embodiments of the invention, the outer weather-resistant coating or layer of the SRTU unit may be constructed using PPR (Polypropylene Random Copolymer) that has been enhanced with nano-coatings. This approach involves imbuing the PPR with nano-scale materials to significantly bolster its protective qualities. In some other cases, PPR or other polymers can be used as part of a nanocomposite coating for the outer weather-resistant coating or layer of the SRTU unit. In such cases, nanoparticles or nanofillers (e.g., silica nanoparticles, clay nanoparticles) can be dispersed within a polymer matrix (including PPR) endowing it with superior mechanical strength and improved barrier properties, which are essential for withstanding environmental stressors. These nanocomposite coatings demonstrate enhanced performance characteristics over traditional polymer coatings, including increased durability, resistance to UV radiation, moisture, and thermal extremes. While PPR in its standard form is not a nano-coating material, its amalgamation with selected nanoparticles or nanofillers in a nanocomposite arrangement allows it to achieve advanced functionalities. This integration effectively elevates the weather-resistant capabilities of the SRTU, ensuring its longevity and reliability as an HVACSolution

[0081] Some embodiments of the invention may include an enhanced modular design for the SRTU unit, implementing a snap-fit or interlocking mechanism for joining different portions of the unit for simplifying the assembly process, making it more efficient and cost-effective, especially during installation or routine maintenance. The snap-fit mechanism may involve designing the edges of the SRTU's modular components with complementary shapes that can easily click or lock together without the need for additional fastening tools or hardware. This design not only streamlines the assembly process but also significantly reduces the time and labor involved in the installation. The interlocking parts are precision-engineered to ensure a secure and robust connection, important for maintaining structural integrity and performance efficiency of the HVAC system. This method of assembly is particularly advantageous in rooftop environments, where ease of installation is paramount due to the often challenging and less accessible nature of these spaces. Further, in some cases, these interlocking parts may also be joined together using basic fastening tools like nuts, bolts, or screws.

[0082] Furthermore, the snap-fit design inherently allows for easy disassembly, which is a major advantage during maintenance or repair operations. Service technicians can quickly disengage the interlocking components, perform maintenance or replacements, and reassemble the unit with minimal effort and time. This feature not only enhances the serviceability of the SRTU but also contributes to reduced maintenance costs over its lifespan.

[0083] Moreover, this modular and tool-less assembly approach can facilitate customizable configurations of the SRTU. Depending on the specific needs of a building's HVAC system, components can be added, removed, or rearranged with greater flexibility, adapting to varying architectural demands or changes in air conditioning requirements over time. This flexibility, combined with the ease of assembly, positions the SRTU as a highly adaptable and user-friendly option in the realm of HVAC solutions.

[0084] In the following sections, detailed descriptions of examples, apparatuses and methods will be given. The description of both preferred and alternative examples, though thorough, are exemplary only. It is understood by those skilled in the art, that various modifications and alterations may be apparent and within the scope of the present invention. Unless otherwise indicated by the language of the claims, the examples do not limit the broadness of the aspects of the underlying invention as defined by the claims.

[0085] Referring now to FIG. 1, an exemplary view of the SRTU 100 as part of an HVAC system, incorporating the principles and innovative aspects discussed in the present invention. The SRTU 100 may be constructed to optimize performance through real-time data acquisition and analysis.

[0086] According to embodiments of the present invention, a plurality of IR cameras 110A-110B, may strategically be positioned on, around or within the SRTU 100 to capture comprehensive thermal images from different angles. The IR cameras 110A and 110B may monitor the surface temperatures of various components, capturing high-resolution thermal images that are essential for detecting anomalies and providing efficient operation. The captured images may be transmitted to a SRTU control system 112 through wired or wireless connection 112A. The wired connection can utilize standard Ethernet cables for robust and reliable data transfer, while the wireless connection can leverage Wi-Fi or other wireless communication protocols like Zigbee or Bluetooth, offering flexibility and case of installation. In FIG. 1, the IR cameras 110A and 110B are shown in position to capture at least portion of an area within an SRTU 100. A position of image capture may be a fixed position, or a movable, or mobile location 113.

[0087] Multiple sensors 111 may be installed within the SRTU 100, providing data on various operational parameters. These sensors can include, but are not limited to, temperature sensors, humidity sensors, airflow sensors, and pressure sensors. Temperature sensors monitor the heat levels of critical components such as the cooling component 103 and the economizer hood 104. Humidity sensors may measure the moisture levels within the unit, which is vital for maintaining optimal air quality and preventing condensation issues. Airflow sensors may track the movement and volume of air through the supply air 106 and return air 107 pathways, providing efficient distribution and circulation. Pressure sensors may monitor the system's internal pressure to prevent overloading and detect potential leaks.

[0088] The SRTU control system 112 may be a sophisticated unit that processes the data received from the IR cameras 110A-110B and sensors 111. The control system 112 may comprise a display for real-time monitoring, a Controller and / or AI engine for data analysis and predictive maintenance, and connectivity features for remote access. The control system 112 can be physically installed on the SRTU 100 or located at a distant site, such as a cloud server, allowing for scalable and flexible deployment.

[0089] The Controller and / or AI engine within the control system 112 may analyze the thermal images from the IR cameras 110A-110B and sensor data to identify patterns, detect anomalies, and predict potential failures. This predictive maintenance capability helps in reducing downtime and extending the lifespan of the SRTU components. The display may provide a user-friendly interface for monitoring real-time data, configuring system settings, and receiving alerts and notifications.

[0090] The SRTU control system 112 may also support machine learning algorithms that continuously improve the accuracy of predictions based on historical data. Additionally, the SRTU can be equipped with smart alerts that notify maintenance personnel of potential issues via mobile devices, providing timely interventions. The integration of multiple IR cameras and sensors with the SRTU control system 112 enables comprehensive monitoring, real-time data analysis, and predictive maintenance, providing the efficient and reliable operation of the SRTU 100.

[0091] In some embodiments of the invention, the SRTU control system 112 may be integrated with a Building Management System (BMS) to enhance the overall efficiency and performance of the HVAC system within a building where the SRTU 100 is installed. This integration allows the SRTU control system 112 to receive and utilize various data points from the BMS to dynamically control the operations of the SRTU 100, providing optimal climate control, energy efficiency, and occupant comfort.

[0092] The control system 112 within the SRTU 100 may comprise a sophisticated array of components constructed to handle advanced processing, storage, and communication tasks. At its core, the control system may include a high-performance processor capable of executing complex algorithms and real-time data analysis. The processor may be complemented by a memory, including both RAM for quick access and operations, and non-volatile storage for maintaining logs, historical data, and system configurations. Additionally, the control system 112 may include robust connectivity options, such as Ethernet, Wi-Fi, and possibly cellular modules, to ensure seamless communication with cloud servers, BMS, and remote user interfaces.

[0093] To support its AI-driven functions, the control system 112 may integrate a dedicated Controller and / or AI engine, either as a specialized chipset or through optimized software running on the main processor. The control system may also comprise various wired and / or wireless I / O interfaces to connect with external sensors, IR cameras, and other monitoring devices. These interfaces may also include USB, RS485, and digital / analog input-output ports.

[0094] For enhanced functionality, the control system 112 may be equipped with redundant power supplies and backup batteries to ensure uninterrupted operation during power outages. Additionally, incorporating advanced security features such as encryption, secure boot, and intrusion detection systems protects sensitive data and prevents unauthorized access.

[0095] To facilitate user interaction and system configuration, the control system 112 may include a user-friendly interface, potentially featuring a touchscreen display for on-site control and monitoring. This interface may allow technicians to perform diagnostics, configure settings, and view real-time system status. For remote management, the system may support mobile and web applications, enabling users to monitor and control the SRTU 100 from anywhere.

[0096] The SRTU control system 112 may be configured to receive a wide array of data from the BMS, including but not limited to:

[0097] Internal Temperatures: Real-time data on the internal temperatures of different zones or rooms within the building. This information allows the SRTU control system 112 to adjust the cooling or heating output based on the specific needs of each area, providing consistent and comfortable indoor temperatures.

[0098] Occupied Spaces: Information on which areas of the building are currently occupied. By knowing the occupancy status, the SRTU control system 112 can prioritize conditioning air in occupied spaces while reducing energy usage in unoccupied areas, leading to significant energy savings.

[0099] Occupancy Levels: Detailed data on the number of occupants in different parts of the building. This helps the SRTU control system 112 to adjust ventilation rates to maintain optimal indoor air quality, enhancing the comfort and well-being of building occupants. In some embodiments of the invention, the occupied spaces and occupancy level within the building may to determined based on CCTV cameras installed within the building spaces.

[0100] Air Quality Metrics: Data on indoor air quality parameters such as CO2 levels, humidity, and the presence of pollutants. The SRTU control system 112 can adjust ventilation and filtration settings to maintain healthy air quality standards.

[0101] Energy Usage: Information on the building's overall energy consumption and patterns. By integrating this data, the SRTU control system 112 can optimize its operations to align with energy-saving goals, reducing operational costs and environmental impact.

[0102] Weather Conditions: External weather data, including temperature, humidity, wind speed, and solar radiation. This may allow the SRTU control system 112 to anticipate changes in the building's thermal load and adjust its operations accordingly. In some embodiments of the invention, the SRTU control system 112 may be integrated with a cloud server for receiving real time weather updates, weather predictions so that the SRTU can be optimized accordingly.

[0103] Scheduled Events: Information on scheduled events or changes in building usage, such as meetings, conferences, or maintenance activities. This may help the SRTU control system 112 to prepare and adjust its settings proactively.

[0104] The integration of the SRTU control system 112 with the BMS may be facilitated through standard communication protocols such as BACnet, Modbus, or LonWorks, enabling seamless data exchange and interoperability between the systems. The SRTU control system 112 processes the received BMS data using its Controller and / or AI engine, which analyzes the information to make real-time adjustments to the SRTU 100's operations.

[0105] For instance, if the BMS indicates that a particular zone in the building is experiencing a higher occupancy level, the SRTU control system 112 can increase the ventilation rate and adjust the cooling output to ensure that the area remains comfortable and well-ventilated. Similarly, if the BMS detects that a zone is unoccupied, the SRTU control system 112 can reduce the cooling or heating to that area, thereby conserving energy.

[0106] The Controller and / or AI engine within the SRTU control system 112 may continuously learn from the BMS data and historical performance metrics to improve its predictive capabilities. This may include optimizing defrost cycles based on weather conditions, adjusting airflow patterns to prevent hot or cold spots, and scheduling maintenance activities based on usage patterns and predictive analytics.

[0107] Additionally, the integrated system 112 can provide building managers with comprehensive insights and reports through a user-friendly interface, accessible via the SRTU control system's display or via smart devices remotely through cloud-based platforms. These reports may include energy usage trends, indoor air quality metrics, system performance analytics, and maintenance recommendations, empowering facility managers to make informed decisions and optimize building operations.

[0108] Further, the SRTU 100 may be constructed with a focus on modularity, energy efficiency, and environmental protection, showcasing several distinct features and components. At the forefront of the SRTU's design is a casing top 101, a modular panel constructed from Polypropylene Random Copolymer (PPR) that is enhanced with a protective layer or coatings for durability. This top panel may serve as the primary shield against direct environmental exposure, such as solar radiation and precipitation, and may be potentially outfitted with nano coatings to mitigate wear and UV damage.

[0109] A casing end panel 102 works in conjunction with the casing top 101 to encapsulate the SRTU unit 100, providing a complete barrier that safeguards the internal components of the HVAC system. The panels are constructed for easy removal, facilitating access for maintenance and repair, which is part of the unit's modular design philosophy.

[0110] A cooling component 103 is the heart of the SRTU's climate control capability. It may utilize advanced, eco-friendly refrigerants and is engineered for maximum heat exchange efficiency. The cooling component 103 may integrate variable speed fans and compressors to adapt its performance based on real-time demand, significantly reducing energy consumption.

[0111] An economizer hood 104 may be included to take advantage of cool external air when available, reducing the need for mechanical cooling and thereby enhancing the unit's overall energy efficiency. This hood 104 may be equipped with sensors to automatically adjust the air intake based on the outside temperature and air quality.

[0112] A reduced support 105 implies a lightweight yet sturdy framework that underpins the SRTU 100. It is optimized to minimize the load on the building structure while maintaining the stability and integrity of the SRTU unit 100, even under adverse weather conditions.

[0113] The supply air 106 and return air 107 channels are integral to the air circulation process within the SRTU 100. The supply air 106 pathway directs the conditioned air into the building, while the return air 107 channel cycles the indoor air back to the SRTU for air reconditioning. These pathways are constructed to maximize airflow efficiency and may be lined with sound-dampening materials to minimize operational noise. A roof safety wall 108, although not a part of the SRTU 100 itself, is an essential aspect of the installation environment. The design of the SRTU 100 may integrate these components into a cohesive unit that prioritizes energy efficiency, ease of maintenance, and robustness against environmental stressors.

[0114] In some embodiments, the SRTU 100 may incorporate the sophisticated control system 112 capable of managing the defrost cycle for the evaporator coils. The control system 112 leverages real-time data from IR cameras 110A-110B, BMS system, and / or various sensors to cause the Controller and / or AI engine to determine the optimal times for initiating and ending the defrost cycle.

[0115] When the evaporator coils need to be defrosted, the control system 112 receives input from temperature sensors and IR cameras that monitor the coil's surface temperature and detect frost accumulation. Once the Controller and / or AI engine analyzes this data and identifies a significant build-up of frost, it initiates the defrost cycle. The defrost process may carefully be managed to ensure that the coil is efficiently cleared of frost without disrupting the overall operation of the SRTU 100.

[0116] During the defrost cycle, additional instrumentation such as humidity sensors and airflow meters may be employed to monitor the conditions within the SRTU 100. These sensors may provide the Controller and / or AI engine with comprehensive data, allowing it to fine-tune the defrosting process and ensure that it is both effective and energy efficient.

[0117] Determining when the defrost time should end is important to prevent unnecessary energy consumption and ensure the evaporator coils return to optimal operating conditions as quickly as possible. The Controller and / or AI engine continuously analyzes data from temperature sensors and IR cameras to assess the progress of the defrost cycle. Once the sensors and / or the thermal images from the IR cameras indicate that the evaporator coil's surface temperature has reached a predetermined threshold, indicating the removal of frost, the Controller and / or AI engine concludes the defrost cycle.

[0118] In cases where additional instrumentation may be required to enhance the accuracy and efficiency of the defrost cycle, the system can be equipped with advanced thermal imaging cameras, moisture sensors, and even vibration sensors to detect any mechanical strain on the coils. These additional instruments may provide a more detailed understanding of the defrost process, ensuring that the evaporator coils operate efficiently and reliably.

[0119] In some embodiments of the invention, the Smart Roof Top Unit (SRTU) may be equipped with a comprehensive suite of environmental sensors constructed to dynamically adjust the unit's operations based on real-time atmospheric conditions. These sensors are strategically placed to detect a variety of environmental factors, including temperature, humidity, solar radiation, wind speed, and air quality.

[0120] Temperature sensors may provide data on external and internal temperatures, allowing the SRTU to optimize its heating or cooling output to maintain the desired indoor climate efficiently. Humidity sensors monitor the moisture levels in the air, which not only influence thermal comfort but also impact the unit's cooling efficiency due to the effects of latent heat.

[0121] In some embodiments, solar radiation sensors may play an important role in the SRTU's operation by measuring the intensity of sunlight impacting the unit. This information may be used to adjust the cooling load and to control the operation of the integrated solar panels, if present, to maximize their energy generation potential while minimizing the heat gain from solar exposure.

[0122] Wind speed sensors may inform the SRTU when to bolster system protections against potential wind damage, and when it is advantageous to leverage natural ventilation as part of the economizer function as discussed above. Air quality sensors may detect pollutants and particulates, prompting the advanced filtration system of the HVAC to adjust its operation to ensure a healthy indoor environment.

[0123] The SRTU's control system, which interfaces with these sensors, may utilize the data to intelligently adapt various components of the unit. For example, in some embodiments, the control system can modulate fan speeds, open or close dampers, and regulate the economizer to improve air quality and energy efficiency. It may also initiate protective measures during adverse conditions, such as retracting or shielding components (which may be associated with the SRTU) that may be damaged by severe weather.

[0124] In some embodiments, a SRTU may also be integrated with a building management system (BMS), allowing it to operate in concert with other building systems and to respond to both occupant requirements and external environmental conditions. This level of integration and responsiveness not only enhances occupant comfort and safety but also promotes sustainable operation by reducing energy consumption and extending the service life of the HVAC system.

[0125] Referring now to FIG. 1A, it illustrates an exemplary SRTU system 100A, highlighting the intricate network of components and data flows that enable advanced monitoring, control, and optimization of the SRTU 100 (FIG. 1). The SRTU control system or control panel 112 may be the central hub that receives and processes various data inputs to manage the operation of the SRTU 100 efficiently.

[0126] The SRTU control system 112 may receive SRTU data over a wired or wireless connection 113A. The SRTU data may comprise thermal images from one or more infrared (IR) cameras 110 installed around the SRTU unit100. These IR cameras 110 may strategically be positioned to capture comprehensive thermal images of the SRTU 100, monitoring temperature variations across its surfaces. The thermal imaging data is useful for identifying hot spots, assessing the thermal performance of the unit, and detecting potential issues such as overheating components or inefficient heat distribution. The cameras 110 may utilize high-resolution sensors to provide detailed thermal maps, which are transmitted to the control system 112 for detailed analysis.

[0127] In addition to thermal imaging, the SRTU data may include sensor data from multiple sensors 111 installed on or within the SRTU 100. These sensors can be of various types, each providing helpful information about different operational parameters of the SRTU. For example, temperature sensors measure the heat levels of specific components, humidity sensors monitor the moisture levels within the unit, airflow sensors track the volume and movement of air through the SRTU 100, and pressure sensors assess the internal pressure to prevent overloading and detect air leaks. The continuous flow of data from these sensors may allow the control system 112 to maintain optimal conditions within the SRTU 100, providing efficient and reliable performance.

[0128] The SRTU control system 112 may also integrate a Building Management System (BMS) 115, receiving BMS data 116 over a wired or wireless connection. This integration may enable the SRTU 100 to be part of a broader network of building automation systems, enhancing its ability to respond to the dynamic needs of the building. The BMS data 116 may include internal temperatures of different building zones, occupancy status, air quality metrics, energy usage patterns, and scheduled events. By incorporating this data, the SRTU control system 112 can adjust its operations based on real-time conditions and historical trends, optimizing energy efficiency and occupant comfort.

[0129] For example, in some embodiments, if the BMS 115 indicates that certain areas of the building are currently unoccupied, the SRTU control system 112 can reduce the cooling or heating output to those areas, conserving energy. Conversely, if a zone is heavily occupied, the system can increase ventilation and adjust temperature settings and engagement of HVAC equipment 1C to ensure a comfortable environment. The integration with BMS 115 may also allow the SRTU to participate in demand response programs, where it can adjust its operation during peak energy usage periods to reduce overall building consumption.

[0130] In various embodiments, a communication network for the SRTU system 100A may include both wired and / or wireless connections. Wired connections, such as Ethernet cables, offer robust and reliable data transfer with minimal interference, ideal for important data paths between the SRTU 100 and the control system 112. Wireless connections, including Wi-Fi, Zigbee, or Bluetooth, may provide flexibility in sensor placement and ease of installation, enabling a scalable and adaptable monitoring network.

[0131] The SRTU control system 112 may also interface with cloud-based servers 114 for extended data storage, advanced analytics, and remote access. By uploading data to the cloud 114, the system 100A can leverage powerful computational resources for machine learning and predictive analytics, identifying long-term trends and improving the predictive maintenance capabilities of the SRTU 100. Remote access via cloud servers 114 may allow facility managers to monitor and control the SRTU 100 from anywhere, receiving alerts and updates through mobile devices or web interfaces.

[0132] In some embodiments of the invention, the SRTU control system 112 may interface with cloud-based servers 114 through various networks 113B, enabling enhanced data storage, advanced analytics, and remote monitoring capabilities. These networks can include a range of technologies to ensure reliable and secure communication. For example, the SRTU control system 112 may connect to cloud-based servers 114 via wired connections such as fiber optic or Ethernet cables, which offer high-speed and stable data transfer suitable for transmitting large volumes of sensor and thermal imaging data. Additionally, wireless networks such as Wi-Fi, 4G LTE, and 5G cellular networks provide flexibility and ease of installation, allowing the SRTU to be deployed in various locations without the constraints of physical wiring. Satellite communication networks can also be employed for remote or off-grid installations where traditional wired or cellular networks may not be available. By leveraging these diverse networking options, the SRTU control system 112 may ensure continuous and robust communication with cloud-based servers 114, facilitating real-time data processing, remote diagnostics, and the integration of machine learning algorithms to predict maintenance needs and optimize system performance. This connectivity allows facility managers to access the SRTU data from anywhere, using secure web interfaces or mobile applications, thereby enhancing the overall efficiency and responsiveness of the building's HVAC system.

[0133] Moreover, the SRTU control system 112 may also be equipped with a user-friendly display and interface, providing real-time visualization of thermal images, sensor data, and operational status. This interface can be installed locally on the SRTU 100 or accessed remotely, offering comprehensive insights into the system's performance. Users can configure settings, view historical data, and receive maintenance recommendations through this interface, providing proactive management of the SRTU 100.

[0134] Various other features may also be integrated into the system 100A that include advanced fault detection algorithms, adaptive learning for continuous improvement, and integration with renewable energy sources. Fault detection algorithms may use the thermal and / or sensor data to identify and diagnose issues before they lead to failures, minimizing downtime. Adaptive learning may allow the Controller and / or AI engine to refine its predictions and control strategies based on feedback and new data, continuously enhancing the system's performance. Integration with renewable energy sources, such as solar panels, can further reduce the building's carbon footprint by using green energy to power the SRTU 100.

[0135] In some embodiments of the invention, the BMS data 116 may comprise a comprehensive array of information that is helpful for optimizing the performance of the SRTU 100. This data can include camera feed, which provides real-time visual monitoring of different areas within the building, enabling the detection of occupancy patterns, security incidents, or maintenance needs. Occupancy data indicates the presence and number of individuals in various zones, allowing the SRTU 100 to adjust ventilation and temperature settings dynamically to maintain comfort and air quality. Load requirement data includes the specific heating, cooling, and ventilation demands of different areas within the building, which are essential for balancing the HVAC load and preventing energy wastage.

[0136] Additionally, space usage data may offer insights into how different parts of the building are being utilized, which can influence HVAC zoning strategies and prioritize high-traffic areas. Energy consumption data tracks the real-time and historical usage of electricity, helping in identifying inefficiencies and potential savings opportunities. Indoor air quality metrics such as CO2 levels, particulate matter, and humidity may also be part of the BMS data, ensuring that the air remains healthy and comfortable for occupants. Environmental conditions, both internal and external, such as temperature, humidity, and weather forecasts, may be integrated to allow the SRTU 100 to anticipate and adjust to changing conditions proactively.

[0137] Furthermore, scheduling data, including planned events and peak usage times, may enable the SRTU 100 to prepare for variations in load and occupancy. Security system statuses, fire alarm triggers, and emergency signals may also be monitored, ensuring the HVAC system can respond appropriately during critical situations. By incorporating this diverse and detailed BMS data 116, the SRTU control system 112 can perform real-time optimization, predictive maintenance, and energy-efficient operations, enhancing the overall performance and sustainability of the building's HVAC system.

[0138] In some embodiments of the invention, the Controller and / or AI engine integrated within the SRTU control system 112 may be constructed to analyze trends and historical data to learn and predict periods of increased or decreased heating or cooling requirements. This capability may allow the SRTU 100 to adjust its operations proactively, providing optimal climate control and energy efficiency.

[0139] The Controller and / or AI engine may collect and examine extensive data sets that may include time-specific variables such as the time of day, day of the week, and month or season of the year. By analyzing these data points, the Controller and / or AI engine can identify patterns and trends in the building's HVAC usage. For example, the Controller and / or AI engine may detect that there is a consistently higher cooling demand in the late afternoon during summer weekdays, likely due to increased sunlight exposure and occupancy levels. Similarly, it may observe that heating requirements peak in the early mornings during winter months when temperatures are lower, and occupants are arriving at the building.

[0140] Once these patterns are identified, the Controller and / or AI engine uses this information to adjust the SRTU's operations accordingly. For example, on a hot summer day, the Controller and / or AI engine can pre-cool the building before peak occupancy times to maintain a comfortable indoor environment while avoiding the energy spike that may occur if the cooling system were to ramp up suddenly during high demand periods. Conversely, during winter mornings, the Controller and / or AI engine can initiate the heating system slightly earlier to ensure the building reaches the desired temperature by the time occupants arrive.

[0141] Furthermore, the Controller and / or AI engine may continuously refine its predictive model by incorporating new data, allowing it to adapt to changes in building usage patterns or external weather conditions. It can also factor in external data sources such as weather forecasts to anticipate and respond to sudden changes in environmental conditions, ensuring that the SRTU 100 operates efficiently regardless of external variables.

[0142] The Controller and / or AI engine's ability to predict and adjust for seasonal variations is also significant. For example, during spring and autumn, when temperature fluctuations are more common, the AI can switch between heating and cooling modes as needed throughout the day, maintaining consistent comfort levels without manual intervention. This proactive approach not only enhances occupant comfort but also maximizes energy efficiency by avoiding overuse of the HVAC system.

[0143] Additionally, the Controller and / or AI engine can integrate with other building systems through the BMS, receiving real-time occupancy and usage data. This integration may allow the AI to make more informed decisions based on the current and expected building usage, further optimizing the SRTU's performance. For example, if a large meeting is scheduled in a conference room, the AI can ensure that the room is pre-cooled or pre-heated to the appropriate temperature, providing comfort for the occupants.

[0144] In some embodiments of the invention, the Controller and / or AI engine integrated within the SRTU control system 112 may take into account the geographic location of the building to optimize heating and cooling operations. By considering the location, the Controller and / or AI engine can analyze and learn the specific climatic patterns and seasonal variations that impact the building's heating and cooling requirements. For example, a building located in a region with hot summers and mild winters will have different HVAC demands compared to a building in a colder climate. The Controller and / or AI engine can adjust the SRTU's operations based on these learned patterns to ensure efficient energy use and occupant comfort throughout the year.

[0145] Furthermore, the Controller and / or AI engine can detect and predict occupancy patterns based on scheduled events and typical building usage. For example, in an office building, the AI can analyze historical data to identify peak times when people are likely to arrive, such as weekday mornings, and times when the building is less occupied, such as evenings and weekends. By understanding these patterns, the Controller and / or AI engine can proactively adjust the SRTU's settings to pre-cool or pre-heat the building before occupants arrive, providing a comfortable environment from the moment they enter.

[0146] The Controller and / or AI engine can also integrate with the building's scheduling systems to predict occupancy based on planned meetings, conferences, or other events. For example, if a large meeting is scheduled in a conference room at 10 AM, the AI can ensure that the room is at the optimal temperature and ventilation level by the time the meeting starts. Conversely, during periods of low occupancy, such as lunchtime or after office hours, the AI can reduce heating or cooling to save energy while maintaining basic comfort levels.

[0147] By leveraging occupancy sensors and data from the BMS 115, the Controller and / or AI engine can continuously refine its predictions and adjustments. It can detect real-time changes in occupancy and respond accordingly. For example, if a large number of people unexpectedly gather in a particular area, the AI can increase ventilation and cooling to accommodate the additional heat load generated by the occupants.

[0148] Additionally, the Controller and / or AI engine considers external factors such as weather forecasts and real-time climate data. By predicting temperature fluctuations, humidity levels, and other environmental conditions, the AI can adjust the SRTU's operations to maintain indoor comfort while minimizing energy consumption. For example, on a day when a heatwave is forecasted, the AI can pre-emptively increase cooling capacity to ensure the building remains comfortable despite the extreme external temperatures.

[0149] In some embodiments, the Controller and / or AI engine within the SRTU control system 112 may utilize machine learning to optimize the defrosting process. By analyzing historical data, BMS data, SRTU data and real-time environmental conditions, the Controller and / or AI engine can predict the optimal times and conditions for initiating defrost cycles for the SRTU 100. It learns patterns related to frost accumulation, such as specific weather conditions or operational behaviors that lead to increased frost. Based on this knowledge, the AI can dynamically adjust the defrosting frequency and intensity, providing efficient frost removal without energy expenditure. This adaptive defrosting strategy enhances the overall performance and energy efficiency of the SRTU, preventing frost-related issues and maintaining consistent heating and cooling capabilities.

[0150] In some embodiments, the Controller and / or AI engine that powers the SRTU control system 112 may reside on a cloud-based server 114 itself. By leveraging the computational power and scalability of cloud infrastructure, the Controller and / or AI engine can process vast amounts of data collected from the SRTU 100, including thermal images, sensor data, and BMS inputs. Such a centralized approach may allow for more sophisticated analytics and machine learning models that continuously improve over time. The server-based Controller and / or AI engine can also integrate data from multiple SRTUs across different locations, providing a broader perspective and more robust predictive capabilities. Remote access to the Controller and / or AI engine via the cloud enables real-time monitoring, diagnostics, and updates, ensuring that the SRTU 100 operates at peak efficiency and reliability regardless of its physical location.

[0151] Referring now to FIG. 1B, an exemplary configuration of overlapping fields of view 120 for IR cameras 110A and 110B are illustrated. The cameras 110A and 110B are installed to capture comprehensive thermal images of the SRTU 100 from various directions and angles. These IR cameras are exemplary, and the system can accommodate one or several IR cameras to ensure thorough thermal monitoring of the SRTU 100.

[0152] The IR cameras 110A and 110B may capture different fields of view, each providing corresponding thermal perspectives of the SRTU 100. The overlapping fields of view 120 ensure that all important areas of the SRTU 100 are monitored, minimizing blind spots and providing a complete thermal profile. The captured thermal images are then analyzed by the Controller and / or AI engine, which may process these images to generate detailed heat maps or thermograms.

[0153] The Controller and / or AI engine may use the thermograms to identify specific points, such as 120A and 120B, where higher temperatures are detected (near the exhaust air 109). These points of varying temperature may indicate the operational conditions of the components inside the SRTU 100. For example, a consistently high temperature at point 120A may indicate an overheating compressor, while an elevated temperature at point 120B may signal a failing fan motor. By analyzing these thermal patterns, the Controller and / or AI engine can determine which components require attention or adjustment.

[0154] Additionally, the Controller and / or AI engine can correlate surface temperature data with the internal working conditions of the corresponding components within the SRTU 100. For example, if the exterior surface of the SRTU 100 shows unusual thermal hotspots, it may indicate internal components struggling to dissipate heat effectively, suggesting potential inefficiencies or impending failures. This correlation may allow the Controller and / or AI engine to make informed decisions about controlling the SRTU 100 to optimize its performance.

[0155] Moreover, the Controller and / or AI engine can proactively adjust the SRTU operations based on real-time thermal data. For example, if the thermograms indicate that a particular section of the SRTU 100 is consistently hotter than the rest, the AI can increase airflow to that section, initiate a targeted cooling cycle, or schedule maintenance checks to prevent component failure. This proactive approach may ensure better and more efficient cooling or heating as required, enhancing the overall reliability and lifespan of the SRTU 100.

[0156] The system may also integrate additional features, such as predictive maintenance alerts. By continuously learning from the thermal data, the Controller and / or AI engine can predict when components are likely to fail based on their thermal behavior patterns. This may allow for timely maintenance interventions, reducing unplanned downtime and operational disruptions.

[0157] Furthermore, the Controller and / or AI engine can utilize machine learning algorithms to refine its analysis over time. As it processes more thermal data, it becomes better at recognizing patterns and anomalies, improving its predictive accuracy. This adaptive capability may ensure that the SRTU 100 operates at peak efficiency, even as environmental conditions and usage patterns change.

[0158] In some embodiments, the Controller and / or AI engine within the SRTU control system 112 may analyze the thermograms of the exterior surface of the SRTU 100, where specific sections, points, and / or zones on the exterior surface may correlate with the internal components housed within the SRTU 100. The thermographic analysis may allow the Controller and / or AI engine to infer the operational status and condition of these internal components based on their thermal signatures (For example, 120A-120B) on the exterior surface. Components within the SRTU 100 may include, but are not limited to, compressors, evaporator coils, condenser coils, heating coils, cooling coils, filters, fan motors, electrical circuits, and heat exchangers.

[0159] For example, if the thermogram indicates an unusually high temperature in a zone corresponding to the compressor, this may signify that the compressor is operating under excessive load or is potentially failing. Similarly, thermal anomalies in areas correlating with the evaporator coils may suggest issues such as frost buildup, which may impede airflow and reduce efficiency. By identifying these thermal patterns, the Controller and / or AI engine can pinpoint which components require attention and perform automated adjustments to maintain optimal performance.

[0160] This thermal analysis may particularly be useful for managing defrost cycles. For example, if the thermogram shows consistent cold spots on the exterior surface where the evaporator coils are located inside, the Controller and / or AI engine can infer that frost is accumulating on these coils. Based on this data, the AI can initiate a defrost cycle to melt the frost and restore efficient heat exchange. By optimizing the timing and duration of defrost cycles based on real-time thermal data, the Controller and / or AI engine may ensure that the SRTU 100 operates efficiently, preventing excessive energy consumption and minimizing wear on components.

[0161] Furthermore, the Controller and / or AI engine's ability to correlate exterior thermal patterns with internal component conditions may allow for more targeted and effective maintenance strategies. It can prioritize maintenance tasks based on the severity and urgency of detected issues, ensuring that the most critical problems are addressed promptly. This proactive maintenance approach reduces the risk of unexpected failures and extends the lifespan of the SRTU components.

[0162] In some embodiments, when the Controller and / or AI engine resides on the cloud server 114, it can leverage historical data and trends from a multitude of sources, including numerous SRTUs, various thermograms, and extensive operational data. By aggregating and analyzing data from multiple SRTU units deployed across different locations and environments, the cloud-based Controller and / or AI engine can learn from a vast amount of diverse information. This comprehensive data set allows the AI to identify broader patterns and trends that may not be apparent from a single SRTU.

[0163] For example, the Controller and / or AI engine can compare thermograms from several SRTUs to determine common thermal signatures associated with specific component failures or inefficiencies. It can also analyze historical operational data to understand the effects of different environmental conditions, usage patterns, and maintenance practices on the performance of the SRTUs. By utilizing machine learning algorithms, the Controller and / or AI engine continuously refines its predictive models, enhancing its ability to forecast potential issues and optimize the performance of each SRTU.

[0164] This cloud-based approach may enable the Controller and / or AI engine to provide more accurate and reliable predictions, as it benefits from a wider range of data inputs. It can generate insights and recommendations that are informed by collective knowledge, leading to more effective and proactive maintenance strategies. Additionally, the cloud server's computational power allows for complex data processing and analysis, ensuring that the Controller and / or AI engine can handle the large volumes of data generated by multiple SRTUs efficiently.

[0165] Referring now to FIG. 1C, it illustrates an exemplary process where multiple thermal images (121A, 121B, 121C) may be combined to form a comprehensive single thermal image 121 for advanced AI analysis. Such an integration of thermal data from various perspectives may enhance the accuracy and depth of the thermal profile, allowing the Controller and / or AI engine to make more informed decisions regarding the operational state of the SRTU 100.

[0166] In such embodiments, the individual thermal images 121A, 121B, and 121C may be captured by IR cameras from different angles or positions around the SRTU 100. Each image may provide a unique view of the thermal characteristics of the unit, capturing specific details and temperature variations that may not be visible from a single vantage point. These images may then be combined into a single, unified thermal image 121, which offers a complete and detailed thermal map of the SRTU's exterior surface.

[0167] The Controller and / or AI engine may analyze this combined thermal image 121 to identify critical points and / or zones, such as 122A, 122B, and 122C, where significant temperature variations are detected. These points may indicate potential issues or areas that require attention. For example, a hotspot at 122A may suggest an overheating component, while a cold spot at 122B may indicate frost buildup. The Controller and / or AI engine can use this detailed thermal information to optimize the SRTU's performance, adjusting cooling or heating operations to maintain efficiency and prevent component failure.

[0168] Furthermore, a single IR camera can capture a continuous video stream for AI analysis. This continuous stream may provide real-time thermal monitoring, enabling the AI to detect and respond to dynamic changes in temperature more effectively. By capturing multiple frames over time, the IR camera can create a time-lapse thermal profile, which the AI can analyze to understand trends and patterns in the SRTU's thermal behavior. This real-time data is invaluable for proactive maintenance and operational adjustments.

[0169] For example, the Controller and / or AI engine can use the continuous video stream to monitor the defrost cycles of the SRTU 100. By analyzing the thermal changes during these cycles, the AI can determine the optimal timing and duration for defrost operations, ensuring that frost is effectively removed without wasting energy. Additionally, the AI can identify anomalies such as unexpected temperature spikes or drops, which may indicate emerging issues that need to be addressed promptly.

[0170] Moreover, the Controller and / or AI engine's ability to combine multiple images or frames may allow for more sophisticated analysis techniques. For example, it can employ image stitching algorithms to merge the thermal images seamlessly, creating a high-resolution composite image that retains the details and nuances of the individual frames. This composite image can then be processed using advanced machine learning models to detect subtle patterns and anomalies that may not be apparent in a single frame.

[0171] Referring now to FIG. 2, in an exemplary embodiment, the SRTU 100 is situated in its operational environment atop a building structure. The SRTU 100 may be encased within a protective housing, labeled as SRTU Casing 201, which may be mainly constructed from PPR with a protective outer layer that may consist of either a metallic or non-metallic substance as discussed in some embodiments of the invention. The casing 201 is constructed to shield the internal components of the SRTU 100 from various environmental elements.

[0172] The Solar Stress 203, depicted as a wavy arrow pointing towards the SRTU, signifies the impact of solar radiation on the unit 100. This aspect of the design acknowledges the need for the SRTU 100 to withstand prolonged exposure to sunlight, which can contribute to thermal stress and the potential degradation of material over time. Additionally, the unit 100 is also shown in the context of Snow and Rain 204 to illustrate the SRTU's 100 exposure to various forms of precipitation, necessitating a robust and weather-resistant design to ensure consistent operation through diverse, and potentially harsh, weather conditions. The FIG. 2 serves to underscore the SRTU's resilience and the effectiveness of its design in protecting against environmental stressors, aligning with the invention's objective to provide a durable, efficient, and environmentally conscious HVAC solution.

[0173] Solar stress 203 can cause significant temperature increases on the surface of the SRTU casing 201, potentially affecting the internal components' performance and efficiency. The invention may employ multiple infrared (IR) cameras installed around the SRTU 100 to monitor these temperature variations caused by solar exposure. The AI system may use this data to optimize the cooling load and other operational parameters to mitigate the impact of solar stress, providing efficient and reliable operation. The multiple IR cameras installed around the SRTU 100 may continuously monitor the surface for areas with excessive frost or moisture accumulation. The real-time thermal data enables the AI system to dynamically adjust defrost cycles and other control mechanisms to prevent ice buildup and ensure effective drainage, thus maintaining optimal performance and preventing weather-related damage.

[0174] In accordance with various embodiments of the present invention, the SRTU 100 may innovatively be constructed to offer enhanced protection and durability for HVAC systems. At the core of this invention is the use of Polypropylene Random Copolymer (PPR) as the primary material for the construction of the SRTU 100. PPR is selected for its notable characteristics, including its lightweight nature, structural strength, and resistance to environmental factors such as chemical corrosion and temperature variations. These properties make PPR an ideal choice for rooftop applications where exposure to diverse weather conditions is a constant challenge.

[0175] To further reinforce the SRTU 100 and safeguard its internal components, the PPR layer is coated with a protective layer (metallic or non-metallic layer), such as galvanized steel. This metallic coating or layer serves multiple important functions. Firstly, it acts as a robust barrier against environmental elements like rain, snow, and UV radiation, preventing direct contact with the PPR layer and thus averting potential material degradation over time. The galvanized steel coating is particularly effective in shielding the unit 100 from moisture-induced damage and corrosion, a common issue in metallic components exposed to the outdoors.

[0176] Secondly, the protective layer enhances the overall structural integrity of the SRTU 100. Galvanized steel, known for its strength and durability, provides additional rigidity to the unit 100, ensuring it remains stable and secure in various climatic conditions, including high winds or heavy snow loads. This added strength is important in maintaining the unit's shape and functionality over its lifespan.

[0177] Thirdly, the combination of PPR with a galvanized steel coating contributes to the thermal efficiency of the SRTU 100. The metallic layer reflects a significant portion of solar radiation, thereby reducing the heat absorbed by the unit 100. This reflection helps in maintaining a more stable internal temperature, which is beneficial for the optimal performance of the HVAC system housed within the SRTU unit 100.

[0178] In addition, the smooth surface of the galvanized steel coating facilitates easier maintenance and cleaning of the SRTU 100. With this case of maintenance, the unit can be kept in optimal condition, further extending its operational life and reliability. Overall, the use of PPR as the main structural layer, combined with an outer protective layer or coating, provides a superior solution for rooftop HVAC units. With this combination, the components within the SRTU 100 are well-protected from environmental elements, leading to a more durable, efficient, and reliable HVAC system.

[0179] Referring now to FIG. 2A, an exemplary view of a building HVAC system showcasing the interrelation between various components, including the SRTU 100. The SRTU 100 is depicted alongside other important elements of the HVAC system, namely the Air Handler Unit (AHU) 200 and the Air-Cooled Chiller 202. These components are typically found within the mechanical services area of a building's rooftop or a designated utility space. The Air Handler Unit 200 is responsible for the circulation and regulation of air throughout the building's interior spaces. It is typically connected to ductwork that distributes conditioned air through various zones and returns it to the AHU 200. The Air-Cooled Chiller 202 functions to remove heat from the indoor air through the refrigeration cycle, contributing to the cooling requirements of the HVAC system.

[0180] The SRTU 100, as part of this assembly, is strategically positioned to facilitate its role in the overall climate control process. Its construction from PPR with a protective outer layer is essential for withstanding the external rooftop environment, where it works in tandem with the AHU 200 and chiller 202 to provide efficient heating, cooling, and ventilation. The integration of these components into a cohesive system demonstrates the importance of each unit's design and placement in achieving optimal HVAC performance. The FIG. 2A illustrates the SRTU's 100 compatibility and functionality within a larger HVAC network, highlighting its significance in a comprehensive climate control solution for modern buildings.

[0181] The SRTU 100 may be constructed to handle localized cooling and heating needs, leveraging advanced infrared thermal imaging and AI integration to optimize performance, ensure real-time monitoring, and provide predictive maintenance. The SRTU 100 may monitor its own components and the immediate environment, adjusting its operations dynamically based on the data collected to maintain optimal indoor conditions.

[0182] The AHU 200 may be responsible for distributing conditioned air throughout the various floors. The AHU 200 is connected to the air distribution ducts that run vertically through the building, ensuring that each floor receives an adequate supply of conditioned air. The AHU 200 works in conjunction with the SRTU 100, receiving air that has been pre-cooled or pre-heated by the SRTU and further conditioning it before distributing it to the building's interior spaces.

[0183] The chiller 202 may serve as the primary cooling source for the entire HVAC system. It removes heat from the building's air and transfers it to the outside environment. The chiller 201 may operate by circulating a refrigerant through a series of coils, which absorb heat from the air passing over them. The cooled air is then directed to the AHU 200 for distribution. The integration of the chiller 202 with the AHU 200 and the SRTU 100 may ensure a cohesive and efficient cooling system.

[0184] Referring now to FIG. 3, an exemplary representation of the SRTU 300, with a focus on its modular design and component architecture. The modular SRTU 300 may be under the supervision of multiple infrared (IR) cameras constructed to capture comprehensive thermal images from various directions and angles to monitor and optimize the performance of the SRTU 300. The SRTU 300 is shown featuring multiple modular components, referred to as SRTU Casing Side Panels 303, which are integral to the present invention's innovative approach to HVAC system construction. These panels are part of the unit's 300 protective casing, with the SRTU Casing Top 301 and SRTU Casing End Panel 302, delineating the complete enclosure of the unit 300.

[0185] One or more external IR cameras 310 may strategically be installed on the building structure where the SRTU 300 is located. These cameras may be positioned to capture thermal images of the SRTU 300 from multiple directions and angles, providing a holistic view of the unit's surface temperature distribution. The external cameras 310 can monitor the entire surface of the SRTU 300, detecting any hotspots, cold spots, or unusual temperature variations that may indicate potential issues or inefficiencies.

[0186] Additionally, a plurality of internal IR cameras 310A and 310B may be installed within the SRTU 300 itself. These internal cameras may strategically be placed to capture thermal images of the components housed inside the SRTU 300, such as but not limited to, the heating coil, cooling coil, evaporator coils, filters, dampers, centrifugal EC fan, and other important elements. By capturing thermal images of the internal components, the system can monitor their operating temperatures in real-time, ensuring that each component is functioning within optimal temperature ranges.

[0187] The captured thermal images from both external and internal IR cameras may be transmitted to a control system comprising a processor, a memory storing instructions executable by the processor, and an artificial intelligence (AI) engine. The Controller and / or AI engine may process these thermal images to convert them into digital value patterns that represent the temperature distributions across the SRTU 300 and its components.

[0188] Using advanced algorithms, the Controller and / or AI engine may analyze these digital value patterns or the heat signatures to identify zones and / or spots that may indicate operational inefficiencies, equipment failures, or potential maintenance needs. For example, if a particular component exhibits consistently high temperatures, the Controller and / or AI engine may flag this as an anomaly, suggesting that the component is under excessive stress or nearing failure.

[0189] Based on the analysis of the thermal images, the Controller and / or AI engine can control the SRTU 300 by adjusting operational parameters such as fan speed, damper positions, and heating or cooling cycles to optimize performance. For example, if the Controller and / or AI engine detects that certain areas or components of the SRTU 300 are overheating, it can increase airflow to those areas to dissipate heat more effectively.

[0190] Furthermore, the Controller and / or AI engine can also predict future maintenance needs and operational adjustments by continuously learning from the thermal data and historical performance trends. In addition to real-time control and predictive maintenance, the Controller and / or AI engine can also provide automated design suggestions to improve the performance of the SRTU 300. By analyzing thermal patterns and performance data, the Controller and / or AI engine can recommend modifications to the design of certain components or the overall structure of the SRTU 300. These suggestions may include replacing a component with a more efficient one, redesigning airflow pathways, or adjusting the placement of internal components for better thermal management.

[0191] The Controller and / or AI engine may also integrate data from the BMS, considering factors such as building occupancy, usage patterns, and geographic location. This integration may allow the Controller and / or AI engine to tailor its recommendations and control strategies to the specific needs and conditions of the building, ensuring that the SRTU 300 operates optimally within its unique environment.

[0192] The modular components 303 are constructed to facilitate easy assembly and disassembly, which is essential for efficient transportation, installation, and repair. The modularity allows for the SRTU 300 to be disassembled into manageable sections, making it easier to transport the unit 300 to the installation site, particularly when space constraints or access limitations are present. This design feature significantly reduces logistical challenges and costs associated with moving large, unwieldy equipment. Once on-site, the modular nature of the SRTU 300 simplifies the installation process as well. Technicians can quickly assemble the unit 300 piece by piece, which is especially advantageous in rooftop applications where time and space are at a premium. The ability to add or remove modular components also provides flexibility in system configuration and the potential for future expansion or reconfiguration as building needs evolve.

[0193] Furthermore, the modular design enhances the serviceability of the SRTU 300. Maintenance personnel can easily access internal components by removing specific panels, facilitating timely repairs and routine service checks without the need for complete system disassembly. This not only minimizes downtime but also extends the life of the unit by ensuring that all components are readily accessible for maintenance. The modular panels 301-303 of the SRTU 300 allow for a more streamlined and cost-effective lifecycle of the unit 300, from transportation and installation to operation and maintenance, reflecting the adaptability and user-friendly design.

[0194] In some embodiments, the Controller and / or AI engine integrated to the SRTU 300 ay also suggest automated designs for the modular components 303. By analyzing the thermal images captured by the IR cameras, the Controller and / or AI engine identifies thermal patterns and inefficiencies that can be addressed through design modifications. The Controller and / or AI engine may leverage advanced machine learning algorithms and historical performance data to propose optimal configurations for the modular components 303. These suggestions may include adjustments to the size, shape, and material composition of the components 303 to enhance thermal management and airflow efficiency. Additionally, the Controller and / or AI engine can recommend the integration of new materials or technologies that improve the overall performance and durability of the SRTU 300. By continuously learning from operational data and adapting to changing conditions, the Controller and / or AI engine may ensure that the modular components 303 are constructed to meet the specific needs of the HVAC system, thereby maximizing energy efficiency and operational effectiveness.

[0195] In some embodiments of the invention, the SRTU 300 is distinguished by its modular design, featuring an array of interlocking panels, including the SRTU Casing Top 301, the SRTU Casing End Panel 302, and multiple SRTU Casing Side Panels 303. Each panel is constructed as an individual module that can be swiftly assembled or disassembled, providing unparalleled adaptability and ease of maintenance.

[0196] Unique features of this modular design may include specialized sealing mechanisms between panels that may enhance the unit's weather resistance, ensuring that each join is both secure and impervious to environmental elements. This sealing technique may not only protect the interior components of the SRTU 300 but also simplify the process of replacing or repairing individual module panels 301-303 without disturbing the integrity of the entire unit 300.

[0197] Another innovative aspect of the SRTU's modular panels may be their construction with integrated insulation materials that enhance the unit's energy efficiency. These materials may be embedded within the panels themselves, thereby maintaining the SRTU's comparatively lightweight characteristic while optimizing thermal efficiency.

[0198] The modular panels may also be constructed with acoustic dampening properties to reduce operational noise, a feature that is increasingly important in urban or residential areas. Furthermore, the exterior surfaces of the panels may be treated with a reflective coating to minimize solar heat gain, further contributing to the unit's overall energy efficiency.

[0199] For added functionality, certain modular panels within the SRTU may be equipped with quick-release mechanisms that allow for rapid access to the interior of the unit for maintenance or emergency repairs. These quick-release mechanisms are constructed to be operated without specialized tools, emphasizing case of use and efficiency.

[0200] Referring now to FIG. 4, an exemplary SRTU control system 112 providing automated design suggestions for the SRTU (100 or 300) to improve its performance, is illustrated. The SRTU control system 112 is equipped with a Controller and / or AI engine that analyzes thermal images captured by one or both the internal IR cameras and external IR cameras to optimize the design and operation of the SRTU. The thermal images provide real-time data on temperature distributions across the SRTU's surface and internal components, enabling the Controller and / or AI engine to make informed design recommendations.

[0201] As shown in FIG. 4, the SRTU control system 112 may provide a comprehensive suggested design 400 for an SRTU. This suggested design 400 may leverage detailed analysis of one or more of: thermal images captured by both one or both the internal IR cameras and external IR cameras, the BMS data, SRTU operational data, sensor data, environmental data, and the geographic location of the building. The Controller and / or AI engine may process this comprehensive data and propose design modifications to enhance the overall performance and efficiency of the SRTU.

[0202] The external IR cameras, strategically installed on the building structure, capture thermal images of the SRTU from various angles and / or directions. These images provide a holistic view of the surface temperature distribution, allowing the Controller and / or AI engine to detect hotspots, cold spots, and other temperature anomalies. The internal IR cameras, positioned within the SRTU, focus on internal components such as the heating coil, cooling coil, evaporator coil, filters, dampers, EC fans, and other important elements. These cameras monitor the real-time operational temperatures of these components, ensuring they are functioning within optimal ranges (as discussed in FIG. 3 above).

[0203] The Controller and / or AI engine may process the thermal images to generate digital value patterns representing the temperature distributions across the SRTU's surface and internal components. By analyzing these patterns, the Controller and / or AI engine can identify areas where heat or frost buildup occurs, components that are overheating, and zones with insufficient cooling or airflow. Based on this analysis, the Controller and / or AI engine may provide design suggestions to address these issues.

[0204] For example, Controller and / or AI engine may recommend a tubular SRTU 400, with no flat surfaces. This design may enhance aerodynamic properties, reduce air resistance, and improve airflow efficiency. The tubular shape may help in minimizing turbulence and pressure drops, leading to more efficient operation of the HVAC system. The suggested tubular SRTU 400 may be based on a detailed analysis of thermal images and operational data to enhance the overall performance and efficiency of the SRTU.

[0205] The tubular design of the SRTU 400 may offer several key advantages over traditional rectangular or box-shaped units. The tubular form may minimize air resistance and turbulence, which are common issues with flat surfaces. By having a streamlined, rounded shape, the SRTU 400 may facilitate smoother airflow both around and within the unit. This reduction in air resistance may lead to more efficient operation of the HVAC components, as the airflow is less obstructed, and the pressure drops are minimized.

[0206] The tubular SRTU 400 placed on the roof 401 of a building comprises a smooth, tubular exterior with no flat surfaces. The tubular design may particularly be beneficial in maintaining high hygiene standards, as it eliminates corners and crevices where dirt and contaminants can accumulate. The smooth surfaces also facilitate easy cleaning and maintenance, ensuring that the unit 400 can be kept in a pristine condition, which is important for environments where cleanliness is paramount, such as hospitals, laboratories, and food processing facilities.

[0207] In terms of thermal management, the tubular design may help distribute thermal loads more evenly across the unit's surface. Traditional flat surfaces can create hotspots where heat accumulates, leading to inefficiencies and potential component overheating. The curved surfaces of the tubular SRTU 400 allow for better heat dissipation and more uniform temperature distribution. The Controller and / or AI engine, through thermal imaging analysis, can identify areas where heat tends to build up and suggest this tubular form to mitigate such issues.

[0208] Additionally, the tubular shape may also enhance the structural integrity and durability of the SRTU 400. The rounded design can better withstand external environmental stressors such as wind, rain, and debris, compared to flat surfaces that can create points of weakness or catch wind, leading to structural damage over time. This makes the tubular SRTU 400 more robust and long-lasting, particularly in harsh weather conditions.

[0209] The Controller and / or AI engine's recommendations may also include optimizing the internal layout of the SRTU 400. By placing components like the heating coil, cooling coil, dampers, and fans along the inner circumference of the tubular structure, the Controller and / or AI engine enables these components to benefit from the enhanced airflow and temperature regulation. Furthermore, the Controller and / or AI engine may take into account the ease of maintenance and accessibility in its design recommendations. The tubular SRTU 400 can be constructed with modular sections that allow easy access to internal components for maintenance, repairs, or upgrades.

[0210] Furthermore, the Controller and / or AI engine may also consider, in addition to thermal images, the BMS data, SRTU operational data, sensor data, environmental data, and the geographic location of the building to generate additional automated suggestions, including but not limited to:

[0211] Optimized Airflow Pathways: The Controller and / or AI engine may suggest specific pathways for supply air and return air to optimize airflow. The supply air is delivered through a duct pipe 402, while the return air is channeled through a duct pipe 403. The Controller and / or AI engine may recommend the appropriate diameters for these duct pipes (e.g., diameter 402A for supply air and diameter 403A for return air) based on the AI analysis of airflow patterns and pressure balance. Additionally, the Controller and / or AI engine may propose the use of advanced materials for the duct pipes (402-403), such as lightweight, high-durability composites or insulated materials to minimize thermal losses and reduce energy consumption. The Controller and / or AI engine may also recommend specific duct designs, such as smooth interior surfaces to reduce friction and enhance airflow efficiency, or flexible ducting to accommodate dynamic building layouts and reduce installation complexity.

[0212] Strategic Component Placement: The Controller and / or AI engine may provide recommendations for the placement of internal components 404 housed within the SRTU 400. By analyzing one of more of the comprehensive data (thermal images, the BMS data, SRTU operational data, sensor data, environmental data, and the geographic location of the building), the AI can identify areas where components may be overheating or not receiving adequate cooling. For example, if the cooling coil exhibits higher temperatures in certain areas, the Controller and / or AI engine may suggest repositioning it to improve airflow and enhance cooling efficiency. Similarly, the AI may recommend relocating the heating coil or the centrifugal EC fan to optimize their performance based on thermal data or the comprehensive data.

[0213] Enhanced Insulation and Material Selection: The Controller and / or AI engine may suggest modifications to the insulation and materials used in the SRTU 400. For example, it may recommend additional insulation in areas where heat loss is detected or suggest materials with better thermal conductivity for components that require efficient heat dissipation. These recommendations may help in maintaining optimal internal temperatures and improving energy efficiency.

[0214] Adaptive Control AI gorithms: The Controller and / or AI engine not only provides design suggestions but may also recommend adaptive control algorithms to dynamically adjust the operation of the SRTU 400. These algorithms may take into account real-time data from the IR cameras and other data, adjusting fan speeds, damper positions, and heating / cooling cycles to maintain and / or improve optimal conditions. In some embodiments, the Controller and / or AI engine may update its machine learning algorithm to dynamically adjust the operation of the SRTU 400.

[0215] Predictive Maintenance and Future Upgrades: The Controller and / or AI engine's analysis may extend to predicting future maintenance needs and suggesting design upgrades. By continuously monitoring thermal patterns and performance data, the Controller and / or AI engine can identify components that may require maintenance or replacement soon. It can also recommend design upgrades to accommodate future HVAC demands, ensuring the SRTU 400 remains efficient and reliable over time.

[0216] In some embodiments, the Controller and / or AI engine may consider data from the BMS, which may include occupancy patterns, usage schedules, and geographic location. By integrating this data, the AI can tailor its design recommendations to the specific needs of the building. For example, in areas with high occupancy during certain hours, the AI may suggest enhancing cooling capacity or optimizing airflow to those zones.

[0217] In some embodiments of the present invention, the Controller and / or AI engine integrated within the SRTU control system may provide automated design suggestions to enhance the overall efficiency and performance of the SRTU. For example, based on the analysis of airflow patterns and thermal distributions, the Controller and / or AI engine may suggest redesigning the internal layout of the SRTU to optimize the placement of key components such as the heating coil, cooling coil, and centrifugal electronically commutated (EC) fan. It may recommend repositioning these components to areas with better airflow or less thermal stress, thereby enhancing their performance and lifespan.

[0218] Referring now to FIG. 4A, an exemplary Smart Rooftop Unit (SRTU) 400A is shown, which includes a variety of internal components, strategically designed and positioned to optimize the performance and efficiency of the HVAC system. The SRTU control system 112, equipped with an AI engine provides automated design suggestions for the arrangement and operation of the internal components. The system leverages real-time data, historical performance metrics, and advanced analytics to continually refine the design and functionality of the SRTU 400A.

[0219] The supply air 406 and return air 407 channels are integral to the SRTU's operation, facilitating the movement of air through the system to be heated or cooled as required. The control system 112 may suggest specific pathways and diameters for these ducts to maximize airflow efficiency and minimize pressure loss. For example, the diameter of the supply air duct 406 may be adjusted to allow optimal delivery of conditioned air to the occupied spaces, while the diameter of the return air duct 407 may be optimized to facilitate efficient air recirculation.

[0220] The outer surface 414 of the SRTU 400A may be designed from PPR to be robust and weather-resistant, protecting the internal components from environmental factors. The AI engine may recommend using specific materials or coatings for the surface 414, such as UV-resistant polymers or corrosion-resistant metals, depending on the geographic location and environmental conditions of the installation site. The control system 112 may provide suggestions on the optimal placement and orientation of the SRTU 400A on a roof 417 to enhance airflow dynamics and ease of maintenance.

[0221] The initial filter 416 is the first line of defense against airborne contaminants, capturing large particles and debris before they enter the SRTU. The control system 112 may suggest the type of filter media and the replacement schedule to maintain optimal air quality and system performance.

[0222] The heating and cooling coils 405 are crucial for temperature regulation within the SRTU 400A. The AI engine can analyze thermal images and operational data to suggest improvements in the coil design, such as enhancing the fin density or adjusting the coil size, to improve heat exchange efficiency and reduce energy consumption.

[0223] Additional filters 410 may maintain air quality by removing particulates and contaminants from the air stream. The AI engine can recommend the type and configuration of these filters based on the specific needs of the building and the external environment. For example, in areas with high pollution levels, the system 112 may suggest using high-efficiency particulate air (HEPA) filters for superior air quality.

[0224] The mixing damper 412 provides for blending return air with fresh outdoor air to maintain indoor air quality and comfort. The control system 112 may suggest optimal damper positions and operational schedules to balance energy efficiency with ventilation requirements, allowing that the indoor environment remains comfortable while minimizing energy use.

[0225] Filter 418 may serve as an additional layer of air purification, allowing that the air entering the SRTU 400A is free from harmful particulates. The AI engine may also recommend the placement and maintenance schedule for the filter 418 to maximize its effectiveness and lifespan.

[0226] The heat wheel 413 provides for energy recovery, capturing heat from the exhaust air and transferring it to the incoming fresh air. The AI engine may provide suggestions for optimizing the heat wheel's design and operation, such as adjusting the rotational speed or enhancing the material properties, to improve energy recovery efficiency.

[0227] The exhaust fan 415 and exhaust damper 411 work together to expel stale air from the building while managing the internal pressure and airflow. The AI engine can analyze airflow patterns and recommend optimal fan speeds and damper positions for efficient ventilation and pressure balance within the building.

[0228] The centrifugal electronically commutated (EC) fan 409 is responsible for moving air through the SRTU 400A. The AI engine can monitor the fan's performance and provide recommendations for speed adjustments and maintenance schedules for efficient and reliable operation.

[0229] The compressor chamber 408 houses the components necessary for the refrigeration cycle, including the compressor and associated control mechanisms. The AI engine may analyze operational data and thermal images to suggest improvements in compressor efficiency, such as optimizing the refrigerant charge or adjusting the compressor speed.

[0230] In some embodiments, the SRTU control system 112 may provide automated suggestions for the design and operation of the air hood and grille. By analyzing thermal images captured by IR cameras, along with real-time airflow and pressure data, the AI engine can optimize the shape and placement of the air hood to ensure maximum intake efficiency and minimal resistance. For the grille, the AI engine may recommend the most effective design to distribute air evenly and reduce noise levels, as well as suggest materials that minimize debris accumulation and are easier to maintain. These automated suggestions may help in enhancing the overall performance and longevity of the SRTU.

[0231] Referring now to FIG. 5, it illustrates an exemplary SRTU system integrating an SRTU 500 with an IR camera 510 and a BMS 501, in accordance with some embodiments of the present invention. The SRTU 500 may be constructed to provide advanced HVAC functionality through intelligent monitoring and control mechanisms.

[0232] The SRTU 500 may include a control panel 502, which comprises the Controller and / or AI engine responsible for analyzing data and optimizing the operation of the unit. The Controller and / or AI engine processes information from various sources, including the IR camera 510 and the BMS 501, to ensure efficient and reliable performance.

[0233] The IR camera 510 may be positioned to capture thermal images of the SRTU 500. It continuously monitors the thermal profile of the unit, providing real-time data on temperature variations across different components inside the SRTU 500. The thermal imaging capability may allow the Controller and / or AI engine within the control panel 502 to detect anomalies, such as overheating or inefficient cooling, and take corrective actions promptly.

[0234] The SRTU 500 may be equipped with an air hood 504, which directs air intake into the system. The air hood 504 may ensure that the air entering the unit is properly channeled for optimal cooling or heating, contributing to the overall efficiency of the SRTU.

[0235] The BMS 501 may provide helpful data to the SRTU 500 via BMS signals 503. This data may include internal temperatures, occupancy levels, energy usage patterns, and other relevant metrics as discussed in various embodiments of the present invention. By integrating with the BMS 501, the Controller and / or AI engine in the control panel 502 can adjust the SRTU's operations based on real-time conditions and historical trends. For example, if the BMS indicates that a specific zone in the building is experiencing high occupancy and increased temperature, the Controller and / or AI engine can boost cooling in that area to maintain comfort.

[0236] The BMS signals 503 allow for seamless communication between the SRTU 500 and the BMS 501. This integration may enable the Controller and / or AI engine to consider a wide range of factors when making operational decisions, such as adjusting airflow, initiating defrost cycles, or modifying temperature settings based on occupancy patterns and energy usage trends within the building.

[0237] The control panel 502, equipped with the Controller and / or AI engine, may serve as the central hub for processing all incoming data. It can dynamically adjust the SRTU's settings to optimize performance, reduce energy consumption, and extend the lifespan of the unit. The Controller and / or AI engine's capabilities may include predictive maintenance, where it analyzes data trends to forecast potential issues and schedule maintenance activities proactively.

[0238] Furthermore, the Controller and / or AI engine can leverage historical data from both the IR camera 510 and the BMS 501 to refine its algorithms continually. This continuous learning process allows the SRTU 500 to adapt to changing conditions and improve its efficiency over time.

[0239] The function of the Air Hood 504 is to optimize the introduction of ambient air into the SRTU, leveraging cooler external temperatures to reduce the load on the cooling system, thereby enhancing energy efficiency. This is particularly advantageous during periods when the outside air is sufficiently cool to assist in meeting the cooling requirements of the building without the need for the unit to engage its full refrigerative cooling capabilities.

[0240] In keeping with the innovative aspects of the invention, the Air Hood 504 may be equipped with a series of environmental sensors. These sensors can detect not only temperature but also humidity levels, air quality, and the presence of contaminants. This real-time environmental data allows the SRTU 500 to intelligently determine whether to utilize the economizer mode (of the Economizer Hood 104 or Air Hood 504), wherein the unit increases the use of outdoor air to conserve energy.

[0241] Furthermore, the modular nature of the Air Hood 504 suggests that it may be constructed for easy removal and attachment, facilitating maintenance and potential upgrades. The hood's design may also include adjustable louvers or dampers, which can be automatically or manually adjusted to control the volume and direction of the incoming air, providing optimal performance under varying environmental conditions.

[0242] In some embodiments, the Controller and / or AI engine may provide automated design suggestions specifically for the Air Hood 504. Based on the detailed analysis of thermal images and BMS data, the Controller and / or AI engine can optimize the design and functionality of the Air Hood to enhance the overall performance and efficiency of the SRTU 500.

[0243] For example, Air Hood suggestion 504A may involve modifying the shape and orientation of the Air Hood 504 to improve the intake of ambient air. The Controller and / or AI engine may recommend a more aerodynamic design that reduces air resistance and turbulence, providing smoother and more efficient airflow into the SRTU 500.

[0244] Air Hood suggestion 504B may focus on integrating advanced filtration systems within the Air Hood 504B. Based on the Controller and / or AI engine's analysis of air quality data and particulate levels, it may suggest incorporating high-efficiency particulate air (HEPA) filters or electrostatic precipitators within the Air Hood 504B. These filters can effectively remove airborne contaminants and particulate matter from the incoming air, ensuring that only clean air enters the SRTU 500.

[0245] Additionally, the Controller and / or AI engine may propose the use of smart materials and coatings for the Air Hood 504. For example, it may suggest applying a hydrophobic coating to prevent water accumulation and reduce the risk of corrosion. AI ternatively, the Controller and / or AI engine may recommend using lightweight, high-durability composites that improve the structural integrity of the Air Hood while minimizing weight.

[0246] The Controller and / or AI engine also considers external factors such as environmental conditions and building-specific requirements. By analyzing data from the BMS 501, the Controller and / or AI engine can tailor its design suggestions to optimize the Air Hood 504 for specific climatic conditions, seasonal variations, and occupancy patterns. For example, in regions with high humidity, the Controller and / or AI engine may recommend integrating moisture control features to prevent condensation and improve overall air handling efficiency.

[0247] Furthermore, the Controller and / or AI engine's suggestions can be adaptive and dynamic. It continuously monitors the performance of the Air Hood 504 and provides real-time adjustments based on changing conditions. For example, if the AI detects increased particulate levels or changes in ambient air quality, it may recommend adjusting the filtration settings or implementing additional airflow control measures to maintain optimal performance. In some embodiments, the Controller and / or AI engine may automatically adjust the filtration settings and implement additional airflow control.

[0248] In some embodiments of the invention, the Economizer Hood 104 (or 504) may be constructed with an aerodynamic shape to maximize air intake efficiency while reducing drag, thus minimizing the load on the SRTU's internal fans and conserving energy.

[0249] The Economizer Hood may be constructed from a durable, weather-resistant material compatible with or similar to the rest of the SRTU's casing. It may be constructed to pivot or adjust its opening based on real-time sensor data, effectively capturing optimal air quantities while preventing the entry of debris or precipitation. This dynamic adjustability may be controlled by an intelligent mechanism that responds to changes in outdoor air conditions, such as temperature, humidity, and air quality.

[0250] Within the Economizer Hood (104), a series of high-efficiency filters can be integrated to clean incoming air of particulates and pollutants. These filters are easily accessible for maintenance and can be interchanged with different filtration grades depending on the specific environmental requirements of the installation site.

[0251] Furthermore, the Economizer Hood may include a built-in thermal exchange system, wherein incoming cooler air assists in pre-cooling the refrigerant or air streams within the SRTU, enhancing the unit's overall energy efficiency. This feature is particularly advantageous during transitional seasons when the external air temperature is lower than the indoor air temperature, allowing for natural cooling without engaging the unit's compressor.

[0252] In addition, the Economizer Hood may feature solar-reflective surfaces or coatings to prevent excessive heat absorption, and it may be insulated to maintain the desired temperature of the incoming air. The embodiment may also encompass a smart actuation system that allows the hood to be closed completely, securing the SRTU when outdoor conditions are unfavorable, or when the unit is not in use, thus protecting internal components.

[0253] Referring now to FIG. 5A, an exemplary embodiment of an SRTU system in accordance with the present invention is illustrated. The SRTU 500 may be strategically installed on the rooftop of a building 511. The building 511 may be equipped with a plurality of cameras 512 positioned both inside and outside of the building 511 to capture various activities within and around the building 511. The cameras 512 may be placed to monitor areas such as parking slots 513, people 514 entering and exiting the building 511, and vehicles 515 coming in and out of the premises.

[0254] The images or video feeds captured by these cameras 512 are transmitted to the Building Management System (BMS) 501. The BMS 501 acts as a central hub, collecting and processing the visual data from the cameras 512 and various sensors installed within the building. This data may then be sent to the SRTU control system 502. The control system 502 is equipped with a Controller and / or AI engine that analyzes the visual data in conjunction with other data sources, such as thermal images captured by the IR cameras 510 installed on, around and / or within the SRTU 500.

[0255] The Controller and / or AI engine may use the visual data (images or video feed from cameras 512) to monitor and predict occupancy patterns, vehicle movements, and the influx and outflow of people 514. This information is used for optimizing the HVAC system's performance. For example, the Controller and / or AI engine can adjust the ventilation and air conditioning settings based on the number of people entering the building 511. If a large number of people 514 are detected entering the building 511, the AI can anticipate an increased cooling demand and adjust the SRTU 500 operations accordingly to maintain optimal indoor temperatures.

[0256] Similarly, the cameras 512 monitoring the parking slots 513 may provide data on vehicle occupancy, which can be used to predict peak times for HVAC system usage. The Controller and / or AI engine can use this information to pre-cool or pre-heat the building spaces based on expected occupancy levels, thereby improving energy efficiency and comfort.

[0257] Additionally, the thermal images captured by the IR camera 510 may provide real-time temperature data of the SRTU 500 components. This data is analyzed by the Controller and / or AI engine to detect any anomalies or inefficiencies in the system. The AI can adjust the operation of the SRTU components, such as the heating and cooling coils, fans, and dampers, to optimize performance based on the thermal signatures.

[0258] In some embodiments of the present invention, the Controller and / or AI engine within the SRTU control system 502 may be constructed to learn and analyze patterns of occupancy within the building 511 by continuously monitoring the data captured by the plurality of cameras 512 installed both inside and outside the building 511.

[0259] The Controller and / or AI engine may process the visual data (captured by cameras 512) to identify trends and patterns in building occupancy. By analyzing historical data, the Controller and / or AI engine can determine specific times of the day, days of the week, and seasons when the building 511 experiences higher or lower occupancy levels. For example, the AI may learn that occupancy peaks during weekday mornings and afternoons, coinciding with typical office hours, and that there is a significant drop in occupancy during weekends and holidays.

[0260] Additionally, the Controller and / or AI engine can identify seasonal variations in occupancy. For example, it may detect increased occupancy during the winter months or during the summer when special programs or events are held. By recognizing these patterns, the Controller and / or AI engine can anticipate HVAC demands more accurately.

[0261] Based on these learned patterns, the Controller and / or AI engine optimizes the operation of the SRTU 500 to align with predicted occupancy levels. During times of expected high occupancy, the Controller and / or AI engine can pre-emptively adjust the HVAC settings to ensure that the building 511 is comfortably cooled or heated. Conversely, during periods of low occupancy, the Controller and / or AI engine can scale back the HVAC operation to conserve energy, thereby improving overall efficiency.

[0262] In some embodiments, if the building 511 is a warehouse, the Controller and / or AI engine can intelligently control the SRTU components based on the vehicles 515 entering or exiting the building 511. The plurality of cameras 512 installed around the warehouse monitor the movement of vehicles 515, capturing images and video feeds that are sent to the BMS 501 and subsequently to the SRTU control system 502.

[0263] The Controller and / or AI engine (within the SRTU control system 502) processes this data to identify patterns in vehicle activity. For example, the Controller and / or AI engine may detect specific times of day when delivery trucks or forklifts are most active, indicating periods of high activity within the warehouse. It can learn these patterns over time, noting peak hours for deliveries and shipments.

[0264] Based on this analysis, the Controller and / or AI engine can make real-time adjustments to the SRTU 500 and its components to optimize the indoor climate of the warehouse. For example, when a high volume of vehicles 515 is detected entering the warehouse, the Controller and / or AI engine can increase the airflow and adjust the cooling or heating settings to compensate for the additional heat or cold brought in by frequent door openings.

[0265] In scenarios where vehicles 515 are frequently exiting the warehouse, such as during the dispatch of goods, the Controller and / or AI engine can reduce the cooling or heating load to save energy, knowing that doors will be opened less frequently. This dynamic adjustment based on vehicle activity helps maintain optimal conditions within the warehouse while improving energy efficiency and reducing operational costs. Moreover, the Controller and / or AI engine can integrate this data with other environmental sensors within the warehouse, such as temperature, humidity, and air quality sensors, to further refine the control of the SRTU components.

[0266] Referring now to FIG. 6, an exemplary view of the internal configuration of the SRTU 600, which may align with the innovative principles of the present invention. The depiction showcases the various components of the SRTU 600 and their functions, emphasizing the unit's efficiency and environmental adaptability.

[0267] The journey of air through the SRTU 600 begins at the Air Hood 604, an intelligently constructed intake system that may be equipped with environmental sensors for detecting temperature, humidity, and pollutant levels. The data from these sensors enables the SRTU 600 to adjust the volume and temperature of the incoming air, optimizing the unit's energy usage.

[0268] Air passes through the Damper 605, which is a controllable gate dictating airflow into the system, allowing the SRTU 600 to respond to varying ventilation needs dynamically. The initial Filter 606, possibly a high-efficiency particulate air (HEPA) filter, traps fine particles from the incoming air, which facilitates the maintenance of high indoor air quality.

[0269] The Heat Wheel 603 is a pivotal energy recovery component that may capture thermal energy from the exhaust air and transfer it to the incoming fresh air or vice-versa. This process significantly reduces the energy required to bring the incoming air to a comfortable temperature.

[0270] Subsequent Filters 602 provide an additional level of air purification before the air reaches Fan 601. The fan 601, constructed for variable speed operation, circulates air through the SRTU 600 efficiently, adapting to the system's current load, further contributing to energy savings.

[0271] The Exhaust system, comprised of the Exhaust Damper 605 and the Exhaust Fan 609, manages the removal of indoor air through the Grille 607. The grille 607 design may be adjustable, allowing for directional control of the airflow to distribute the indoor air outside the building. The damper 605 adjusts the amount of air being expelled, maintaining the building's pressure balance and air quality.

[0272] The Filter 610, positioned strategically within the airflow pathway, may serve a dual-purpose role in some embodiments of the invention. While it may primarily act to purify the air being circulated into the building, providing a clean and healthy indoor environment, it may also be constructed to filter the exhaust air leaving the building. This unique feature may ensure that the SRTU 600 not only protects the internal environment from external pollutants but also minimizes the HVAC system's environmental footprint by cleaning the air before it is released back into the atmosphere.

[0273] The Mixing Damper 611 of the SRTU 600 may be constructed to regulate the blend of fresh outdoor air with the return indoor air within the system. The damper 611 may adjust the proportions of air mixed based on the optimal requirements for indoor air quality and temperature control. Its operation is central to the SRTU's energy efficiency, as it can reduce the need for heating or cooling through the Heating / Cooling Coil 612 by taking advantage of the desired properties of the air streams. For example, during cooler periods, the damper 611 can allow more warm return air to mix with the cooler fresh air to minimize the heating requirements. The Heating / Cooling Coil 612 adjusts the air temperature to a desired level. The coil's operation is responsive, with the ability to switch between heating and cooling to maintain consistent indoor conditions.

[0274] In some embodiments of the present invention, the atmospheric air is processed through the SRTU 600 by first passing through the air hood 604, then the damper 605, followed by the filter 606, the heat wheel 607, and additional filters 602, creating an atmospheric conveyance channel towards that heating coil or the cooling coil 612. This atmospheric conveyance channel then directs the air through either the heating coil or the cooling coil 612, or both, depending on the system's requirements. The movement of atmospheric air through this channel is controlled by the operation of the centrifugal electronically commutated fan 601, which adjusts its speed to ensure efficient air distribution and optimal temperature regulation.

[0275] In some embodiments of the invention, each part of the SRTU 600 may be constructed to work in concert, creating an integrated system that prioritizes energy efficiency, environmental impact, and air quality. The unit's modular design further facilitates easy maintenance and replacement of individual components. Further, unique features of this SRTU 600 may include smart diagnostic systems that monitor the performance of each component and alert maintenance personnel of potential issues before they arise. Additionally, the use of advanced composite materials for components like dampers and filters can further enhance durability and performance while maintaining the comparatively lightweight nature of the unit.

[0276] Furthermore, an IR camera 615 can be strategically installed on the roof where the SRTU 600 is placed, providing a comprehensive vantage point to capture thermal images of the entire unit. This placement may ensure that the IR camera can monitor the surface temperature of the SRTU 600 accurately, detecting heat signatures that correlate with the internal components' performance. By analyzing these thermal images, the Controller and / or AI engine can identify potential issues, optimize operations, and schedule maintenance activities proactively, ensuring the SRTU 600 operates efficiently and reliably. For example, the heat signatures captured on the SRTU's surface above the location of the Heat Wheel 603, or the Heating / Cooling Coil 612 can provide insights into their operational status. High temperatures at these spots may indicate excessive load or potential malfunction, prompting the Controller and / or AI engine in the control panel to adjust the SRTU's operations or initiate maintenance procedures.

[0277] The thermal images captured by the IR camera 615 may enable the Controller and / or AI engine to monitor the efficiency of the internal components continually. For example, if the exterior surface above the Exhaust Fan 609 shows an unusually high temperature, it may suggest that the fan is not expelling air efficiently, possibly due to blockage or mechanical failure. Similarly, thermal anomalies around the Mixing Damper 611 may indicate improper air mixing, affecting the overall efficiency of the HVAC system.

[0278] By integrating the IR camera 615 and leveraging its thermal imaging capabilities, the SRTU 600 may ensure that each component operates within optimal temperature ranges, thereby enhancing energy efficiency, reducing wear and tear, and extending the system's lifespan. This advanced thermal monitoring system may allow for real-time adjustments and predictive maintenance, ensuring the SRTU 600 remains reliable and efficient under varying operational conditions.

[0279] Referring now to FIG. 7, an exemplary view of the SRTU unit 700 in accordance with an embodiment of the invention. The SRTU 700 comprises a Damper 701 which is essential for controlling the flow of air into and out of the SRTU 700. The damper 701 can be adjusted to regulate the volume of air based on the system's needs, thereby enhancing the unit's overall energy efficiency. The damper 701 can be automated, responding to signals from the SRTU's control system (not shown, but housed along with other components with the SRTU 700) that dictate the required airflow based on various factors, such as the internal temperature demand, the quality of the outside air, and the specific operational mode of the HVAC system.

[0280] Additionally, the damper's design may include a series of airtight seals to prevent energy losses and maintain the integrity of the air being processed. This contributes to the sustainable nature of the SRTU 700, as minimal energy is wasted during operation.

[0281] An IR camera 710 may strategically be installed on or around the SRTU 700 to capture thermal images of at least one surface of the SRTU 700. For example, the IR camera 710 can be positioned to capture thermal images of the top surface 702 of the SRTU 700. The thermal images provide a visual representation of the temperature distribution across the surface of the SRTU 700, highlighting areas of varying heat signatures.

[0282] These thermal images are then transmitted to the SRTU control system, where a Controller and / or AI engine processes the images to identify specific heat signatures corresponding to the internal components of the SRTU 700. For example, the heat signatures 710A detected on the top surface 702 may be indicative of the operating condition of the dampers 701 located inside the SRTU 700. By analyzing the heat signatures 710A, the Controller and / or AI engine can determine whether the dampers 701 are functioning optimally or if there are any anomalies that need to be addressed.

[0283] The Controller and / or AI engine may utilize advanced algorithms to compare the detected heat signatures against predefined optimal temperature ranges for each SRTU component. If the heat signature 710A deviates from the expected range, it indicates a potential issue with the dampers 701. The Controller and / or AI engine then takes appropriate actions to control the SRTU 700 and its components to rectify the issue. For example, if the dampers 701 are overheating, the Controller and / or AI engine may adjust the airflow or activate cooling mechanisms to bring the temperature back within the desired range.

[0284] Moreover, the Controller and / or AI engine continuously monitors the thermal images to ensure real-time responsiveness to any changes in the heat signatures. This dynamic monitoring allows the system to maintain optimal performance and efficiency of the SRTU 700. The Controller and / or AI engine can also predict potential maintenance needs by identifying gradual changes in heat signatures over time, enabling proactive maintenance, and reducing the risk of component failure.

[0285] In addition to controlling the SRTU 700, the Controller and / or AI engine can integrate with the building's HVAC system to optimize overall climate control. For example, if the thermal images indicate that the dampers 701 are not operating efficiently, the Controller and / or AI engine can adjust the HVAC settings to compensate, providing consistent and comfortable indoor conditions.

[0286] In some embodiments, the Controller and / or AI engine within the control system of the SRTU 700 may leverage thermal data captured by an IR camera positioned on the roof or nearby to monitor heat signatures on the surface of the SRTU 700. By analyzing these thermal images, the Controller and / or AI engine can infer the operational status of internal components, including the damper 701. For example, if the thermal images indicate an unusual heat buildup on the SRTU's surface above and / or near the location of the damper 701, it may suggest that the damper is not functioning optimally, possibly due to blockage or mechanical failure.

[0287] The Controller and / or AI engine can then take proactive measures to adjust the damper 701 to ensure efficient airflow. For example, if the heat signatures suggest that the airflow through the damper 701 is restricted, the Controller and / or AI engine can signal the damper to open wider to increase air volume and improve cooling efficiency. Conversely, if excessive cooling is detected, the AI can close the damper slightly to reduce airflow and maintain the desired temperature, thereby optimizing energy usage.

[0288] Moreover, the Controller and / or AI engine can use the thermal data to detect patterns over time, learning the typical thermal behavior associated with different damper positions and operational states. This learning may enable the AI to predict the most efficient damper settings for varying conditions, such as changes in external temperature, occupancy levels, and internal heat generation. For example, during peak occupancy, the AI can pre-emptively adjust the damper 701 to maximize airflow and cooling capacity, providing comfort without waiting for temperature sensors alone to trigger adjustments.

[0289] Referring now to FIG. 8, an exemplary view of the SRTU unit 800 in accordance with another embodiment of the invention, showcasing its filtration system. The Filters 801 are constructed to purify the incoming air, removing particulates, allergens, and other airborne contaminants to ensure a high standard of air quality within the building.

[0290] The design of the Filters 801 may include multiple stages with different filtration media to address a variety of contaminants. The first stage may consist of a pre-filter for larger particles, followed by higher-grade filters, such as HEPA filters, for fine particulates. This multi-stage approach enables comprehensive air purification and contributes to the health and comfort of the building's occupants. Given the modular nature of the SRTU 800 as discussed in the invention, the Filters 801 are likely constructed for easy access and maintenance. They may be housed in a removable panel or drawer-like component, allowing for quick replacement or cleaning, which aligns with the need for user-friendly operation and serviceability.

[0291] The positioning of the Filters 801 at the air intake point further suggests that the SRTU 800 is engineered to address environmental sustainability. By ensuring that the exhaust air is also filtered, the SRTU 800 can minimize the impact on the external environment.

[0292] An IR camera 810 may strategically be installed on or around the SRTU 800 to capture thermal images of at least one surface of the SRTU 800. For example, the IR camera 810 can be positioned to capture thermal images of the top surface 802 of the SRTU 800. These thermal images provide a detailed visual representation of the temperature distribution across the top surface 802, highlighting areas of varying heat signatures.

[0293] The thermal images are then transmitted to the SRTU control system, where a Controller and / or AI engine may process the thermal images to identify specific heat signatures corresponding to the internal components of the SRTU 800. For example, the heat signature 810A detected on the surface 802 may be indicative of the operating condition of the filters 801 located inside the SRTU 800. By analyzing the heat signatures, the Controller and / or AI engine can determine whether the filters 801 are functioning optimally or if there are any anomalies that need to be addressed.

[0294] The Controller and / or AI engine may utilize advanced algorithms to compare the detected heat signatures against predefined optimal temperature ranges for each SRTU component. If the heat signature 810A deviates from the expected range, it indicates a potential issue with the filters 801. The Controller and / or AI engine then takes appropriate actions to control the SRTU 800 and its components to rectify the issue. For example, if the filters 801 are clogged or not functioning efficiently, the Controller and / or AI engine may adjust the airflow or initiate a maintenance alert to replace or clean the filters 801.

[0295] In some embodiments, the Controller and / or AI engine within the control system of the SRTU 800 can utilize thermal data captured by an IR camera to monitor the condition of the Filters 801. By analyzing heat signatures on the surface of the SRTU 800, the Controller and / or AI engine can detect changes in airflow and potential blockages within the filters. For example, if the thermal images reveal a consistent increase in temperature around the filters, it may indicate reduced airflow due to clogged or dirty filters.

[0296] Based on this analysis, the Controller and / or AI engine can optimize the filtration system's operation. It can also send alerts for maintenance when it detects that the filters need cleaning or replacement, ensuring that the air purification process remains efficient. Additionally, the AI can adjust the speed of the fans to compensate for any detected airflow reduction, maintaining the desired indoor air quality without compromising energy efficiency.

[0297] The Controller and / or AI engine can also learn from historical thermal data to predict when the filters will likely require maintenance. By identifying patterns in how quickly the filters become dirty under different conditions, the AI can create a maintenance schedule that minimizes downtime and maximizes the SRTU's operational efficiency.

[0298] Furthermore, the Controller and / or AI engine can integrate data from the BMS to enhance its analysis. For example, it can correlate occupancy data with filter usage, understanding that higher occupancy levels may lead to faster accumulation of contaminants. This may allow for more precise and responsive adjustments to the filtration system, providing optimal air quality at all times.

[0299] Referring now to FIG. 9, an exemplary view of the SRTU unit 900 in accordance with an embodiment of the invention, focusing on the temperature modulation components within the system. A Cooling Coil 901 is constructed to reduce the temperature of the air as it flows through the unit 900. The Cooling Coil 901 may utilize an eco-friendly refrigerant and advanced materials for enhanced heat exchange efficiency, contributing to the SRTU's energy-saving features. The coil's design may also allow for variable cooling rates, adapting to the current thermal load and external temperatures to optimize energy consumption.

[0300] Adjacent to the cooling component is a Heating Coil 902, which raises the temperature of the air during colder conditions. The Heating Coil 902 may incorporate technology such as low-emission burners or energy-efficient heat pumps, aligning with the environmentally conscious approach. The modularity of the design means that both the Cooling Coil 901 and Heating Coil 902 can be easily accessed for maintenance or replaced as part of the SRTU's serviceable design. Both the Cooling Coil 901 and the Heating Coil 902 are important for maintaining the desired indoor environment, responding to the demands set by the SRTU's integrated control system. The system can manage the operation of the coils based on inputs from various sensors, ensuring that indoor temperature and humidity levels remain comfortable for occupants.

[0301] An IR camera 910 may strategically be installed on or around the SRTU 900 to capture thermal images of the top surface of the SRTU 900. The IR camera 910 can be positioned to capture detailed thermal images, highlighting areas with different heat signatures across the top surface. These thermal images are then transmitted to the SRTU control system for analysis by a Controller and / or AI engine.

[0302] The Controller and / or AI engine processes the thermal images to identify specific heat signatures corresponding to the internal components of the SRTU 900. For example, heat signature 910A detected on the surface of the SRTU 900 corresponds to the Cooling Coil 901, while heat signature 910B corresponds to the Heating Coil 902. These heat signatures may provide real-time data on the operational temperatures of these coils, allowing the Controller and / or AI engine to monitor their performance continuously.

[0303] The Controller and / or AI engine may utilize advanced algorithms to analyze the temperature distributions represented by the heat signatures. By comparing these heat signatures to predefined optimal temperature ranges, the Controller and / or AI engine can identify any deviations or anomalies. For example, if heat signature 910A indicates that the cooling coil 901 is operating at a higher temperature than expected, the Controller and / or AI engine may determine that the coil 901 is not functioning efficiently or that there is an issue with the refrigerant flow.

[0304] Based on the analysis of the heat signatures, the Controller and / or AI engine can take several actions to control the SRTU 900 and its components. If the cooling coil 901 is not performing optimally, the Controller and / or AI engine can adjust the airflow, increase the refrigerant flow, or initiate a maintenance alert to inspect the coil 901. Similarly, if the heating coil 902 shows an unusual heat signature 910B, the Controller and / or AI engine can modify the heating parameters to ensure efficient operation or schedule a maintenance check.

[0305] Furthermore, the Controller and / or AI engine can predict potential maintenance needs by tracking gradual changes in the heat signatures over time. The Controller and / or AI engine may also provide recommendations for design modifications based on the analysis of the thermal images. For example, it may suggest changes to the placement or design of the cooling coil 901 and heating coil 902 to improve heat dissipation and enhance overall efficiency.

[0306] In some embodiments, the Controller and / or AI engine integrated within the SRTU's control system may leverage data from an IR camera to monitor the thermal performance of both the Cooling Coil 901 and the Heating Coil 902. By capturing thermal images of the SRTU's exterior, the Controller and / or AI engine can identify specific heat signatures that correlate with the operation of these coils. For example, if the IR camera detects an unusually high temperature on the surface area above the Heating Coil 902, it may indicate that the coil is overworking or experiencing a malfunction.

[0307] The Controller and / or AI engine can then use this thermal data to make real-time adjustments to the operation of the coils. For example, if the Cooling Coil 901 shows signs of inefficiency through elevated surface temperatures, the AI can increase the flow rate of the refrigerant to enhance cooling performance. Similarly, if the Heating Coil 902 is not generating sufficient heat, the AI can activate supplementary heating elements or adjust the airflow to improve heating efficiency.

[0308] The Controller and / or AI engine may also analyze historical thermal data to predict maintenance needs for the coils. By identifying patterns such as gradual increases or decreases in surface temperature over time, the AI can forecast when the coils are likely to require cleaning or other maintenance. This predictive maintenance capability helps prevent unexpected failures and enables the SRTU 900 to operate reliably.

[0309] In some embodiments, an indirect burner 903 may be incorporated into the SRTU 900 to provide an efficient means of heating. The indirect burner 903 may operate by transferring heat through a heat exchanger rather than directly exposing the air to combustion gases. This method may ensure that the air circulated within the building remains free of combustion by-products, enhancing indoor air quality and safety. The indirect burner 903 can utilize various fuels, such as natural gas, propane, or biofuels, aligning with the environmentally conscious design principles of the SRTU 900.

[0310] The incorporation of the indirect burner 903 within the SRTU 900 may offer several advantages. Firstly, it may allow for precise control over the heating process. The Controller and / or AI engine within the control system can regulate the burner's output based on real-time data from temperature sensors and thermal images captured by the IR camera. This may ensure that the heating coil 902 maintains the desired temperature efficiently, even under varying load conditions. The AI can adjust the burner's fuel flow rate and ignition cycles to optimize performance and energy consumption, minimizing operational costs while maintaining comfort levels.

[0311] Moreover, the indirect burner 903 may enhance the system's flexibility and reliability. In colder climates, the burner 903 provides a robust and responsive heating solution that can quickly adapt to changing weather conditions. The Controller and / or AI engine can predict heating demands based on historical data and external weather forecasts, ensuring that the SRTU 900 pre-heats the indoor space before occupancy periods, thus enhancing occupant comfort.

[0312] The indirect burner's design may also include safety features such as flame detection sensors, pressure monitors, and automatic shutoff valves. These safety mechanisms may be integrated with the Controller and / or AI engine, which continuously monitors the burner's operation and can take immediate action in case of any abnormalities, such as extinguishing the flame if an unsafe condition is detected.

[0313] Additionally, the use of the indirect burner 903 aligns with the SRTU 900's modular design, allowing for easy maintenance and replacement. The burner and its associated components can be accessed and serviced without disrupting the rest of the unit, providing minimal downtime. Advanced materials used in the construction of the burner 903 and heat exchanger may improve durability and thermal efficiency, contributing to the long-term sustainability of the SRTU 900.

[0314] In some embodiments of the invention, the placement of the indirect burner 903 can be either inside or outside the SRTU 900, each configuration offering distinct advantages based on specific operational requirements and design considerations.

[0315] When placed inside the SRTU 900, the indirect burner 903 may typically be located near the heating coil 902 to facilitate efficient heat transfer. The burner 903 heats the air indirectly through a heat exchanger, which then warms the air as it passes over the heating coil 902. Such a configuration may ensure that the heat generated by the burner 903 is effectively utilized within the SRTU 900, minimizing heat losses and maximizing energy efficiency. The placement inside the unit may also allow for compact and integrated design, reducing the overall footprint of the HVAC system.

[0316] The internal placement of the indirect burner 903 requires careful design to ensure proper ventilation and safe operation. The burner compartment must be isolated from the air handling areas to prevent any combustion by-products from entering the airstream. Additionally, the compartment may be equipped with safety features such as flame detection sensors, pressure monitors, and automatic shutoff valves to ensure safe operation. The Controller and / or AI engine can monitor these safety features and adjust the burner's operation based on real-time data to maintain optimal performance and safety.

[0317] AI ternatively, when the indirect burner 903 is placed outside the SRTU 900, it can be located in a separate mechanical room or adjacent to the unit 900. In such a configuration, the burner 903 heats a fluid (such as water or a glycol mixture) that is circulated through a heat exchanger inside the SRTU 900. This setup may allow for flexibility in system design, as the burner can be placed in a location that is more convenient for maintenance and fuel supply. It also reduces the risk of combustion-related issues within the SRTU 900, as the burner 903 is physically separated from the air handling components of the SRTU 900.

[0318] The external placement of the indirect burner 903 may require a robust piping system to transport the heated fluid to and from the SRTU 900. The heat exchanger inside the SRTU 900 transfers the heat from the fluid to the air, providing efficient heating. The Controller and / or AI engine can control the flow rate of the heated fluid and the burner's operation to match the heating demand, providing precise temperature control.

[0319] Referring now to FIG. 10, an exemplary view of the SRTU 1000 in accordance with an embodiment of the invention, showcasing a Centrifugal EC (Electronically Commutated) Fan 1001. This fan is integral to the HVAC system, as it is responsible for moving air through the unit 1000 for both heating and cooling processes.

[0320] The Centrifugal EC Fan 1001 is chosen for its energy-efficient operation and its ability to provide variable airflow. Electronically commutated motors are known for their high efficiency, especially when compared to traditional motors, as they can adapt their speed to the system's demand, significantly reducing power consumption. The fan's design can be optimized for quiet operation, which maintains a comfortable environment both inside and outside the building. Additionally, the fan's centrifugal design allows it to work effectively against the resistance caused by ductwork and filters within the SRTU 1000, providing consistent airflow and pressure throughout the system.

[0321] A plurality of infrared (IR) cameras may be strategically installed within the SRTU 1000 to capture thermal images of the internal components of the SRTU 1000. For example, an IR camera 1010 may be positioned within the SRTU 1000 to monitor the heating coil 1002. The IR camera 1010 captures detailed thermal images 1010A of the heating coil 1002, providing real-time data on its temperature distribution and operational state.

[0322] The captured thermal images 1010A are then transmitted to the SRTU control system, where a Controller and / or AI engine may process these images 1010A to generate thermal profiles of the heating coil 1002. The thermal profiles reveal temperature variations across the heating coil 1002, identifying hotspots, cold spots, and areas of potential concern. By analyzing these thermal profiles, the Controller and / or AI engine can assess the heating coil's performance, detect anomalies, and predict maintenance needs.

[0323] The Controller and / or AI engine may use advanced image processing algorithms to convert the thermal images into digital value patterns representing the temperature distribution across the heating coil 1002. These digital value patterns are then mapped against predefined optimal temperature ranges for the heating coil 1002. If the Controller and / or AI engine detects temperature deviations outside the acceptable range, it can trigger alerts or initiate corrective actions to address the issue.

[0324] For example, if the thermal images 1010A indicate that a section of the heating coil 1002 is significantly hotter than the rest, this may suggest a blockage or inefficiency in that part of the coil 1002. The Controller and / or AI engine can respond by adjusting the airflow, modulating the heating power, or scheduling a maintenance check to inspect and clean the coil 1002. With this proactive approach, the heating coil 1002 operates efficiently and prevents potential failures.

[0325] Furthermore, the Controller and / or AI engine can use historical data and real-time thermal images to track the heating coil's performance over time. By identifying gradual changes in the temperature distribution, the Controller and / or AI engine can predict when the coil 1002 may require maintenance or replacement, allowing for timely intervention and reducing the risk of unexpected breakdowns. The integration of IR cameras within the SRTU 1000 may enhance the unit's ability to monitor and optimize its internal components continuously. With the AI-driven analysis of thermal images, the heating coil 1002, along with other important components, operates at peak efficiency.

[0326] In addition to monitoring the heating coil, the plurality of IR cameras can be positioned to capture thermal images of other internal components such as the cooling coil, evaporator coil, filters, dampers, and fans. Each component's thermal profile is analyzed by the Controller and / or AI engine to ensure optimal performance and detect any anomalies that may impact the SRTU's efficiency. In some embodiments, a plurality of IR cameras may be placed on, around or inside the SRTU 1000.

[0327] The Controller and / or AI engine can also provide recommendations for design modifications (for the SRTU components, ductwork, duct-pipes, and / or the SRTU itself) based on the analysis of thermal images. For example, it may suggest changes to the placement of the heating coil or adjustments to the airflow pathways to enhance heat dissipation and improve overall efficiency. These automated design suggestions may help in optimizing the SRTU's configuration for better performance and energy efficiency.

[0328] In some embodiments, the Controller and / or AI engine integrated within the SRTU 1000's control system can leverage data from an IR camera and various sensors to monitor the performance of the Centrifugal EC Fan 1001. The IR camera can capture thermal images of the SRTU's exterior surface, focusing on the areas corresponding to the fan and its motor. By analyzing these thermal images, the Controller and / or AI engine can predict or detect abnormal heat patterns that may indicate issues such as overheating or mechanical stress.

[0329] For example, if the IR camera detects an elevated temperature around the fan motor, the Controller and / or AI engine can interpret this as a sign of potential overloading or bearing failure. The AI can then adjust the fan's speed or operational parameters to alleviate the stress, providing continued efficient performance while preventing damage. Additionally, the Controller and / or AI engine can trigger maintenance alerts, prompting technicians to inspect the fan before a minor issue escalates into a significant problem.

[0330] The Controller and / or AI engine can also optimize the operation of the Centrifugal EC Fan 1001 based on real-time airflow and pressure data from sensors within the SRTU 1000. By continuously adjusting the fan speed to match the current demand, the AI enables the system to maintain optimal airflow and pressure, contributing to the overall energy efficiency of the HVAC system. For example, during periods of low cooling or heating demand, the AI can reduce the fan speed to conserve energy, whereas, during peak demand, it can increase the speed to ensure adequate air circulation.

[0331] The Controller and / or AI engine can also utilize historical data and predictive analytics to anticipate future airflow needs based on patterns such as occupancy levels, time of day, and external weather conditions. This allows the SRTU 1000 to pre-emptively adjust the fan's operation, ensuring that the indoor environment remains comfortable and energy efficient.

[0332] Referring now to FIG. 11, an exemplary view of the SRTU 1100 in accordance with an embodiment of the invention, highlighting a Damper 1101 with an innovative design and a placement feature “Damper Open”. This feature is indicative of the SRTU's energy-efficient design, which allows for the modulation of air circulation to minimize heating requirements when conditions permit.

[0333] The Damper 1101 can adjust to allow for the recirculation of air within the system. By recirculating warmer indoor air, instead of solely relying on outside air that may be cooler, the SRTU 1100 can reduce the demand on its heating components. This is especially beneficial during periods of mild outdoor temperatures, where the need for additional heating is lessened, thereby conserving energy and reducing operational costs. In “Damper Open” mode, the system can accept fresh air intake based on specific requirements and considering the differential between indoor-outdoor temperatures. During this mode, the system can also recirculate the air as needed to minimize heating or cooling requirements.

[0334] The Damper's capacity to recirculate air also demonstrates the SRTU's responsiveness to the internal climate conditions of the building, dynamically adjusting to maintain comfort levels with optimal energy usage. This process can be managed automatically by the SRTU's control system, which may process data from temperature sensors within the building to make real-time adjustments to the damper positions.

[0335] The Damper 1101 demonstrates an innovative design that may contrast with the exhaust damper 605 as shown in FIG. 6. The damper 1101 represents a design where the damper 1101 can be adjusted to an open position, allowing for the recirculation of indoor air. This recirculation is a strategic function that takes advantage of the thermal energy already present within the building's environment, thereby minimizing the need for additional heating and reducing energy consumption.

[0336] In comparison, the exhaust damper 605 in FIG. 6 may be constructed primarily (although not necessarily) to manage the expulsion of air from the building's interior. Its operation may typically involve releasing stale air and maintaining air quality, but it may not contribute directly to the heating efficiency of the system.

[0337] The damper 1101's design and placement may allow for a more dynamic and responsive air handling strategy within the SRTU 1100. When the indoor temperature is higher than the outside air temperature, the damper opens to recirculate the warmer indoor air, thus conserving heat and reducing the demand on the heating coil. The control systems for both dampers (1101&605), although not detailed in the figures, may likely be different. The control system for the recirculating damper 1101 may be responsive to temperature variations and capable of precise modulation to balance indoor air temperature efficiently. The control system for the exhaust damper 605 may be simpler, focusing on air quality parameters and possibly building pressurization.

[0338] In some embodiments, the Controller and / or AI engine within the SRTU 1100 leverages thermal data captured by an IR camera to optimize the operation of Damper 1101. By monitoring the heat signatures on the exterior surface of the SRTU 1100, the Controller and / or AI engine can infer the efficiency of air recirculation and heating processes. For example, if the thermal images show a consistent temperature increase near the damper, it may indicate that the damper 1101 is effectively recirculating warm indoor air, reducing the need for additional heating.

[0339] The Controller and / or AI engine can make real-time adjustments to the damper position based on the analyzed thermal data and / or inputs from temperature sensors installed within the SRTU 1100 as well as within the building. If the AI detects that the indoor air temperature is higher than the outdoor temperature, it can open the damper to maximize air recirculation, conserving energy. Conversely, if the indoor temperature drops, the AI can close the damper 1101 to limit recirculation and initiate additional heating.

[0340] Additionally, the Controller and / or AI engine can predict the optimal times for damper operation by analyzing historical temperature data and occupancy patterns. By understanding when the building is typically occupied or unoccupied, the AI can pre-emptively adjust the damper 1101 to maintain a comfortable indoor climate with minimal energy use.

[0341] Referring now to FIG. 12, an exemplary view of the SRTU 1200 in accordance with an embodiment of the invention. It specifically details the air management pathways within the HVAC system. The Fresh Air Intake 1201 through an Air Hood (e.g., 504) is an important component that indicates where outside air enters the SRTU 1200. This air intake may include filtration and possibly pre-heating or pre-cooling functions as part of the unit's energy-efficient design.

[0342] The Return Air Exhaust 1202 is where the indoor air, which has been circulated through the building and is now being exhausted, exits the SRTU 1200. This design may also incorporate energy recovery systems to retain some of the thermal energy from the exhaust air, which may then be transferred to the incoming fresh air to improve overall efficiency.

[0343] The Damper 1203 having a specific placement feature “Damper Closed” (when compared to the Damper Open feature of the damper 1101 as discussed in FIG. 11), illustrates a mode where the unit 1200 is not taking in outside air and is recirculating the indoor air. This may be used during peak heating or cooling periods when the outside air temperature is far from the desired indoor conditions, or when the air quality outside is poor. In this mode, the SRTU 1200 may rely solely on its internal heating and cooling mechanisms to maintain the indoor climate.

[0344] The integration of dampers (1101 or 1203) in the SRTUs (1100 or 1200) suggests a level of control and adaptability in the operation of the SRTUs. The system can modify the balance of fresh air to return air to optimize air quality and energy usage. These dampers may be part of the modular design of the SRTUs, allowing for easy access and maintenance, consistent with the emphasis on serviceability described throughout the invention.

[0345] In some embodiments, the Controller and / or AI engine integrated within the SRTU 1200 can leverage thermal data captured by an IR camera to optimize the operation of Damper 1203. By analyzing the heat signatures on the SRTU's exterior surface, the Controller and / or AI engine can infer the effectiveness of air recirculation and identify any potential inefficiencies. For example, if the thermal images indicate an unusual temperature gradient near the damper, it may suggest that the damper is not sealing properly when closed, leading to unwanted air exchange and energy loss.

[0346] The Controller and / or AI engine can make real-time adjustments to the damper positions based on this thermal data and inputs from indoor temperature and air quality sensors. If the AI detects that the indoor air quality is degrading due to high levels of CO2 or other pollutants, it can open the damper 1203 to allow fresh air intake, even if the outside temperature is not ideal. Conversely, if maintaining indoor temperature is the priority, the AI can ensure the damper 1203 remains closed to maximize recirculation and minimize energy consumption.

[0347] Moreover, the Controller and / or AI engine can also predict optimal damper operation times by analyzing historical data and forecasting environmental conditions. For example, it can anticipate periods of high occupancy or external weather changes, adjusting the damper positions in advance to maintain optimal indoor conditions with minimal energy use.

[0348] In an embodiment of the invention, an SRTU may incorporate an advanced damper mechanism capable of automatic or manual modulation to optimize environmental conditions within a building. The SRTU features a sophisticated control system integrated with sensors that continuously monitor various parameters such as indoor air quality, temperature, humidity, and outdoor air conditions.

[0349] In some embodiments of the invention, the dampers may play a pivotal role in regulating the airflow within the SRTU. Dampers can be automatically adjusted to either an open or closed position, dictating the flow of air based on real-time data collected by the sensors. For example, when the indoor air temperature is lower than desired, the dampers may automatically close, reducing the intake of cooler outside air and enabling the system to efficiently recirculate and warm the indoor air. Conversely, if the sensors detect that the indoor air quality is compromised or the indoor air temperature exceeds the desired threshold, the dampers can open to allow fresh outside air to enter, facilitating the dilution of indoor pollutants and assisting in temperature control.

[0350] The damper operation may not solely be reliant on automation. Users have the capability to manually override the automatic settings, providing flexibility in operation. This can be particularly useful in scenarios where specific ventilation requirements are needed, such as in response to occupancy changes or particular indoor activities that may affect air quality or temperature.

[0351] Moreover, the SRTU can operate in various modes, depending on the damper positions. In the ‘Damper Open’ mode, the system prioritizes fresh air intake, which is essential for maintaining air quality and managing internal CO2 levels. In the ‘Damper Closed’ mode, the emphasis is on air recirculation, which is energy efficient and can be beneficial for maintaining consistent thermal conditions within the building.

[0352] The SRTU can dynamically adjust to the least energy-intensive operation required to maintain comfort. Additionally, it contributes to the building's environmental sustainability by reducing the need for mechanical heating or cooling when the external conditions are favorable for natural ventilation or air recirculation. With the inclusion of user control, the SRTU can adapt to the diverse and changing needs of the building's occupants, providing a responsive and user-friendly climate control solution.

[0353] In some embodiments of the invention, a Smart Roof Top Unit (SRTU) suitable for roof-mounted applications on commercial buildings or positioned proximally may provide fluid communication with an internal HVAC system. The SRTU and its associated components are constructed to deliver heating, cooling, and ventilation to spaces within the associated building.

[0354] The cooling process within the SRTU involves drawing air from the building's interior into the unit. This air passes through filters, removing particulates, and then flows over cooling coils. Inside these coils, a refrigerant absorbs heat from the air, thereby cooling it. The refrigerant circulates to an external cooling unit, and the cooled air is then distributed back into the building through ductwork.

[0355] Referring now to FIG. 13, an exemplary block diagram of an SRTU system 1300, constructed in accordance with the innovative features discussed throughout the invention. The diagram encapsulates only a few of the primary components and systems that the SRTU system 1300 may include, showcasing its sophisticated structure and functionality. In some embodiments, a number of other components may also be integrated within the SRTU system 1300.

[0356] The Outer Shell 1302 represents a durable exterior of the SRTU 1300, meticulously constructed from a PPR core layer intricately bonded with various protective layers. These layers have been elaborated upon across various embodiments of the invention. With this advanced, composite construction of the Outer Shell 1302, the SRTU 1300 is well-defended against a multitude of environmental challenges, including extreme weather conditions, UV exposure, and physical impacts, thereby providing the longevity and reliability of the unit.

[0357] HVAC Components 1304 constitute the core operational elements of the HVAC system housed within the SRTU 1300, encompassing a broad array of parts facilitating its multi-faceted climate control capabilities. This may include, but is not limited to, precision dampers that meticulously regulate airflow, advanced heating and cooling coils that ensure effective temperature modulation, and strategically placed fans that facilitate optimal air circulation throughout the system. Additionally, the component suite features high-efficiency air filtration units, such as HEPA filters, which are instrumental in purifying the air by trapping fine particulates and maintaining superior air quality. The HVAC components may also integrate an economizer for harnessing external air for cooling under suitable conditions, variable frequency drives for energy-efficient operation of motors, and a refrigeration circuit complete with compressors and expansion valves that play a pivotal role in the thermodynamic processes of the SRTU 1300.

[0358] The Control System 1306 serves as the sophisticated brain of the SRTU 1300, adeptly managing and synthesizing data from an array of sensors to orchestrate the unit's operations. The Control System 1306 enables the maintenance of optimal indoor environmental conditions by dynamically adjusting HVAC components in response to real-time feedback from various sensors. The Control System 1306 may optimize energy use while maintaining comfort, integrating advanced algorithms for predictive maintenance and adaptive response to changing conditions. The Control System 1306 may also be constructed for seamless integration with building management systems (BMS), facilitating remote monitoring, diagnostics, and control, which allows for pre-emptive adjustments and swift resolution of potential issues. Furthermore, it supports user interfaces that enable customized settings and preferences, ensuring that the SRTU 1300 operates not only with precision but also with a high degree of user-friendly interactivity.

[0359] The Controller and / or AI engine 1307 is a component integrated within the Control System 1306. The Controller and / or AI engine 1307 may employ machine learning algorithms to analyze trends and historical data, learning from various operational scenarios to enhance predictive maintenance, optimize energy efficiency, and adapt the SRTU's performance to real-time conditions. For example, the Controller and / or AI engine 1307 can predict periods of high occupancy or temperature fluctuations and adjust the HVAC operations, accordingly, providing optimal comfort and energy usage. Additionally, the Controller and / or AI engine can analyze thermal images captured by IR cameras to detect potential issues such as overheating or component failures, enabling proactive maintenance and reducing downtime.

[0360] Sensors 1308 are the SRTU's sensory organs, encompassing devices such as temperature sensors to monitor heat levels, pressure sensors to maintain optimal airflow, and air quality sensors to detect and respond to the presence of pollutants or particulates. Temperature sensors constantly assess thermal conditions, ensuring the system responds effectively to maintain desired heat levels. Pressure sensors play a vital role in managing airflow dynamics within the HVAC system, maintaining an equilibrium that maximizes efficiency and comfort. Air quality sensors are important in detecting a spectrum of pollutants, from volatile organic compounds to particulate matter, triggering the control system 1306 to initiate appropriate filtration and ventilation responses. Additionally, humidity sensors maintain balanced moisture levels, helpful for both comfort and the prevention of mold and mildew. Together, these sensors form an integrated network that feeds real-time data to the Control System 1306, enabling the SRTU 1300 to adapt its operations to the ever-changing indoor environment, thus preserving a healthy and comfortable atmosphere. Apart from these sensors, there can also be various other sensors integrated to the SRTU 1300.

[0361] Communication Interface 1310 is the gateway for external communication, facilitating remote control, integration with Building Management Systems (BMS), integration with a cloud server, and transmitting alerts for maintenance or repair needs, thus allowing for smart, responsive management of the HVAC system. The seamless remote control allows facility managers or occupants to adjust settings and respond to HVAC needs from afar. Integral to smart building operations, it provides robust integration with Building Management Systems (BMS), providing synchronized and harmonized control across various building systems for enhanced efficiency and comfort. The interface 1310 is also responsible for broadcasting timely maintenance and repair alerts, which are essential for proactive system management and minimizing downtime. Moreover, it supports the transmission of performance data to cloud-based analytics platforms, allowing for the utilization of big data and AI-driven insights for predictive maintenance and energy optimization strategies. In essence, the Communication Interface 1310 is pivotal in transforming the SRTU 1300 into an intelligent, interactive component of the modern, smart building ecosystem.

[0362] Further enhancing its sophisticated design, the SRTU 1300 may also integrate a suite of additional components (not shown) to elevate its operational efficiency and sustainability. An Economizer may ingeniously be incorporated to exploit cooler external air for natural ventilation, substantially curtailing energy expenditure during suitable weather conditions. Photovoltaic Solar Cells may strategically be embedded to capture solar energy, thus supplementing the SRTU's power supply and underscoring its commitment to renewable energy utilization. A Rainwater Harvesting System may be included to collect and repurpose rainwater, aligning with sustainable water resource practices and contributing to the building's eco-friendly initiatives. The system may also include a meticulously constructed Condensate Drainage system that enables effective management and disposal of moisture accumulation, a byproduct of the cooling process, thereby preventing potential water damage and maintaining system integrity. To ensure reliable operation, the SRTU 1300 may be outfitted with versatile Power Supplies that can seamlessly switch between conventional grid electricity and alternative energy sources, providing uninterrupted service and energy resilience. User Interfaces may thoughtfully be developed, featuring intuitive touchscreens or tactile buttons, allowing end-users to effortlessly interact with the system for manual adjustments, personalized settings, and system diagnostics, thereby offering a user-centric approach to HVAC system management.

[0363] In some embodiments of the invention, cooling components that may be housed in the SRTU may include one or more: Compressors that drive the refrigeration cycle. The compressors are operative to compress low-pressure, low-temperature refrigerant gas, turning it into high-pressure, high-temperature gas; Condenser Coils where high-temperature refrigerant gas releases its heat to the outside atmosphere, turning it into high-pressure liquid; Expansion Valves that transform high-pressure liquid refrigerant into a low-pressure, low-temperature liquid; Evaporator Coils positioned to have air from the building pass over Evaporator Coils such that refrigerant inside Evaporator Coils absorbs heat from the air, cooling the air. The refrigerant evaporates, turning back into a low-pressure gas; Blower Fans circulate air from the building over the evaporator coil to form conditioned air and then push the conditioned air back into the building; and Filters that capture dust, pollen, and other particulate matter from the air before the air is cooled or heated. Other components associated with a cooling process may also be present in the SRTU, such as, by way of example, an Economizer which is an optional component that may be included in an SRTU. The Economizer allows for reduced carbon footprint cooling when outside atmospheric temperatures are appropriate for cooling a building interior by drawing in cool outside air to reduce indoor temperatures.

[0364] Heating is accomplished by drawing air from an interior of the building and into the SRTU and passing the air through filters over heating apparatus. The heating apparatus may include one or more electric heating units and gas-fired heating units. Electric heating units include electric resistance devices to warm the air. Gas-fired units provide one or more burners to heat a heat exchanger such that air is warmed as the air passes over and / or through the heat exchanger.

[0365] Heating components that may be housed in the SRTU may include one or more: Heat Exchangers (for gas-fired units) with burners to heat air as the air is circulated over the heat exchanger to warm the air; and Burners (for gas-fired units) to produce a flame that heats the heat exchanger.

[0366] The SRTU may also encompass Controls, such as one or more of: thermostats, sensors, and controller units. The Controls may be operative to regulate the operation of components with the SRTU based upon desired conditions which may include, for example, one or more of; temperatures, airborne particulates, and humidity.

[0367] An SRTU provides significant advantages by reducing roof loading which allows for reduced structural support. Structural support is typically accomplished with a considerable carbon footprint impact, increased costs, and increased time to construct the building. In addition, the SRTU according to the present invention provides for optimum space usage since the SRTU is light enough to be located on a roof of a building with relatively low structural support and the SRTU does not require area interior to the building; or occupy ground space.

[0368] While the SRTU does not require an area interior to the building, the SRTUs may be assembled with multiple disparate modular components. SRTU's may be manufactured with diverse manufacturing processes including, but not limited to, one or more of: extrusion of synthetic material and bonding to a weather-resistant surface coating; three-dimensional (“3D”) printing of one or both of synthetic material and a weather resistant surface coating; and injection molding of synthetic material and bonding to a weather resistant surface coating.

[0369] Referring now to FIGS. 14, 14A, and 14B, an exemplary flow chart 1400 of method steps that may be performed in some embodiments of the present invention are illustrated. The flow chart 1400 outlines exemplary process for controlling a Smart Roof Top Unit (SRTU), integrating advanced technologies such as IR temperature monitoring, AI-based analysis, and predictive maintenance strategies to enhance the efficiency and performance of HVAC systems.

[0370] At step 1402, the process begins by providing a Smart Roof Top Unit (SRTU) that comprises various HVAC or SRTU components essential for efficient climate control within a building. The SRTU may be strategically placed on the roof to optimize space usage within the building while providing effective distribution of conditioned air. The SRTU integrates a range of components constructed to work together seamlessly, providing optimal heating, ventilation, and air conditioning (HVAC) performance.

[0371] The HVAC or SRTU components (housed within the SRTU) may include, but not limited to: heating and cooling coils, evaporator coils, fans, filters, dampers, economizers, compressors, expansion valves, heat exchangers, sensors for temperature, humidity, and pressure, air quality monitors, variable frequency drives, energy recovery ventilators, control panels with AI integration, infrared cameras for thermal monitoring, UV germicidal irradiation systems, high-efficiency particulate air (HEPA) filters, sound-dampening insulation, condensate drainage systems, vibration isolation mounts, photovoltaic solar panels, and integrated communication interfaces for remote monitoring and control.

[0372] The modular design of the SRTU may allow for easy installation, maintenance, and scalability. Each component can be accessed and serviced individually, reducing downtime and maintenance costs. This flexibility also facilitates upgrades and expansions, enabling the SRTU to adapt to changing building requirements and advancements in HVAC technology. By integrating these various HVAC components into a single, cohesive unit, the SRTU provides a comprehensive solution for modern building climate control, combining efficiency, reliability, and case of maintenance.

[0373] At step 1404, the process involves providing at least one infrared (IR) camera to capture thermal images of the SRTU. These IR cameras play an important role in monitoring the thermal performance and health of the SRTU by capturing detailed thermal images. These images are used to analyze the temperature distribution and detect any anomalies that may indicate issues with the unit's operation.

[0374] The placement of IR cameras can vary based on the specific monitoring needs and design of the SRTU. IR cameras may be positioned outside the SRTU, either mounted on adjacent structures or on the rooftop itself, to capture thermal images of the SRTU's surface. The external placement allows the IR cameras to monitor the overall thermal profile of the SRTU, identifying hot or cold spots that may correspond to underlying issues with internal components. By mapping zones, points, or areas on the SRTU's surface to specific internal components, the thermal data from these cameras can help predict the condition of those components. For example, a hot spot on the surface above a cooling coil may indicate a malfunction or inefficiency within that coil.

[0375] AI ternatively, IR cameras can be directly attached to the SRTU, providing a closer and more detailed view of specific areas. These cameras can focus on important components such as compressors, heat exchangers, evaporator coils, heating / cooling coils, and fan motors, capturing thermal images that reveal their operating temperatures. By being attached to the SRTU, the cameras can provide continuous, precise monitoring of these components, ensuring that any temperature anomalies are quickly detected and addressed.

[0376] Additionally, IR cameras may also be placed inside the SRTU itself to directly capture thermal images of the internal components. This internal placement may allow for detailed monitoring of the actual operating temperatures of the components, providing real-time data that facilitates optimal performance. By capturing thermal images from within the SRTU, these cameras can provide insights into the health and efficiency of components that are otherwise difficult to monitor, such as internal sections of heat exchangers or the inner workings of compressors.

[0377] The thermal images captured by both external and internal IR cameras may be processed by the SRTU's control system, which uses the data to predict the condition of the internal components. This predictive capability is important for proactive maintenance and operational optimization, allowing the SRTU to maintain high efficiency and reliability by addressing issues before they lead to significant problems. By strategically placing IR cameras both inside and outside the SRTU, a comprehensive thermal profile can be obtained, providing thorough monitoring and precise control of the unit's performance.

[0378] At step 1406, the process involves providing a control system comprising a Controller and / or AI engine for processing the thermal images captured by the IR cameras. The control system is a pivotal component of the SRTU, as it leverages advanced computational capabilities to analyze the thermal data and derive actionable insights that optimize the unit's performance.

[0379] The control system can be integrated directly into the SRTU, allowing for on-site processing of thermal images. Such an integration may ensure that the thermal data is processed in real-time, enabling immediate responses to any detected anomalies or inefficiencies. The Controller and / or AI engine within the control system uses machine learning algorithms to interpret the thermal images, identifying patterns and trends that indicate the operating condition of various components. By continuously analyzing the thermal data, the Controller and / or AI engine can predict potential issues, recommend maintenance actions, and adjust operational parameters to maintain optimal efficiency.

[0380] AI ternatively, the control system may also reside on a cloud server, where the thermal images captured by the IR cameras are transmitted for processing. The cloud-based approach may offer several advantages, including the ability to leverage more powerful computational resources and access to a broader dataset for more accurate analysis. By sending thermal images to the cloud server, the SRTU benefits from advanced AI processing without the need for extensive on-site hardware. The cloud server processes the thermal images, runs predictive analytics, and sends back control commands or maintenance recommendations to the SRTU.

[0381] Whether integrated into the SRTU or hosted on a cloud server, the Controller and / or AI engine processes the thermal images to assess the temperature distribution across the SRTU's components. It maps the thermal patterns against historical data and operational benchmarks to detect deviations that may indicate issues such as overheating, frost buildup, or component failures. By continuously learning from the data, the Controller and / or AI engine improves its predictive capabilities over time, ensuring that the SRTU operates efficiently and reliably.

[0382] At step 1408, the process involves capturing thermal images of the SRTU using the at least one IR camera. The IR camera operates by detecting infrared radiation emitted by the SRTU's surfaces and components. Since different materials and components emit varying levels of infrared radiation based on their temperatures, the camera produces a thermal image where each pixel corresponds to a specific temperature value. These thermal images provide a visual representation of heat patterns, enabling the identification of hotspots, cold spots, and other thermal anomalies.

[0383] The captured thermal images offer several insights into the SRTU's operation. For example, areas with abnormally high temperatures may indicate overheating components, while areas with unexpected cold spots may signify inefficient cooling or frost buildup. By capturing these images continuously, the IR camera allows for constant monitoring of the SRTU's thermal state, ensuring that any deviations from normal operating conditions are quickly detected.

[0384] At step 1410, the process involves converting the captured thermal images into digital value patterns. Each thermal image consists of a multitude of pixels, with each pixel representing a specific temperature value based on the infrared radiation detected from the SRTU's components.

[0385] The conversion process begins with the thermal images captured by the IR cameras. These images are initially in a visual format, where different colors or shades represent varying temperature levels. To transform these images into a format suitable for detailed analysis, the visual data may be converted into numerical data. Each pixel in the thermal image may be assigned a corresponding temperature value, creating a digital matrix of temperature readings.

[0386] This digital matrix, or digital value pattern, may provide a precise representation of the temperature distribution across the SRTU. By converting the thermal images into numerical data, the control system (or the Controller and / or AI engine) can perform more accurate and complex analyses. The digital value patterns enable the system to detect even subtle temperature variations and trends that may not be easily visible in the raw thermal images.

[0387] At step 1412, the process involves analyzing the digital value patterns using a Controller and / or AI engine to assess temperature distribution and identify anomalies. The Controller and / or AI engine receives the thermal images and / or digital value patterns, which represent the precise temperature readings of the SRTU's components. These patterns are essentially a matrix of numerical data that maps the thermal state of the unit in real-time. The Controller and / or AI engine employs sophisticated machine learning algorithms to analyze this data, searching for patterns, trends, and deviations from normal operating conditions.

[0388] The primary goal of the AI analysis is to assess the temperature distribution across the SRTU. The Controller and / or AI engine creates a comprehensive thermal profile of the unit, identifying the typical temperature ranges for different components under various operating conditions. By establishing these baseline profiles, the Controller and / or AI engine can effectively monitor for any deviations that may indicate potential issues.

[0389] One of the key functions of the Controller and / or AI engine is to identify anomalies within the temperature distribution. These anomalies can manifest as hotspots, cold spots, or unexpected temperature fluctuations. For example, a hotspot on the surface of the SRTU may indicate an overheating component, which may lead to a failure if not addressed promptly. Conversely, a cold spot may suggest inefficient cooling or frost buildup on a coil, which can compromise the unit's performance.

[0390] The Controller and / or AI engine uses historical data, real-time monitoring, and predictive analytics to detect these anomalies. It continuously compares the current thermal data against historical trends and predefined thresholds. When an anomaly is detected, the Controller and / or AI engine can trigger alerts and / or recommend corrective actions. For example, if the Controller and / or AI engine identifies a component that is consistently overheating, it may suggest a maintenance check or an adjustment to the operating parameters to prevent failure.

[0391] At step 1414, the process involves mapping the digital value patterns against variable trends, including defrost cycles, power use, equipment status, and operational efficiency. The Controller and / or AI engine begins by correlating the digital value patterns derived from the thermal images with historical and real-time operational data. This mapping process may involve creating a multidimensional dataset where temperature readings are analyzed for variables such as defrost cycles, power consumption, and equipment performance metrics.

[0392] By mapping thermal data against defrost cycle trends, the Controller and / or AI engine can optimize the timing and duration of defrost operations. For example, if the thermal data indicates excessive frost buildup on the evaporator coils, the AI can trigger a defrost cycle. Conversely, by analyzing patterns over time, the AI can adjust defrost schedules to prevent additional cycles, thereby saving energy and reducing wear on the system.

[0393] The Controller and / or AI engine may also analyze how temperature variations correlate with power consumption, identifying opportunities for energy savings. For example, if certain components are consistently operating at higher temperatures, the AI may suggest or perform adjustments to reduce power usage without compromising performance. This analysis helps in fine-tuning the SRTU's operations to achieve optimal energy efficiency.

[0394] The Controller and / or AI engine may also detect early signs of potential failures by identifying anomalies in temperature trends that precede equipment malfunctions. For example, a gradual increase in temperature in a specific component may indicate wear and tear or impending failure. By recognizing these patterns early, the AI can prompt preventive maintenance actions, reducing the likelihood of unexpected breakdowns and costly repairs.

[0395] The Controller and / or AI engine also evaluates how effectively the SRTU maintains desired temperature levels while balancing energy use and system health. This may include optimizing airflow, adjusting fan speeds, and modulating heating and cooling output based on real-time conditions. By mapping thermal data against efficiency metrics, the AI enables the SRTU to operate at peak performance with minimal resource consumption.

[0396] At step 1416, the process involves initiating defrost cycles based on the analysis of thermal images and frost accumulation. The Controller and / or AI engine continuously monitors the thermal images captured by the IR cameras to assess the temperature distribution across the SRTU's components. These thermal images provide detailed visual data that helps identify areas where frost is accumulating on the evaporator coils. Frost buildup can significantly impair the heat exchange efficiency of the coils, leading to reduced cooling performance and increased energy consumption.

[0397] When the Controller and / or AI engine detects frost accumulation through the thermal images or their digital value patterns, it analyzes the extent and distribution of the frost. The Controller and / or AI engine may also use this data to determine the optimal timing and duration for initiating a defrost cycle. The goal is to remove the frost efficiently without unnecessarily disrupting the cooling process or wasting energy.

[0398] The defrost cycle may be initiated by the Controller and / or AI engine when specific thresholds for frost accumulation are met. These thresholds may be set automatically based on historical data and real-time monitoring to ensure that defrosting occurs. The Controller and / or AI engine may also consider factors such as ambient temperature, humidity levels, and the operational load on the SRTU to fine-tune the defrost initiation process.

[0399] Once the defrost cycle is triggered, the SRTU system temporarily switches from cooling mode to defrost mode. The SRTU may employ various defrosting methods, such as reversing the refrigerant flow, using electric heaters, indirect burners, louvers, jets, multiple fans, or circulating warm air over the coils. The choice of method depends on the specific design and requirements of the SRTU.

[0400] Throughout the defrost cycle, the Controller and / or AI engine continues to monitor the thermal images to track the progress of frost removal. It enables the coils to be adequately defrosted and ready to resume efficient cooling operation. By dynamically adjusting the defrost process based on real-time data, the Controller and / or AI engine minimizes the energy consumption and time required for defrosting. In addition to optimizing the defrost cycles, the Controller and / or AI engine can also schedule preventive defrost operations based on historical patterns of frost accumulation.

[0401] At step 1418, the process involves optimizing power use and operational efficiency by adjusting HVAC components based on AI analysis. The Controller and / or AI engine continuously analyzes the thermal images and other operational data collected from the SRTU. By leveraging machine learning algorithms, the AI identifies patterns and trends that indicate how the system is performing under various conditions.

[0402] One of the primary goals of the Controller and / or AI engine is to reduce energy consumption without compromising comfort and efficiency. The AI achieves this by monitoring the power usage of different components, such as compressors, fans, and heating / cooling coils, and identifying opportunities to reduce energy consumption. For example, the AI may detect that certain components are operating at higher power to maintain the desired temperature. In such cases, the AI can adjust the settings to lower the power usage, thus conserving energy.

[0403] Additionally, the Controller and / or AI engine can optimize the operational efficiency of the SRTU by dynamically adjusting the airflow, temperature setpoints, and humidity levels. For example, if the AI detects that certain areas within the building require more cooling while others need less, it can modulate the airflow to direct more conditioned air to the hotter zones and reduce it in the cooler zones.

[0404] At step 1420, the SRTU system receives commands for additional cooling or heating requirements. These commands can originate from various sources, including building management systems (BMS), facility managers, or even occupants through user interfaces or wirelessly. The BMS may issue commands based on pre-set schedules, detected occupancy levels, or real-time environmental conditions. For example, if a conference room is scheduled to be used in an hour, the BMS may request additional cooling to ensure a comfortable environment. Similarly, occupants may manually request changes via a thermostat or a mobile app to suit their immediate comfort needs.

[0405] Upon receiving these commands, the system (or Controller and / or AI engine) may utilize predictive analytics to anticipate the temperature changes required to meet the new demands. This may involve creating detailed temperature maps based on the expected load. The Controller and / or AI engine uses historical data, current conditions, and the specifics of the request to generate these predictions. For example, if the system anticipates a significant increase in occupancy in a particular zone, it will predict a corresponding rise in temperature and humidity, prompting pre-emptive cooling adjustments to maintain comfort.

[0406] Step 1422 involves the continuous monitoring of ambient conditions within the building spaces to be cooled or heated. This monitoring may be conducted using a network of sensors and / or cameras strategically placed throughout the building. The sensors may measure various parameters, including temperature, humidity, occupancy, and airflow.

[0407] This comprehensive monitoring allows the system to maintain an accurate and dynamic understanding of the building's environmental conditions. The data collected by these sensors or cameras is continuously fed into the control system, where the Controller and / or AI engine analyzes it to make informed adjustments to the HVAC operations, providing optimal comfort and efficiency.

[0408] At step 1424, the system assesses the status of HVAC equipment and occupancy trends using infrared imaging, camera feeds and various sensors. Infrared cameras installed in and around the SRTU capture thermal images of the unit's components, providing detailed insights into their operating conditions. These images help identify any anomalies, such as overheating or underperformance, which may indicate potential failures or inefficiencies.

[0409] Additionally, occupancy sensors or cameras throughout the building detect the presence and movement of people in different zones. The sensors may include motion detectors, CO2 sensors, and even thermal cameras that identify human heat signatures. By analyzing this data, the Controller and / or AI engine can determine which areas of the building are currently occupied and may also predict future occupancy patterns.

[0410] Combining data from infrared imaging and occupancy sensors allows the system to adjust HVAC operations proactively. For example, if an infrared camera detects that a compressor is running hotter than usual, the system can pre-emptively schedule maintenance or adjust its operation to prevent failure. Similarly, if occupancy sensors indicate that a particular area will soon be filled with people, the system can adjust cooling or heating to ensure comfort upon their arrival.

[0411] Step 1426 involves adjusting HVAC operations based on predicted demand, taking into account various factors such as the time of day, day of the week, seasonality, geographic location, and historical data. The Controller and / or AI engine uses these variables to create predictive models that anticipate the building's HVAC needs with high accuracy.

[0412] For example, the system may recognize that mornings typically require increased heating during winter due to lower overnight temperatures, while afternoons may need more cooling as the building's occupancy and external temperatures rise. On weekdays, the demand pattern may differ significantly from weekends, influenced by typical office hours and occupancy levels.

[0413] Seasonality may also play a role in determining the HVAC requirements. The system may adjust its operations based on seasonal variations, such as higher cooling demands in summer and increased heating needs in winter. Geographic location may also influence these adjustments, as buildings in different climates experience varying external temperature ranges and humidity levels.

[0414] Historical data may provide a valuable reference for understanding recurring patterns and anomalies. By analyzing past performance and environmental conditions, the Controller and / or AI engine fine-tunes its predictions and adjustments, providing optimal efficiency and comfort. For example, if historical data shows that a particular area of the building tends to overheat in the afternoon during summer months, the system can pre-emptively increase cooling in that zone.

[0415] At step 1428, the thermal images captured by the IR cameras installed on the SRTU unit may be transmitted to a cloud server. This centralized storage facilitates the cumulative analysis of thermal data from multiple SRTU units. By uploading these images to the cloud, the system can leverage advanced computational resources and AI algorithms that are more powerful than those available on individual units. The cloud-based Controller and / or AI engine may aggregate and analyze the thermal images, identifying common patterns, trends, and anomalies across different units. This collective analysis enhances the predictive accuracy and reliability of the system, as it benefits from a larger dataset and more diverse operational scenarios. The insights gained from this cumulative analysis are used to optimize the performance of all connected SRTU units, providing a scalable and highly efficient monitoring solution.

[0416] At step 1430, the Controller and / or AI engine continuously determines the optimum defrost state for the SRTU based on several predefined criteria. These criteria may include cooling and heating power requirements, energy efficiency targets, and system responsiveness. The Controller and / or AI engine analyzes real-time thermal data to assess frost accumulation on components such as evaporator coils. It then calculates the ideal timing and duration for defrost cycles to ensure that the SRTU maintains its efficiency and performance. By optimizing the defrost state, the system minimizes energy consumption, reduces wear and tear on components, and enables the unit to quickly return to its optimal operating condition. The continuous nature of this assessment allows for real-time adjustments and proactive maintenance, preventing frost-related performance degradation.

[0417] At step 1432, the control parameters of the SRTU and / or the control system may be updated based on real-time data and AI analysis. The Controller and / or AI engine continuously monitors the thermal images, ambient conditions, and operational data from the SRTU. Using this information, it dynamically adjusts the control settings to maintain optimal performance. For example, if the AI detects a drop in cooling efficiency, it may increase airflow or adjust the refrigerant flow rate. Similarly, if energy consumption is higher than expected, the AI may fine-tune the system to operate more efficiently.

[0418] At step 1434, the Controller and / or AI engine predicts HVAC equipment failures, power usage, heating and cooling requirements, and maintenance schedules. By analyzing the digital value patterns from thermal images and other operational data (from SRTU sensors or from BMS), the AI can identify early signs of potential failures, such as abnormal temperature rises or inconsistent performance. It may also forecast power usage trends based on historical data and real-time monitoring, allowing for more accurate energy budgeting. Additionally, the AI also predicts future heating and cooling demands by considering factors such as occupancy patterns, weather forecasts, and historical usage. This predictive capability enables the system to schedule maintenance proactively, reducing downtime and preventing unexpected breakdowns. By forecasting these parameters, the AI enables the SRTU to operate smoothly and efficiently.

[0419] At step 1436, the SRTU and its HVAC components may be controlled based on the predictions and analyses performed by the Controller and / or AI engine. The AI-driven control system adjusts the operation of key components such as fans, filters, coils, compressors, and dampers to optimize performance. For example, if the AI predicts a peak cooling demand in the afternoon, it may pre-cool the building in the morning to reduce the load during peak hours. Similarly, if an equipment failure is predicted, the AI can adjust the system to prevent overloading the affected component. These real-time adjustments ensure that the SRTU maintains optimal indoor conditions while operating efficiently and reliably.

[0420] At step 1438, the Controller and / or AI engine may suggest modifications to the SRTU to improve efficiency and performance. Based on its continuous analysis of thermal images, operational data, and performance trends, the AI identifies opportunities for enhancements. These suggestions may include hardware upgrades, such as installing more efficient fans or adding insulation to reduce thermal losses. The AI may also recommend software updates to optimize control algorithms or introduce new features. Additionally, the AI can suggest changes to maintenance routines or operational strategies to prolong the lifespan of components and improve overall system performance.

[0421] In some embodiments of the invention, a method for controlling an HVAC system incorporating a Smart Roof Top Unit (SRTU) is developed, focusing on the utilization of advanced sensor technology and environmental condition monitoring to optimize system performance and efficiency.

[0422] The method comprises integration of a diverse array of sensors within the SRTU. These sensors are strategically placed to continuously monitor various environmental parameters including indoor and outdoor temperatures, humidity levels, air quality, and pressure. The purpose of this extensive sensor network is to gather detailed real-time data about the environmental conditions both inside and outside the building. This data collection is vital for ensuring that the HVAC system operates in a manner that is both responsive and efficient.

[0423] Temperature sensors play a key role in this system, providing accurate readings of the indoor environment as well as external conditions. These readings enable the SRTU to adjust its heating or cooling output to match the desired indoor temperature set by the occupants, thereby maintaining a comfortable indoor climate.

[0424] Humidity sensors add another layer of environmental monitoring, assessing the moisture content in the air. Maintaining optimal humidity levels is essential not only for comfort but also for the health of building occupants and the integrity of the building structure.

[0425] Air quality sensors monitor the presence of pollutants and particulates in the indoor air. These sensors ensure that the air quality remains within safe and comfortable levels, triggering the HVAC system to increase ventilation or filtration.

[0426] Pressure sensors within the SRTU monitor the air pressure in different parts of the HVAC system. Proper air pressure balance is important for efficient air distribution and for preventing undue stress on the system components. The SRTU may further be equipped with CO2 sensors, ultraviolet (UV) light sensors, and wind speed and direction sensors.

[0427] Additionally, this method encompasses remote monitoring capabilities. The sensor data can be transmitted to a centralized control system, which can be accessed by facility managers or maintenance personnel remotely. This feature allows for real-time adjustments to the system settings from off-site locations, enhancing the flexibility and responsiveness of the HVAC management.

[0428] Furthermore, the method may include predictive maintenance algorithms that analyze sensor data over time to identify potential issues before they become significant problems. With this proactive approach to maintenance, the SRTU operates reliably and efficiently, reducing downtime and extending the lifespan of the system.

[0429] Such an SRTU control method represents a sophisticated approach to HVAC system management. By leveraging advanced sensor technology and remote monitoring capabilities, the system not only provides a comfortable and healthy indoor environment but also operates with enhanced efficiency and reliability.

[0430] Referring now to FIG. 15, an exemplary block diagram of an LRTU 1500, with innovative features included in the present invention. FIG. 15 illustrates a few of the primary components and systems that the LRTU 1500 may include, showcasing the LRTUs 1500 sophisticated structure and functionality. In some embodiments, a number of other components may also be integrated within the LRTU system 1500.

[0431] The Outer Shell 1502 represents a durable exterior of the LRTU 1500, including a PPR core layer intricately bonded with various protective layers. These layers have been elaborated upon across various embodiments of the invention. This advanced, composite construction of the Outer Shell 1502 ensures the LRTU 1500 is well-defended against a multitude of environmental challenges, including extreme weather conditions, UV exposure, and physical impacts, thereby providing the longevity and reliability of the unit.

[0432] HVAC Components 1504 constitute the core operational elements of the HVAC system housed within the LRTU 1500, encompassing a broad array of parts useful for its multi-faceted climate control capabilities. This may include, but is not limited to, precision dampers that meticulously regulate airflow, advanced heating and cooling coils that ensure effective temperature modulation, and strategically placed fans that facilitate optimal air circulation throughout the system. Additionally, the component suite features high-efficiency air filtration units, such as HEPA filters, which are instrumental in purifying the air by trapping fine particulates and maintaining superior air quality. The HVAC components may also integrate an economizer for harnessing external air for cooling under suitable conditions, variable frequency drives for energy-efficient operation of motors, and a refrigeration circuit complete with compressors and expansion valves that play a pivotal role in the thermodynamic processes of the LRTU 1500.

[0433] The Control System 1506 serves as the sophisticated brain of the LRTU 1500, adeptly managing and synthesizing data from an array of sensors to orchestrate the unit's operations. The Control System 1506 ensures the maintenance of optimal indoor environmental conditions by dynamically adjusting HVAC components in response to real-time feedback from various sensors. The Control System 1506 may optimize energy use while maintaining comfort, integrating advanced algorithms for predictive maintenance and adaptive response to changing conditions. The Control System 1506 may also be seamless integrated with building management systems (BMS), facilitating remote monitoring, diagnostics, and control, which allows for pre-emptive adjustments and swift resolution of potential issues. Furthermore, it supports user interfaces that enable customized settings and preferences, ensuring that the LRTU 1500 operates not only with precision but also with a high degree of user-friendly interactivity.

[0434] In some embodiments, the Control System 1506 of the LRTU may comprise an Artificial Intelligence (AI) engine 1506A operative to control performance of the HVAC system by intelligently controlling heating, cooling, and ventilation based on real-time and predicted environmental and operational requirements.

[0435] The AI engine 1506A within the Control System 1506 may be equipped with advanced machine learning algorithms capable of processing vast amounts of data from various sensors 1508 embedded throughout the HVAC system. These sensors 1508 may collect data on temperature, humidity, air quality, occupancy levels, and external weather conditions. By analyzing this data, the AI engine 1506A is operative to generate logical commands comprising one or both of electrical and digital transmissions to adjust the heating, cooling, and airflow settings in real-time, controlling indoor climate conditions and increasing energy efficiency.

[0436] In some embodiments, the AI engine may learn from historical data and identify trends in system performance and environmental conditions. For instance, the AI can learn typical occupancy patterns within a building and adjust the HVAC operations to ramp up heating or cooling shortly before occupants arrive, or scale back during off-hours or when the building is unoccupied. This predictive capability may allow for more proactive management of the HVAC system, reducing energy waste and improving the overall comfort levels for building occupants.

[0437] Furthermore, the AI engine may be programmed to continuously monitor the performance of the HVAC components, such as the efficiency of the heating coils, the operational health of the cooling system, and the integrity of the ventilation pathways. By detecting anomalies or deviations from expected performance benchmarks, the AI engine can trigger maintenance alerts, recommending preventive maintenance or urgent repairs, thereby avoiding costly downtimes and extending the lifespan of the equipment.

[0438] The Control System 1506, through its AI engine, may also interface with other building management systems (BMS) to ensure holistic management of the building's utilities and services. This integration may allow the AI engine to consider additional factors such as energy consumption patterns, security systems, and even external data feeds like weather forecasting services, to dynamically adjust the HVAC operations, further enhancing the building's efficiency and the comfort of its occupants.

[0439] In addition to operational control, the AI engine may incorporate user-friendly interfaces that allow building managers and maintenance personnel to interact with the system. Through an interactive user interface, a user may view detailed reports, including, for example, one or more of: system performance, energy usage, and receive real-time notifications on any issues or adjustments made by the AI. In some embodiments, a user may interact with the interactive user interface to manually override AI decisions, providing flexibility and human oversight to the automated system.

[0440] Imaging devices and / or Sensors 1508 encompassing devices such as infrared imaging capture devices, or other devices capable of generating a quantification of various temperatures of one or more items within a designated area, such as a field of view of an image capture device, and / or temperature sensors to monitor heat levels, pressure sensors to maintain optimal airflow, and air quality sensors to detect and respond to the presence of pollutants or particulates. Temperature sensors constantly assess thermal conditions, ensuring the system responds effectively to maintain desired heat levels. Pressure sensors play a vital role in managing airflow dynamics within the HVAC system, maintaining an equilibrium that maximizes efficiency and comfort. Air quality sensors are crucial in detecting a spectrum of pollutants, from volatile organic compounds to particulate matter, triggering the Control System 1506 to initiate appropriate filtration and ventilation responses.

[0441] Additionally, humidity sensors maintain balanced moisture levels, facilitating both comfort and the prevention of mold and mildew. Together, these sensors form an integrated network that feeds real-time data to the Control System 1506, enabling the LRTU 1500 to adapt its operations to the ever-changing indoor environment, thus preserving a healthy and comfortable atmosphere. Apart from these sensors, there can also be various other sensors integrated to the LRTU 1500.

[0442] Communication Interface 1510 is the gateway for external communication, facilitating remote control, integration with Building Management Systems (BMS), integration with a cloud server, and transmitting alerts for maintenance or repair needs, thus allowing for smart, responsive management of the HVAC system. The seamless remote control allows facility managers or occupants to adjust settings and respond to HVAC needs from afar. Integral to smart building operations, it provides robust integration with Building Management Systems (BMS), providing synchronized and harmonized control across various building systems for enhanced efficiency and comfort.

[0443] The Interface 1510 may also be responsible for broadcasting timely maintenance and repair alerts, which are essential for proactive system management and minimizing downtime. Moreover, it supports the transmission of performance data to cloud-based analytics platforms, allowing for the utilization of big data and AI-driven insights for predictive maintenance and energy optimization strategies. In essence, the Communication Interface 1510 is pivotal in transforming the LRTU 1500 into an intelligent, interactive component of the modern, smart building ecosystem.

[0444] Further, the LRTU 1500 may integrate a suite of additional components (not shown) to elevate its operational efficiency and sustainability. An Economizer may ingeniously be incorporated to exploit cooler external air for natural ventilation, substantially curtailing energy expenditure during suitable weather conditions. Photovoltaic Solar Cells may strategically be embedded to capture solar energy, thus supplementing the LRTU's power supply and underscoring its commitment to renewable energy utilization. A Rainwater Harvesting System may be included to collect and repurpose rainwater, aligning with sustainable water resource practices and contributing to the building's eco-friendly initiatives. The system may also include a Condensate Drainage system that ensures effective management and disposal of moisture accumulation, a byproduct of the cooling process, thereby preventing potential water damage and maintaining system integrity.

[0445] To ensure reliable operation, the LRTU 1500 may be outfitted with versatile Power Supplies that can seamlessly switch between conventional grid electricity and alternative energy sources, providing uninterrupted service and energy resilience. User Interfaces may thoughtfully be developed, featuring intuitive touchscreens or tactile buttons, allowing end-users to effortlessly interact with the system for manual adjustments, personalized settings, and system diagnostics, thereby offering a user-centric approach to HVAC system management.

[0446] Referring now to FIG. 16, an automated controller is illustrated that may be used to implement various aspects of the present invention in various embodiments, and for various aspects of the present invention. Controller 1600 may be included in one or more of: a wireless tablet or handheld smart device, a server, an integrated circuit incorporated into a Node, appliance, equipment item, machinery, or other automation. The controller 1600 includes a processor unit 1602, such as one or more semiconductor-based processors, coupled to a communication device 1601 configured to communicate via a communication network (not shown in FIG. 16). The communication device 1601 may be used to communicate, for example, with one or more online devices, such as a smart device, a Node, personal computer, laptop, or a handheld device.

[0447] The processor unit 1602 is also in communication with a storage device 1603. The storage device 1603 may comprise any appropriate information storage device, including combinations of digital storage devices (e.g., an SSD), optical storage devices, and / or semiconductor memory devices such as Random Access Memory (RAM) devices and Read Only Memory (ROM) devices.

[0448] The storage device 1603 can store a software program 1604 with executable logic for controlling the processor unit 1602. The processor unit 1602 performs instructions of the software program 1604, and thereby operates in accordance with the present invention. The processor unit 1602 may also cause the communication device 1601 to transmit information, including, in some instances, timing transmissions, digital data and control commands to operate apparatus to implement the processes described above. The storage device 1603 can additionally store related data in a database 1605 and database 1606, as needed.

[0449] Referring now to FIG. 17, in some embodiments, a RTU according to the present invention may be based upon Magnetocaloric Technology (sometimes referred to herein as “MGT”). MGT utilizes a temperature change in certain materials when exposed to a magnetic field, and be included in the present invention as an alternative and / or a supplement to traditional vapor-compression cooling systems. Unlike conventional systems that rely on compressors, refrigerants, and expansion valves, magnetocaloric RTUs use solid-state magnetocaloric materials and a moving magnetic field to drive heat exchange, resulting in a sealed system with no chemical refrigerants.

[0450] Use of a MGT based RTU may significantly reduce maintenance requirements by eliminating refrigerant leakage issues and compressor failures, which are among the most common service calls in traditional units.

[0451] Some MGT designs using optimized rare earth materials and permanent magnet arrays include compact footprints. The compact footprint allows for an RTU that is comparable in weight, and in some embodiments less weight as compared to a standard RTU system.

[0452] Some embodiments additionally include MGT RTU systems with improved weather resistance as compared to traditional RTUs since magnetocaloric systems can be more fully enclosed and sealed from environmental exposure. Longevity is another benefit of MGT RTUs. The MGT RTU includes fewer moving parts and no high-pressure refrigerant cycles. Magnetocaloric RTUs may offer extended operational life and reduced degradation over time. Additionally, their operation is quieter and potentially more energy-efficient at partial loads.

[0453] MGTs may be favorable for use in sustainability-focused buildings where mechanical simplicity, energy efficiency, and environmental safety are paramount based upon MGT in rooftop units (RTUs) presenting lower environmental impact compared to conventional RTUs that rely on vapor-compression cycles and hydrofluorocarbon (HFC) refrigerants. Traditional RTUs commonly may use synthetic refrigerants like R-410A or R-134a, which are viewed as greenhouse gases with high global warming potentials (GWPs). In contrast, magnetocaloric RTUs operate without any refrigerants, using solid-state magnetocaloric materials and magnetic fields to achieve cooling, thereby eliminating the risk of refrigerant emissions entirely. Additionally, the absence of compressors and complex piping systems may reduce mechanical wear, and the need for frequent servicing.

[0454] As illustrated in FIG. 17, a RTU that is based upon MGT components (MGT RTU 1700). The MGT RTU 1700 components may include a magnetocaloric cooling module 1701 which acts as the prevailing temperature regulating core subsystem. Cooling may be generated on demand via the magnetocaloric effect via the magnetocaloric cooling module 1701. The magnetocaloric cooling module 1701 may replace an / or supplement conventional refrigerant-based compressors by using solid-state materials that respond thermally to changes in magnetic fields. The magnetocaloric cooling module 1701 houses the magnetocaloric material stack and associated mechanical and thermal components required to generate and transfer heat through cyclical magnetization and demagnetization.

[0455] A heat exchanger 1711 may include a Hot Side 1702 and a Cold Side 1703. The Hot Side 1703 is functional to remove heat from the magnetocaloric material after it has been magnetized and has absorbed thermal energy. Positioned at the exhaust side of the heat exchanger 1711. The Hot Side 1702 transfers rejected heat to an outside environment. The Hot Side 1702 functions similarly to a condenser in a traditional HVAC system but operates with solid-state heat and mass flow.

[0456] The cold-side 1702 acts like an evaporator in conventional systems. It absorbs thermal energy from an indoor air stream or return air. As magnetocaloric material in the Magnetocaloric Cooling Module 1701 cools during demagnetization, the cold-side 1702 draws heat from the airstream, effectively lowering its temperature before it is re-circulated through the building.

[0457] The Magnetocaloric Cooling Module 1701 may include an array of magnetocaloric materials (such as gadolinium-based alloys or lanthanides) that physically change temperature when exposed to a magnetic field. The Magnetocaloric Cooling Module 1701 may include a stack of such magnetocaloric materials that are cyclically magnetized and demagnetized to alternately absorb and reject heat The Magnetocaloric Cooling Module 1701 may be operational as a thermodynamic engine of the cooling module.

[0458] A control and sensor system 1709 serves as a digital brain of the MGT RTU 1700, managing operation parameters such as timing, magnetic field modulation, airflow rates, and temperature control. The control and sensor system 1709 if operational to integrate sensor inputs and command outputs for example to: optimize performance, ensure safe operation, and / or communicate with external systems like building automation systems (BAS).

[0459] Thermal sensors 1707 are operational to provide functions such as, one or more of: measure air and component temperatures at various points within the RTU. The thermal sensors 1707 are capable of providing real-time feedback (e.g., no artificial delay) to the control sensor system 1709 for maintaining setpoints, preventing overheating or overcooling, and adjusting fan speeds and magnetization cycles accordingly.

[0460] Additional sensors, such as, for example pressure and / or flow sensors 1708 are operational to perform useful functions, such as, one or more of: monitor airflow rates, static pressure, and differential pressure across filters and heat exchangers. They are essential for ensuring efficient operation, identifying clogs or performance degradation, and enabling predictive maintenance or automated alerts.

[0461] An outdoor air intake / exhaust component 1705 may be operational to allow the MGT RTU 1700 to exchange air with an external environment. The outdoor air intake / exhaust component 1705 is functional to draw in fresh outdoor air for ventilation and / or expels heat-laden air processed by the hot-side heat exchanger. It may include dampers or economizers for energy-efficient operation.

[0462] A supply fan and blower 1704 provides a mechanical force necessary to circulate air through the MGT RTU 1700 and a building serviced by the MGT RTU 1700. The supply fan and blower 1704 moves cooled air from the cold-side heat exchanger into a supply duct, overcoming resistance and maintaining desired airflow rates throughout the building.

[0463] A duct interface 1706 provides for mechanical connections between the duct interface 1706 and a building's HVAC duct system. The duct interface 1706 enables the integration of the MGT RTU 1700 airflow with interior conditioned space, typically through metal flange or curb-mounted connections. For example, duct interface 1706 may include an outlet point where cooled air exits the RTU and enters the building's supply ductwork. It connects to downstream registers or diffusers and is responsible for delivering conditioned air to interior spaces. A return duct interface may include an inlet where warm air from the building re-enters the RTU for cooling. It may connect the building's return air path to the intake of the air handling portion of the unit.

[0464] The Return Air Intake 1710 gathers used indoor air (return air) and channels it back into the MGT RTU 1700 for re-cooling. The Return Air Intake 1710 may contain filters or dampers and plays a critical role in maintaining airflow balance and system efficiency. The “ALR” label likely stands for “Air-Return,” denoting this point as the return air pathway into the unit.

[0465] Pressure and Flow Sensors 1708 may include an integrated set of pressure and airflow monitoring devices within the MGT RTU 1700. The Pressure and Flow Sensors 1708 play the role of ensuring that the MGT RTU 1700 operates within optimal airflow and static pressure ranges. Pressure and Flow Sensors 1708 detect real-time changes in air velocity, volumetric flow rate, and differential pressure across filters, coils, and duct sections. This data is sent to the control system to regulate fan speed, detect airflow blockages, and maintain balanced operation. In magnetocaloric systems, precise thermal exchange may be important to efficiency, therefore accurate flow monitoring facilitates that heat exchangers function correctly and that the MGT RTU 1700 is capable of adapting to varying load conditions. Additionally, Pressure and Flow Sensors 1708 may be functional to trigger alerts for preventative maintenance when abnormal pressure drops or inconsistent flow patterns are detected, helping to extend system life and maintain performance.

[0466] In some embodiments, a Magnetocaloric based RTU will also operate more quietly and potentially more efficient at part-load conditions.

[0467] In some embodiments, a MGT RTU will include sealed systems so that end-of-life disposal is simpler and safer, avoiding the hazardous recovery of refrigerants.

[0468] In another aspect, a RTU based upon MGT may offer significant advantages in installation and maintenance simplicity compared to conventional RTUs, particularly in light of a projected decline in the availability of highly skilled HVAC technicians. Traditional RTUs rely on complex vapor-compression systems that require precise handling of refrigerants, specialized brazing and vacuuming procedures, pressure testing, and compliance with EPA regulations related to refrigerant recovery and charging. These tasks demand extensive training and certification, and mistakes can lead to system inefficiency, refrigerant leaks, or even equipment failure. In contrast, magnetocaloric RTUs are closed-loop, solid-state systems with no refrigerants and fewer mechanical components such as compressors, expansion valves, or accumulators.

[0469] Embodiments include installation of magnetocaloric units using simple modular equipment with steps such as: position, connect to power, interface with ductwork and controls, and commission, thereby requiring fewer specialized skills.

[0470] From a maintenance perspective, the absence of moving parts like belts, pulleys, and refrigerant circuits drastically reduces the number of failure points. This aligns well with a less skilled or semi-skilled future workforce, as tasks will likely be limited to basic diagnostics, sensor replacement, or firmware updates rather than in-depth refrigeration cycle troubleshooting. Moreover, magnetocaloric systems may offer greater reliability and less routine service, which reduces the dependency on frequent technician intervention. As the HVAC industry adapts to labor shortages and skill gaps, magnetocaloric RTUs could represent a more resilient and workforce-friendly solution, especially in large-scale commercial deployments where case of maintenance and system uptime are critical.

[0471] Installing a magnetocaloric rooftop unit (RTU) follows many of the physical steps used in traditional RTU installations but is simplified due to the absence of refrigerant systems and compressors. The process begins with structural preparation on the roof, where a pre-fabricated roof curb is installed to support the unit and align with duct openings. The curb may be secured to the roof deck, and penetrations are made for supply and return air ducts, electrical conduits, and control cabling. In embodiments with a MGT systems comprising fewer moving parts and generate less vibration than compressor-based systems, vibration isolation and structural reinforcement requirements may be reduced, potentially lowering installation complexity and cost.

[0472] With a curb in place, a magnetocaloric RTU may be lifted onto the rooftop using a crane. The unit is positioned onto the curb and aligned with the duct and mounting openings. Final anchoring is done according to building codes, including wind uplift compliance. Depending on the specific design, magnetocaloric units may be lighter than traditional RTUs, which can reduce crane size and case handling during placement.

[0473] Electrical connections may be made to provide power to the unit, typically using standard commercial voltages such as 208V or 480V. Control wiring is connected either to the building automation system (BAS) or to a standalone thermostat. One advantage at this stage is that refrigerant piping, pressurization, or leak testing may not be required, as magnetocaloric systems do not use chemical refrigerants. This may eliminate a step in traditional HVAC commissioning and reduces a need for EPA-certified personnel.

[0474] Ductwork is connected, and supply and return lines may be routed through the curb or into side-mounted plenums, depending on the unit design. Ducts may be sealed and insulated to minimize energy loss and ensure optimal airflow. With fewer mechanical integration requirements than vapor-compression systems, these connections can typically be completed more quickly.

[0475] With the MGT RTU powered on, a magnetocaloric cycle is initiated through a solid-state system that moves heat using magnetic fields and magnetocaloric materials. Installers check airflow rates, actuator function, sensor outputs, and basic system diagnostics. Since there are no refrigerant pressures to balance or compressors to stage, start-up may be faster and more straightforward, making it easier for less-experienced technicians to perform correctly.

[0476] While the invention has been described in conjunction with specific embodiments, it is evident that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the foregoing description. Accordingly, this description is intended to embrace all such alternatives, modifications and variations as fall within its spirit and scope.

[0477] The headings utilized in this document serve solely for organizational purposes and should not be interpreted as limiting the scope of either the description or the claims. Throughout this application, the term “may” is employed in a permissive sense, implying the potential for an action or feature, rather than a mandatory sense. Additionally, the words “include,”“including,” and “includes” are used in an inclusive manner, meaning “including, but not limited to”. To aid clarity, similar reference numerals have been used, where feasible, to denote similar elements across different figures.

[0478] The expressions “at least one,”“one or more,” and “and / or” are open-ended and operate both conjunctively and disjunctively. For example, the phrases “at least one of A, B, and C,”“at least one of A, B, or C,”“one or more of A, B, and C,”“one or more of A, B, or C,” and “A, B, and / or C” encompass various combinations: A alone, B alone, C alone, A and B, A and C, B and C, or A, B, and C together.

[0479] The term “a” or “an” entity implies one or more of that entity. Consequently, the terms “a” (or “an”), “one or more,” and “at least one” are used interchangeably in this document. It is also important to note that the terms “comprising,”“including,” and “having” are used synonymously.

[0480] Features described in this specification in the context of separate embodiments can also be integrated into a single embodiment. Conversely, features described within a single embodiment can be implemented in multiple separate embodiments, either alone or in any suitable sub-combination. Furthermore, while certain features may be described and initially claimed in combination, it is possible to remove one or more features from the combination, resulting in a claimed sub-combination or variation thereof.

[0481] AI though method steps may be illustrated in a specific order, this should not be construed as a requirement that these operations must be performed in the depicted order or sequentially, nor that all illustrated operations are necessary for achieving the desired outcomes.

[0482] The separation of system components in the described embodiments is not mandatory for all embodiments. The components and systems described can typically be integrated into a single product or distributed across multiple products. Therefore, while specific embodiments have been detailed, other embodiments fall within the scope of the appended claims. In some instances, the actions recited in the claims can be performed in a different order and still yield desirable results. Moreover, the methods, systems or apparatuses shown in the accompanying figures do not necessarily require the depicted order or sequential progression to achieve beneficial outcomes. In certain implementations, selective arrangements may prove beneficial. However, it should be understood that various modifications can be made without departing from the spirit and scope of the claimed disclosure.

Examples

Embodiment Construction

[0059]The present invention provides a system, apparatus and methods for a Smart Roof Top Unit (SRTU) that integrates advanced infrared (IR) temperature monitoring to enhance its operational efficiency and reliability. The system utilizes IR cameras strategically placed on or around the SRTU unit to continuously capture thermal images or video feed of the SRTU. These thermal images are useful for identifying temperature variations and detecting potential issues such as overheating or frost accumulation.

[0060]The captured IR thermal images may be converted into digital value patterns, allowing for precise quantitative analysis by a Controller and / or AI engine. Each pixel in the thermal image corresponds to a specific temperature value, which is digitized to form a detailed thermal map of the SRTU. This digital representation of thermal data is essential for the subsequent analysis and control processes managed by the Controller and / or AI engine integrated within the SRTU or on a clou...

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 676,283, filed Jul. 26, 2024, and entitled SMART HVAC ROOFTOP UNITS WITH INTEGRATED AI AND THERMAL IMAGING FOR ENHANCED OPERATIONAL CONTROL, the entire contents of which are incorporated herein by reference.FIELD OF THE DISCLOSURE

[0002] The present invention relates to methods and apparatus for enhancing the efficiency and performance of heating, ventilation, and air conditioning (HVAC) systems. More specifically, the present invention pertains to a rooftop unit (RTU) equipped with infrared thermal imaging and automated processes for real-time monitoring, predictive maintenance, and optimized defrosting processes. The invention provides for the use of thermal imaging technology, such as, for example, infrared (IR) imaging, to generate thermal profiles and monitor, and / or predict thermal loads of RTU components. By leveraging these thermal profiles, the system optimizes the operation of RTU components, providing more efficient and effective heating, cooling, and ventilation.BACKGROUND OF THE DISCLOSURE

[0003] Rooftop units (RTUs) are widely used in commercial and industrial buildings to provide heating, ventilation, and air conditioning. Traditional RTUs, however, often suffer from several limitations that can affect their performance, efficiency, and reliability. Key issues include the inability to accurately monitor component temperatures, lack of real-time data analysis, inefficient defrosting processes, and reactive rather than proactive maintenance strategies.

[0004] Conventional RTUs typically rely on discrete sensors to monitor the temperature of critical components such as compressors, coils, and fans. These sensors can only provide point-specific data, which may not accurately represent the overall thermal condition of the components. Additionally, physical contact sensors can be prone to wear and tear, leading to inaccurate readings and potential failures.

[0005] Defrosting is a critical process in RTUs, particularly in regions with cold climates where frost accumulation on evaporator coils can severely impact performance. Traditional defrosting methods often involve periodic shutdowns and manual interventions, leading to energy inefficiency, increased wear on components, and potential disruptions in climate control.

[0006] Maintenance of RTUs is typically reactive, addressing issues only after they have caused operational problems. This approach can result in unexpected downtime, costly repairs, and reduced lifespan of the unit. Predictive maintenance strategies, which rely on continuous monitoring and data analysis to anticipate failures, are not commonly integrated into traditional RTUs.

[0007] Further, buildings account for a considerable portion of the total energy consumption, especially in developed countries. This energy consumption includes energy used in building construction in the manufacture of equipment that is incorporated into a building deployed for operation.

[0008] Consequently, the construction industry has an opportunity to improve its impact on the degradation of the environment. Standards such as LEED (Leadership in Energy and Environmental Design) encourage the construction industry to adopt sustainable practices that can mitigate its environmental impact. LEED is a green building certification program developed by the U.S. Green Building Council (USGBC). LEED includes a set of rating systems for the design, construction, operation, and maintenance of green buildings, homes, and communities.

[0009] Buildings may earn different levels of certification based on a number of points the building achieves in various categories. Various LEED designations include, for example, one or more of: Certified: based upon a building earning 40-49 points; Silver: based upon a building earning 50-59 points; Gold: based upon a building earning 60-79 points; and Platinum: based upon a building earning 80+ points.

[0010] The categories in which these points can be achieved include one or more of: Sustainable Sites; Water Efficiency; Energy and Atmosphere; Materials and Resources; Indoor Environmental Quality; Innovation in Design; and Regional Priority.

[0011] LEED promotes sustainability by encouraging designs that: use less water and energy; reduce greenhouse gas emissions; improve indoor environmental quality; and create a healthier and safer environment for occupants.

[0012] Energy involved in the manufacture, transportation, and installation on the top of a commercial building of such large heavy, galvanized steel items, such as a Roof Top Unit (RTU), involves a significant amount of energy and a consequential carbon footprint. The structural strength that is required to support the heavy weight of a traditional RTU is also significant and may further add to detrimental aspects of a LEED rating.

[0013] There is a need within the industry to develop and implement solutions that not only minimize environmental impact but also align with the evolving sustainability standards like LEED. The focus is increasingly shifting towards creating materials and systems that are not only efficient in their use but also contribute to the overall reduction of the carbon footprint of buildings. This shift includes rethinking the materials and design of building components such as HVAC systems, particularly Roof Top Units (RTUs), to make them more eco-friendly.SUMMARY OF THE DISCLOSURE

[0014] The present invention addresses these gaps by introducing a Smart Rooftop Unit (SRTU) with integrated infrared thermal imaging and AI. The system may provide continuous, real-time monitoring of component temperatures, proactive defrosting management, and predictive maintenance capabilities. The SRTU leverages detailed thermal imaging data, analyzed by AI, to optimize HVAC operations, enhance energy efficiency, reduce downtime, and extend the lifespan of critical components.

[0015] A Rooftop Unit (RTU) is a type of HVAC (Heating, Ventilation, and Air Conditioning) system that is typically mounted outside of a commercial building, such as on a roof of the commercial building. RTUs can provide heating, cooling, and ventilation to the space below. RTU is typically housed in its own metal housing or casing (or cabinet) that is specifically constructed to withstand external environmental conditions since it's located on a building's roof. The housing or casing contains major components of the HVAC system and protects the major components from weather, debris, and potential damage. The housing or casing of an RTU is typically manufactured from galvanized steel or other heavy material with an energy-intensive manufacturing process. The galvanized steel often includes multiple panels and may be fashioned into several compartments. The housing will have air intake portions and outlet portions.

[0016] According to the present invention, a SRTU is capable of converting thermal images into digital value patterns, generate heat maps, and dynamically adjust defrost parameters based on real-time data and AI analysis on SRTU components. Such analysis SRTU operating at optimal performance levels, maintaining a comfortable indoor environment while minimizing energy consumption and maintenance costs.

[0017] In some embodiments of the invention, the SRTU may be equipped with an advanced infrared thermal imaging system integrated with artificial intelligence (AI) to provide continuous, real-time monitoring of critical components such as compressors, coils, fans, and electrical circuits. The infrared thermal imaging system captures the thermal radiation emitted by these components and converts it into high-resolution thermal images. These images are digitized and analyzed by the Controller and / or AI engine, which uses machine learning algorithms to identify temperature anomalies, analyze trends, and correlate the thermal data with other operational variables like defrost cycles and power usage. The AI system can predict potential issues, such as overheating or component failures, and recommend maintenance actions before these issues cause significant downtime or damage.

[0018] Additionally, the SRTU may utilize the infrared thermal imaging system to generate real-time heat maps, highlighting areas with excessive frost accumulation. This may enable the system to direct defrost airflow precisely to the affected areas using adjustable louvers, jets, and multiple fans, optimizing the defrosting process and improving energy efficiency. The Controller and / or AI engine continuously adjusts the RTU's operation based on real-time data, providing optimal performance and preventing thermal stress. Users can monitor the system through a user-friendly interface that displays thermal images and operational data, receiving alerts and maintenance recommendations via mobile devices. The SRTU may also be constructed to adapt to varying environmental conditions and operational demands by incorporating data on geographic location, seasonal trends, and weather predictions, providing reliable and efficient operation in diverse settings.

[0019] In some embodiments of the invention, multiple infrared (IR) cameras may be strategically installed around the SRTU on the roof to provide comprehensive coverage from all directions. This arrangement may ensure that the entire surface of the SRTU is monitored for heat variations, allowing for a detailed analysis of temperature distribution and thermal behavior. The IR cameras capture high-resolution thermal images, which are then processed and analyzed by the AI system. By continuously monitoring the thermal patterns across the SRTU, the AI system can detect anomalies, such as unexpected hot spots or uneven heat distribution, which may indicate potential inefficiencies or emerging issues with the unit's operation. This data enables the AI to predict component failures, optimize performance, and recommend proactive maintenance actions.

[0020] The AI system may use the thermal data to control the SRTU dynamically, adjusting parameters such as cooling load, fan speeds, and defrost cycles to ensure optimal efficiency. For example, if the cameras detect an area of the SRTU that is consistently overheating, the AI can increase cooling to that specific region or recommend cleaning or servicing to remove any obstructions or faults causing the issue. Similarly, by monitoring the heat patterns during defrost cycles, the AI can fine-tune the process to target areas with the most frost accumulation, thereby improving the overall energy efficiency of the unit.

[0021] Furthermore, the system can provide detailed recommendations to maintenance personnel through a user interface, displaying thermal images, highlighting areas of concern, and suggesting specific actions, such as replacing a component, adjusting settings, or scheduling a thorough inspection. These recommendations are based on both real-time data and historical trends, allowing for a predictive maintenance approach that reduces downtime and extends the lifespan of the SRTU. Additionally, by continuously learning from the thermal data, the AI system can improve its predictive accuracy over time, making the SRTU smarter and more efficient. This comprehensive thermal monitoring and AI-driven analysis ensure that the SRTU operates at peak performance, providing reliable and efficient climate control while minimizing energy consumption and maintenance costs.

[0022] In some embodiments, the present invention also provides methods and apparatus for reducing one or both of: the weight and carbon footprint associated with an RTU suitable to contain HVAC components on the roof area of a large building. In some embodiments of the invention, the SRTU's housing may primarily be constructed from Polypropylene Random Copolymer (PPR), a material chosen for its lightweight yet robust characteristics. To fortify this, the PPR may be coated with a protective layer, which may be either galvanized steel or a high-grade impervious plastic. This outer coating is constructed to withstand adverse weather conditions, such as heavy rainfall, snow, intense sunlight, and temperature extremes. In some configurations, the SRTU unit may further benefit from a dual-layered approach where the PPR is sandwiched between two such protective coatings. This design not only offers an external shield against environmental factors but also enhances the internal stability of the unit. For example, the outer layer may be a corrosion-resistant alloy in coastal areas to combat saltwater damage, while an inner layer of UV-reflective material may be used in sunnier climates to prevent degradation due to UV exposure. Additionally, the outer surface may also feature a textured finish to minimize dust and debris accumulation, maintaining the unit's efficiency and reducing cleaning requirements.

[0023] In some embodiments of the invention, the SRTU may be equipped with smart technology interfaces. These interfaces allow for remote monitoring and control of the unit, enabling users to optimize performance based on real-time data. This technology can adjust settings for energy efficiency, monitor the health of the unit, and provide alerts for maintenance needs. Such integration with IoT (Internet of Things) devices enhances user experience and operational efficiency. This remote accessibility is particularly advantageous for large buildings or complexes where on-site management of each unit can be logistically challenging. This smart technology goes beyond mere remote control; it may enable the SRTU to deliver real-time data about its performance and condition. This feature may be instrumental in optimizing the unit's performance for energy efficiency. Users can adjust settings such as temperature and airflow, based on real-time feedback, ensuring the unit operates at peak efficiency while minimizing energy consumption. This adaptability not only leads to cost savings but also aligns with environmental sustainability goals. This may continuously analyze the functioning of the SRTU, detecting potential issues before they escalate into major problems. Users receive alerts for regular maintenance or urgent repair needs, enabling proactive management of the unit. This pre-emptive approach to maintenance enables the SRTU to operate reliably over its lifespan, reducing downtime and avoiding costly emergency repairs. The integration of smart technology interfaces transforms the SRTU into a highly intelligent, responsive, and efficient system. This integration may also represent a significant stride toward the future of smart building management, where convenience, efficiency, and sustainability converge.

[0024] Some implementations include an SRTU constructed with a core layer made from Polypropylene Random Copolymer (PPR), chosen for its durability and versatility. Affixed to this core layer is at least one protective layer, which can be a metallic layer composed of materials like aluminum or galvanized steel, a non-metallic UV-resistant polymer, high-grade impervious plastic, or a nanocomposite coating constructed for enhanced durability and reflectivity. In some embodiments, the SRTU features a sandwich structure, where a first protective layer is applied to one side of the PPR core and a second, potentially different, protective layer is applied to the other side.

[0025] The unit's modularity can be a key aspect, with components configured for easy assembly, disassembly, and maintenance. Such a design approach allows for quick servicing and potential future upgrades. The modular components may include detachable panels with standardized connectors for efficient installation and servicing, and they are constructed to be interchangeable to cater to specific building requirements.

[0026] The SRTU may also comprise an integrated control system equipped with a Controller and / or AI engine and various sensors, including, but not limited to, temperature, pressure, humidity, and air-quality sensors. This system can operate in conjunction with a building management system (BMS), enhancing the overall efficiency and responsiveness of the HVAC setup. The control system is also capable of wireless connectivity for remote monitoring and control, adding a layer of convenience and advanced functionality.

[0027] Additional features of the SRTU may include an economizer for utilizing outside air for indoor temperature control, an integrated solar panel system for auxiliary power generation, and a rainwater harvesting system. These features may contribute to the unit's energy efficiency and environmental sustainability. A condensate drain may also be included to manage moisture from the cooling process, and a thermal insulation system adaptable to varying climatic conditions optimizes operational efficiency.

[0028] For enhanced user comfort and structural compatibility, the SRTU may include a sound attenuation system within the protective layers to reduce operational noise and a vibration-damping mechanism to minimize the transmission of vibrations to the building structure. The protective layer may also comprise a self-cleaning surface, reducing maintenance requirements.

[0029] In some embodiments of the invention, the SRTU may be enhanced with a layer of adaptive insulation, which intelligently alters its thermal resistance based on real-time temperature readings. This innovative insulation layer employs materials that can expand or contract, or otherwise change their insulating properties, in response to external temperature shifts. Such smart materials enable the SRTU to maintain optimal internal temperatures more efficiently by reducing the need for additional heating or cooling when external conditions are favorable. This dynamic adjustment capability makes the SRTU more energy-efficient, potentially leading to lower operational costs and a reduced environmental footprint. The adaptive insulation layer can be integrated during the manufacturing process or retrofitted into existing units, providing a versatile solution for new and upgraded HVAC systems.

[0030] In some embodiments of the invention, the modular components may be constructed from biodegradable or compostable materials. These environmentally conscious materials may be selected to minimize the ecological footprint upon the end of the unit's service life, ensuring that components break down naturally without harming the ecosystem. This approach not only contributes to sustainable manufacturing practices but also aligns with green building certifications, potentially enhancing the overall environmental performance rating of the buildings where these units are installed.

[0031] In some embodiments of the invention, the SRTU may be enhanced with smart surface coatings on its outermost protective layer. These advanced coatings may be engineered to change color or texture in response to fluctuations in temperature. This thermochromic feature provides a visual cue to the unit's operating condition, allowing for easy and immediate surface condition monitoring without the need for complex sensors or equipment. Such smart coatings not only serve as a diagnostic tool for maintenance personnel but also offer a way to visually ensure that the unit is functioning within its optimal temperature range, thus contributing to proactive maintenance and energy efficiency.

[0032] In some embodiments of the invention, the SRTU may feature a modular design that allows for customizable configuration of its components. This modularity enables the unit to be tailored to specific building needs, such as varying roof sizes or shapes. The ability to customize the layout of components like air intakes, exhausts, and service panels enables the SRTU to be adapted to a wide range of architectural designs.

[0033] Some embodiments may incorporate vibration-damping materials and designs to minimize operational noise and structural impact. This feature is particularly important in residential areas or buildings where noise reduction is a priority. The vibration damping is achieved through the strategic placement of materials within the unit's structure, ensuring that the unit operates quietly while maintaining its efficiency and durability.

[0034] In certain embodiments, the SRTU may be constructed with an aerodynamic shape to minimize wind resistance and load on the building structure. This design is especially beneficial in high-wind areas or tall buildings, where wind load can be a significant factor. The aerodynamic design also contributes to the overall efficiency of the unit, reducing potential energy loss due to wind resistance.

[0035] Some versions of the SRTU may integrate a heat recovery system, which captures and reuses waste heat from the HVAC process. This system enhances the overall energy efficiency of the unit, reducing the energy needed to heat or cool the building. The heat recovery system is constructed to be compatible with the modular nature of the SRTU, allowing for easy integration into different unit configurations.

[0036] In another embodiment, the SRTU may include an advanced humidity control system. This system is constructed to maintain optimal indoor humidity levels, which is critical for comfort and health. The humidity control is particularly beneficial in regions with high humidity or arid climates. It works in tandem with the HVAC system to ensure a comfortable and healthy indoor environment, further enhancing the SRTU's appeal in diverse climatic conditions.BRIEF DESCRIPTION OF THE DRAWINGS

[0037] FIG. 1 illustrates an exemplary overview of an SRTU installed on a building roof comprising multiple IR cameras to capture thermal images of the SRTU.

[0038] FIG. 1A illustrates an exemplary SRTU system integrating SRTU control system, IR cameras and BMS in accordance with some embodiments of the present invention.

[0039] FIG. 1B illustrates exemplary fields of view for multiple IR cameras to capture thermal images of an SRTU.

[0040] FIG. 1C illustrates multiple thermal images combined to form a single thermal image for AI analysis.

[0041] FIG. 2 illustrates an exemplary embodiment of an SRTU.

[0042] FIG. 2A illustrates a schematic representation of SRTU integration with the building HVAC system.

[0043] FIG. 3 illustrates an exemplary embodiment of a modular SRTU under supervision of multiple thermal cameras.

[0044] FIGS. 4 and 4A illustrate an exemplary SRTU control system providing automated design suggestions for the SRTU to improve its performance.

[0045] FIG. 5 illustrates an exemplary SRTU system integrating with an IR camera and BMS in accordance with some embodiments of the present invention.

[0046] FIG. 5A illustrates an exemplary embodiment of an SRTU system in accordance with the present invention.

[0047] FIG. 6 illustrates an exemplary embodiment of an SRTU with an internal component's layout.

[0048] FIG. 7 illustrates an internal view of the SRTU with emphasis on airflow dampers and corresponding temperature distribution on SRTU surface.

[0049] FIG. 8 illustrates an SRTU cross-section highlighting an exemplary multistage filtration process and temperature distribution related to the filters.

[0050] FIG. 9 illustrates SRTU temperature modulation components featuring heating and cooling coils and their respective temperature distributions on top surface of the SRTU.

[0051] FIG. 10 illustrates the SRTU's centrifugal EC fan, associated airflow mechanics and IR camera installed within the SRTU to monitor heat signatures of the internal SRTU components.

[0052] FIG. 11 illustrates operational dynamics of the SRTU with an open damper for air recirculation.

[0053] FIG. 12 illustrates an SRTU air management system with a closed damper and fresh air intake.

[0054] FIG. 13 illustrates an exemplary block diagram of an SRTU system for an HVAC system.

[0055] FIGS. 14, 14A, and 14B illustrate an exemplary flow chart of method steps that may be performed in some embodiments of the present invention.

[0056] FIG. 15 illustrates an exemplary block diagram of an LRTU system for an HVAC system.

[0057] FIG. 16 illustrates a schematic diagram of a controller.

[0058] FIG. 17 illustrates a schematic diagram of an RTU based upon Magnetocaloric Technology.DETAILED DESCRIPTION

[0059] The present invention provides a system, apparatus and methods for a Smart Roof Top Unit (SRTU) that integrates advanced infrared (IR) temperature monitoring to enhance its operational efficiency and reliability. The system utilizes IR cameras strategically placed on or around the SRTU unit to continuously capture thermal images or video feed of the SRTU. These thermal images are useful for identifying temperature variations and detecting potential issues such as overheating or frost accumulation.

[0060] The captured IR thermal images may be converted into digital value patterns, allowing for precise quantitative analysis by a Controller and / or AI engine. Each pixel in the thermal image corresponds to a specific temperature value, which is digitized to form a detailed thermal map of the SRTU. This digital representation of thermal data is essential for the subsequent analysis and control processes managed by the Controller and / or AI engine integrated within the SRTU or on a cloud server.

[0061] The Controller and / or AI engine may assess the digital value patterns by mapping them against other variable trends such as defrost cycles, power usage, and efficiency metrics. For defrost cycles, the AI analyzes the thermal data to detect frost build-up on the evaporator coils. When frost accumulation is identified, the AI initiates the defrost cycle and monitors the process to ensure effective and efficient frost removal. The Controller and / or AI engine also evaluates power usage trends, optimizing the operation to reduce energy consumption by adjusting settings based on real-time thermal data and historical performance. Efficiency may further be enhanced by minimizing wear and tear on components, reducing the maintenance load, and extending the lifespan of the unit.

[0062] To achieve maximum performance, the Controller and / or AI engine enables the SRTU to operate at peak efficiency, providing maximum cooling capacity when needed. This may include fast transitions between different operating states to respond promptly to changes in cooling or heating demands. When the system receives a command for additional cooling, the AI anticipates the resulting temperature map based on the expected load increase. This proactive adjustment may allow the SRTU to meet the new cooling or heating demands efficiently without overburdening the system.

[0063] The Controller and / or AI engine continuously monitors ambient conditions within the building spaces to be cooled, using data from various sensors integrated in the Building Management System (BMS) of the building. These sensors measure temperature, humidity, and airflow within the controlled space, providing comprehensive real-time environmental data. Additionally, infrared imaging is used to assess the current state of the HVAC equipment and historical trends, identifying whether the equipment is operating under normal conditions or experiencing high stress that can lead to potential failures. The system can also assess the number of occupants in specific areas, using this information to adjust HVAC demand dynamically.

[0064] Predictive HVAC demand may also be calculated based on several factors, including the day of the week, time of year, historical data, and geographic location. For example, the system may anticipate higher cooling demands on workdays and adjust the operation accordingly. Seasonal adjustments and comparisons between historical and current ambient data further refine the demand predictions, providing optimal performance and energy efficiency.

[0065] During defrost cycles, the system receives ambient conditions of the airflow used for defrosting. The Controller and / or AI engine can adjust the temperature and humidity of the defrost airflow to optimize the defrost process. A detailed heat map of the area to be defrosted is generated, indicating regions with excessive frost accumulation. Based on the heat map, the Controller and / or AI engine directs the defrost flow to specific areas using louvers, high-velocity jets, and / or multiple fans, providing targeted and efficient defrosting.

[0066] The Controller and / or AI engine also determines the optimum defrost state by defining specific criteria such as the most cooling power, most energy efficiency, and most responsiveness. By continuously analyzing the thermal data and adjusting the defrost parameters, the system enables the SRTU to operate efficiently, minimize energy consumption, and maintain optimal performance.

[0067] The present invention also provides an improved HVAC RTU design and construction, featuring a Smart RTU (SRTU) predominantly constructed from synthetic materials like Polypropylene Random Copolymer (PPR). The SRTU is further fortified with a weather-resistant surface coating, meticulously engineered to resist the external environmental elements it encounters atop a building's roof. The robust housing or casing of the SRTU safeguards the HVAC system's core components against weather, debris, and potential harm. The weather-resistant surface coating of the SRTU, which may include materials such as galvanized steel or other metallic or impervious plastic coatings, provides a shield against the adverse physical impacts of various weather conditions.

[0068] The SRTU is preferably formed by multiple disparate portions that may be configured to a size and shape specific to deployment suitable for a particular building, or portion of a building. It is noted that in some embodiments, different portions may be manufactured using different modalities of manufacturing processes. For example, larger portions may be extruded PPR onto a thin coating of galvanized steel, and smaller portions of intricate shapes may be injection molded or 3D printed and coated with a metallic coating.

[0069] In some embodiments of the invention, a novel design for Polypropylene Random Copolymer (PPR) Smart Roof Top Units (SRTUs) may be tailored for outdoor installations to conserve precious indoor space and address the environmental shortcomings of traditional HVAC materials. Recognizing that conventional construction materials for RTUs carry a substantial carbon footprint, the invention proposes a comparatively lightweight, eco-friendly alternative that significantly reduces the structural demands on buildings and the associated energy consumption during transport and installation.

[0070] The SRTU's primary structure is crafted from PPR due to its favorable attributes-being both lightweight and less taxing on the environment. However, to ensure longevity and resistance to the harshness of direct sunlight and weather conditions, the PPR requires additional protection. To this end, the invention incorporates a sheeting of PPR with a thin metallic or non-metallic barrier (protective layer), such as, but not limited to, stainless steel, galvanized steel, or aluminum. This layer offers structural integrity while providing a shield against the elements, effectively decreasing the volume of heavier metallic materials traditionally used.

[0071] The embodiment may contemplate a metallic or non-metallic layer that may be applied solely to the exterior or may envelop both sides of the PPR, essentially encapsulating the plastic core. This metallic protection can be achieved through a bonding process of PPR to metallic sheets or by spraying a metallic coating onto the PPR sheet, which may be produced via extrusion or 3D printing techniques.

[0072] The SRTU design significantly mitigates environmental impact not only due to the more sustainable manufacturing process of PPR compared to steel but also because the unit's comparatively lightweight nature demands less energy for transportation. A preferred cylindrical design of the SRTU is suggested, which can be realized by rolling PPR / metal composite materials into shape. This may involve constructing the SRTU from panels that are cut and assembled, or using portions of PPR protected with metallic coating alongside portions that are solely metallic, depending on the needs.

[0073] The SRTUs are non-corrosive and suitable for retrofitting applications that demand higher hygiene standards. The installation process is expedited, leading to reduced labor costs and time. With a higher R-value, these SRTUs provide better insulation, leading to energy savings. The flexible supply chain for PPR and metallic materials contributes to the SRTU's adaptability in production and distribution.

[0074] Monitoring the health of the SRTU is facilitated by measurements across the metallic portions, where stresses may be assessed via changes in electrical resistance. Furthermore, the design supports sustainability by allowing for the regrinding of plastic components and the recycling of steel, thereby contributing to a circular economy in HVAC system production.

[0075] In some embodiments, building upon the innovative design of the SRTU, further enhancements may be made to optimize its functionality and environmental compatibility. One such enhancement may involve the integration of an energy recovery ventilator (ERV) system within the SRTU. This system may capture the energy from exhaust air to precondition incoming fresh air, significantly improving energy efficiency, especially in extreme weather conditions. This ERV integration may be particularly beneficial in maintaining indoor air quality while reducing the energy load on the HVAC system. Additionally, considering the growing focus on sustainable energy sources, the SRTU may incorporate photovoltaic solar fabric, a flexible and lightweight material, over portions of its surface. This solar fabric may also serve as an additional power source besides acting as an extra protective layer, contributing more to the unit's overall energy efficiency, and reducing its reliance on traditional energy sources.

[0076] Other embodiments may enhance the SRTU's adaptability and maintenance case through the incorporation of smart diagnostic sensors. These sensors may continuously monitor the unit's performance and health, providing real-time data analytics for predictive maintenance and early detection of potential issues. The use of such advanced diagnostics may extend the lifespan of the SRTU and optimize its performance.

[0077] Furthermore, in some embodiments, for the outer weather-resistant coating or layer, the use of nano-coatings may offer superior protection. Implementing such a coating may significantly enhance the unit's resilience and longevity. Nano-coatings, at the forefront of material technology, are composed of nanoparticles that, when applied to a surface, create an incredibly thin yet highly effective protective layer. These coatings are renowned for their exceptional durability and their resistance to a wide array of environmental stressors, including UV rays, moisture, and extreme temperature fluctuations. The application of nano-coatings on the SRTU's outer surface may impart several significant advantages. Firstly, with the resistance to UV radiation, the unit's material does not degrade or weaken over time due to prolonged sun exposure, a common issue on rooftops. This feature is particularly important in maintaining the structural integrity and appearance of the unit. Secondly, the hydrophobic nature of many nano-coatings makes the SRTU resistant to moisture, preventing issues such as corrosion, mold growth, and water damage, which are common in outdoor environments. This moisture resistance further extends the unit's operational lifespan and reduces maintenance needs.

[0078] Moreover, nano-coatings are adept at handling extreme temperature variations, protecting the SRTU from the thermal expansion and contraction that can occur in fluctuating climates. This adaptability enables the unit to remain structurally sound and functional regardless of seasonal temperature shifts. Another noteworthy aspect of nano-coatings is their self-cleaning properties. Due to their unique surface characteristics, dirt and debris are less likely to adhere to the coated surface, meaning the SRTU remains cleaner without requiring frequent manual cleaning, thus reducing maintenance efforts and costs.

[0079] Nano-coatings, characterized by their molecular-level precision and robust protective qualities, encompass a diverse range of materials, each tailored for specific applications. One prominent example is Titanium Dioxide (TiO2) nano-coatings, widely used for their photocatalytic properties and UV protection, making them ideal for outdoor applications like HVAC units. Another example is Silicon Dioxide (SiO2) or silica-based nano-coatings, renowned for their hydrophobic (water-repellent) qualities, which effectively protect surfaces from moisture and reduce dirt accumulation. Additionally, Zinc Oxide (ZnO) nano-coatings are noted for their antimicrobial properties and UV protection, often used in medical and outdoor equipment. Carbon nanotubes, though more specialized, offer exceptional strength and thermal conductivity, which can be advantageous in heat-intensive environments. Moreover, graphene, a single layer of carbon atoms arranged in a hexagonal lattice, is gaining attention for its remarkable strength, electrical conductivity, and thinness, making it a groundbreaking material in nano-coatings. Lastly, Polyurethane nano-coatings are utilized for their flexibility and durability, providing a resilient protective layer against physical abrasions and environmental wear and tear. Each of these nano-coating materials offers unique benefits, from UV protection and hydrophobicity to antimicrobial properties and structural strength, thus providing versatile solutions for enhancing the durability and functionality of various applications, including HVAC systems.

[0080] In some embodiments of the invention, the outer weather-resistant coating or layer of the SRTU unit may be constructed using PPR (Polypropylene Random Copolymer) that has been enhanced with nano-coatings. This approach involves imbuing the PPR with nano-scale materials to significantly bolster its protective qualities. In some other cases, PPR or other polymers can be used as part of a nanocomposite coating for the outer weather-resistant coating or layer of the SRTU unit. In such cases, nanoparticles or nanofillers (e.g., silica nanoparticles, clay nanoparticles) can be dispersed within a polymer matrix (including PPR) endowing it with superior mechanical strength and improved barrier properties, which are essential for withstanding environmental stressors. These nanocomposite coatings demonstrate enhanced performance characteristics over traditional polymer coatings, including increased durability, resistance to UV radiation, moisture, and thermal extremes. While PPR in its standard form is not a nano-coating material, its amalgamation with selected nanoparticles or nanofillers in a nanocomposite arrangement allows it to achieve advanced functionalities. This integration effectively elevates the weather-resistant capabilities of the SRTU, ensuring its longevity and reliability as an HVACSolution

[0081] Some embodiments of the invention may include an enhanced modular design for the SRTU unit, implementing a snap-fit or interlocking mechanism for joining different portions of the unit for simplifying the assembly process, making it more efficient and cost-effective, especially during installation or routine maintenance. The snap-fit mechanism may involve designing the edges of the SRTU's modular components with complementary shapes that can easily click or lock together without the need for additional fastening tools or hardware. This design not only streamlines the assembly process but also significantly reduces the time and labor involved in the installation. The interlocking parts are precision-engineered to ensure a secure and robust connection, important for maintaining structural integrity and performance efficiency of the HVAC system. This method of assembly is particularly advantageous in rooftop environments, where ease of installation is paramount due to the often challenging and less accessible nature of these spaces. Further, in some cases, these interlocking parts may also be joined together using basic fastening tools like nuts, bolts, or screws.

[0082] Furthermore, the snap-fit design inherently allows for easy disassembly, which is a major advantage during maintenance or repair operations. Service technicians can quickly disengage the interlocking components, perform maintenance or replacements, and reassemble the unit with minimal effort and time. This feature not only enhances the serviceability of the SRTU but also contributes to reduced maintenance costs over its lifespan.

[0083] Moreover, this modular and tool-less assembly approach can facilitate customizable configurations of the SRTU. Depending on the specific needs of a building's HVAC system, components can be added, removed, or rearranged with greater flexibility, adapting to varying architectural demands or changes in air conditioning requirements over time. This flexibility, combined with the ease of assembly, positions the SRTU as a highly adaptable and user-friendly option in the realm of HVAC solutions.

[0084] In the following sections, detailed descriptions of examples, apparatuses and methods will be given. The description of both preferred and alternative examples, though thorough, are exemplary only. It is understood by those skilled in the art, that various modifications and alterations may be apparent and within the scope of the present invention. Unless otherwise indicated by the language of the claims, the examples do not limit the broadness of the aspects of the underlying invention as defined by the claims.

[0085] Referring now to FIG. 1, an exemplary view of the SRTU 100 as part of an HVAC system, incorporating the principles and innovative aspects discussed in the present invention. The SRTU 100 may be constructed to optimize performance through real-time data acquisition and analysis.

[0086] According to embodiments of the present invention, a plurality of IR cameras 110A-110B, may strategically be positioned on, around or within the SRTU 100 to capture comprehensive thermal images from different angles. The IR cameras 110A and 110B may monitor the surface temperatures of various components, capturing high-resolution thermal images that are essential for detecting anomalies and providing efficient operation. The captured images may be transmitted to a SRTU control system 112 through wired or wireless connection 112A. The wired connection can utilize standard Ethernet cables for robust and reliable data transfer, while the wireless connection can leverage Wi-Fi or other wireless communication protocols like Zigbee or Bluetooth, offering flexibility and case of installation. In FIG. 1, the IR cameras 110A and 110B are shown in position to capture at least portion of an area within an SRTU 100. A position of image capture may be a fixed position, or a movable, or mobile location 113.

[0087] Multiple sensors 111 may be installed within the SRTU 100, providing data on various operational parameters. These sensors can include, but are not limited to, temperature sensors, humidity sensors, airflow sensors, and pressure sensors. Temperature sensors monitor the heat levels of critical components such as the cooling component 103 and the economizer hood 104. Humidity sensors may measure the moisture levels within the unit, which is vital for maintaining optimal air quality and preventing condensation issues. Airflow sensors may track the movement and volume of air through the supply air 106 and return air 107 pathways, providing efficient distribution and circulation. Pressure sensors may monitor the system's internal pressure to prevent overloading and detect potential leaks.

[0088] The SRTU control system 112 may be a sophisticated unit that processes the data received from the IR cameras 110A-110B and sensors 111. The control system 112 may comprise a display for real-time monitoring, a Controller and / or AI engine for data analysis and predictive maintenance, and connectivity features for remote access. The control system 112 can be physically installed on the SRTU 100 or located at a distant site, such as a cloud server, allowing for scalable and flexible deployment.

[0089] The Controller and / or AI engine within the control system 112 may analyze the thermal images from the IR cameras 110A-110B and sensor data to identify patterns, detect anomalies, and predict potential failures. This predictive maintenance capability helps in reducing downtime and extending the lifespan of the SRTU components. The display may provide a user-friendly interface for monitoring real-time data, configuring system settings, and receiving alerts and notifications.

[0090] The SRTU control system 112 may also support machine learning algorithms that continuously improve the accuracy of predictions based on historical data. Additionally, the SRTU can be equipped with smart alerts that notify maintenance personnel of potential issues via mobile devices, providing timely interventions. The integration of multiple IR cameras and sensors with the SRTU control system 112 enables comprehensive monitoring, real-time data analysis, and predictive maintenance, providing the efficient and reliable operation of the SRTU 100.

[0091] In some embodiments of the invention, the SRTU control system 112 may be integrated with a Building Management System (BMS) to enhance the overall efficiency and performance of the HVAC system within a building where the SRTU 100 is installed. This integration allows the SRTU control system 112 to receive and utilize various data points from the BMS to dynamically control the operations of the SRTU 100, providing optimal climate control, energy efficiency, and occupant comfort.

[0092] The control system 112 within the SRTU 100 may comprise a sophisticated array of components constructed to handle advanced processing, storage, and communication tasks. At its core, the control system may include a high-performance processor capable of executing complex algorithms and real-time data analysis. The processor may be complemented by a memory, including both RAM for quick access and operations, and non-volatile storage for maintaining logs, historical data, and system configurations. Additionally, the control system 112 may include robust connectivity options, such as Ethernet, Wi-Fi, and possibly cellular modules, to ensure seamless communication with cloud servers, BMS, and remote user interfaces.

[0093] To support its AI-driven functions, the control system 112 may integrate a dedicated Controller and / or AI engine, either as a specialized chipset or through optimized software running on the main processor. The control system may also comprise various wired and / or wireless I / O interfaces to connect with external sensors, IR cameras, and other monitoring devices. These interfaces may also include USB, RS485, and digital / analog input-output ports.

[0094] For enhanced functionality, the control system 112 may be equipped with redundant power supplies and backup batteries to ensure uninterrupted operation during power outages. Additionally, incorporating advanced security features such as encryption, secure boot, and intrusion detection systems protects sensitive data and prevents unauthorized access.

[0095] To facilitate user interaction and system configuration, the control system 112 may include a user-friendly interface, potentially featuring a touchscreen display for on-site control and monitoring. This interface may allow technicians to perform diagnostics, configure settings, and view real-time system status. For remote management, the system may support mobile and web applications, enabling users to monitor and control the SRTU 100 from anywhere.

[0096] The SRTU control system 112 may be configured to receive a wide array of data from the BMS, including but not limited to:

[0097] Internal Temperatures: Real-time data on the internal temperatures of different zones or rooms within the building. This information allows the SRTU control system 112 to adjust the cooling or heating output based on the specific needs of each area, providing consistent and comfortable indoor temperatures.

[0098] Occupied Spaces: Information on which areas of the building are currently occupied. By knowing the occupancy status, the SRTU control system 112 can prioritize conditioning air in occupied spaces while reducing energy usage in unoccupied areas, leading to significant energy savings.

[0099] Occupancy Levels: Detailed data on the number of occupants in different parts of the building. This helps the SRTU control system 112 to adjust ventilation rates to maintain optimal indoor air quality, enhancing the comfort and well-being of building occupants. In some embodiments of the invention, the occupied spaces and occupancy level within the building may to determined based on CCTV cameras installed within the building spaces.

[0100] Air Quality Metrics: Data on indoor air quality parameters such as CO2 levels, humidity, and the presence of pollutants. The SRTU control system 112 can adjust ventilation and filtration settings to maintain healthy air quality standards.

[0101] Energy Usage: Information on the building's overall energy consumption and patterns. By integrating this data, the SRTU control system 112 can optimize its operations to align with energy-saving goals, reducing operational costs and environmental impact.

[0102] Weather Conditions: External weather data, including temperature, humidity, wind speed, and solar radiation. This may allow the SRTU control system 112 to anticipate changes in the building's thermal load and adjust its operations accordingly. In some embodiments of the invention, the SRTU control system 112 may be integrated with a cloud server for receiving real time weather updates, weather predictions so that the SRTU can be optimized accordingly.

[0103] Scheduled Events: Information on scheduled events or changes in building usage, such as meetings, conferences, or maintenance activities. This may help the SRTU control system 112 to prepare and adjust its settings proactively.

[0104] The integration of the SRTU control system 112 with the BMS may be facilitated through standard communication protocols such as BACnet, Modbus, or LonWorks, enabling seamless data exchange and interoperability between the systems. The SRTU control system 112 processes the received BMS data using its Controller and / or AI engine, which analyzes the information to make real-time adjustments to the SRTU 100's operations.

[0105] For instance, if the BMS indicates that a particular zone in the building is experiencing a higher occupancy level, the SRTU control system 112 can increase the ventilation rate and adjust the cooling output to ensure that the area remains comfortable and well-ventilated. Similarly, if the BMS detects that a zone is unoccupied, the SRTU control system 112 can reduce the cooling or heating to that area, thereby conserving energy.

[0106] The Controller and / or AI engine within the SRTU control system 112 may continuously learn from the BMS data and historical performance metrics to improve its predictive capabilities. This may include optimizing defrost cycles based on weather conditions, adjusting airflow patterns to prevent hot or cold spots, and scheduling maintenance activities based on usage patterns and predictive analytics.

[0107] Additionally, the integrated system 112 can provide building managers with comprehensive insights and reports through a user-friendly interface, accessible via the SRTU control system's display or via smart devices remotely through cloud-based platforms. These reports may include energy usage trends, indoor air quality metrics, system performance analytics, and maintenance recommendations, empowering facility managers to make informed decisions and optimize building operations.

[0108] Further, the SRTU 100 may be constructed with a focus on modularity, energy efficiency, and environmental protection, showcasing several distinct features and components. At the forefront of the SRTU's design is a casing top 101, a modular panel constructed from Polypropylene Random Copolymer (PPR) that is enhanced with a protective layer or coatings for durability. This top panel may serve as the primary shield against direct environmental exposure, such as solar radiation and precipitation, and may be potentially outfitted with nano coatings to mitigate wear and UV damage.

[0109] A casing end panel 102 works in conjunction with the casing top 101 to encapsulate the SRTU unit 100, providing a complete barrier that safeguards the internal components of the HVAC system. The panels are constructed for easy removal, facilitating access for maintenance and repair, which is part of the unit's modular design philosophy.

[0110] A cooling component 103 is the heart of the SRTU's climate control capability. It may utilize advanced, eco-friendly refrigerants and is engineered for maximum heat exchange efficiency. The cooling component 103 may integrate variable speed fans and compressors to adapt its performance based on real-time demand, significantly reducing energy consumption.

[0111] An economizer hood 104 may be included to take advantage of cool external air when available, reducing the need for mechanical cooling and thereby enhancing the unit's overall energy efficiency. This hood 104 may be equipped with sensors to automatically adjust the air intake based on the outside temperature and air quality.

[0112] A reduced support 105 implies a lightweight yet sturdy framework that underpins the SRTU 100. It is optimized to minimize the load on the building structure while maintaining the stability and integrity of the SRTU unit 100, even under adverse weather conditions.

[0113] The supply air 106 and return air 107 channels are integral to the air circulation process within the SRTU 100. The supply air 106 pathway directs the conditioned air into the building, while the return air 107 channel cycles the indoor air back to the SRTU for air reconditioning. These pathways are constructed to maximize airflow efficiency and may be lined with sound-dampening materials to minimize operational noise. A roof safety wall 108, although not a part of the SRTU 100 itself, is an essential aspect of the installation environment. The design of the SRTU 100 may integrate these components into a cohesive unit that prioritizes energy efficiency, ease of maintenance, and robustness against environmental stressors.

[0114] In some embodiments, the SRTU 100 may incorporate the sophisticated control system 112 capable of managing the defrost cycle for the evaporator coils. The control system 112 leverages real-time data from IR cameras 110A-110B, BMS system, and / or various sensors to cause the Controller and / or AI engine to determine the optimal times for initiating and ending the defrost cycle.

[0115] When the evaporator coils need to be defrosted, the control system 112 receives input from temperature sensors and IR cameras that monitor the coil's surface temperature and detect frost accumulation. Once the Controller and / or AI engine analyzes this data and identifies a significant build-up of frost, it initiates the defrost cycle. The defrost process may carefully be managed to ensure that the coil is efficiently cleared of frost without disrupting the overall operation of the SRTU 100.

[0116] During the defrost cycle, additional instrumentation such as humidity sensors and airflow meters may be employed to monitor the conditions within the SRTU 100. These sensors may provide the Controller and / or AI engine with comprehensive data, allowing it to fine-tune the defrosting process and ensure that it is both effective and energy efficient.

[0117] Determining when the defrost time should end is important to prevent unnecessary energy consumption and ensure the evaporator coils return to optimal operating conditions as quickly as possible. The Controller and / or AI engine continuously analyzes data from temperature sensors and IR cameras to assess the progress of the defrost cycle. Once the sensors and / or the thermal images from the IR cameras indicate that the evaporator coil's surface temperature has reached a predetermined threshold, indicating the removal of frost, the Controller and / or AI engine concludes the defrost cycle.

[0118] In cases where additional instrumentation may be required to enhance the accuracy and efficiency of the defrost cycle, the system can be equipped with advanced thermal imaging cameras, moisture sensors, and even vibration sensors to detect any mechanical strain on the coils. These additional instruments may provide a more detailed understanding of the defrost process, ensuring that the evaporator coils operate efficiently and reliably.

[0119] In some embodiments of the invention, the Smart Roof Top Unit (SRTU) may be equipped with a comprehensive suite of environmental sensors constructed to dynamically adjust the unit's operations based on real-time atmospheric conditions. These sensors are strategically placed to detect a variety of environmental factors, including temperature, humidity, solar radiation, wind speed, and air quality.

[0120] Temperature sensors may provide data on external and internal temperatures, allowing the SRTU to optimize its heating or cooling output to maintain the desired indoor climate efficiently. Humidity sensors monitor the moisture levels in the air, which not only influence thermal comfort but also impact the unit's cooling efficiency due to the effects of latent heat.

[0121] In some embodiments, solar radiation sensors may play an important role in the SRTU's operation by measuring the intensity of sunlight impacting the unit. This information may be used to adjust the cooling load and to control the operation of the integrated solar panels, if present, to maximize their energy generation potential while minimizing the heat gain from solar exposure.

[0122] Wind speed sensors may inform the SRTU when to bolster system protections against potential wind damage, and when it is advantageous to leverage natural ventilation as part of the economizer function as discussed above. Air quality sensors may detect pollutants and particulates, prompting the advanced filtration system of the HVAC to adjust its operation to ensure a healthy indoor environment.

[0123] The SRTU's control system, which interfaces with these sensors, may utilize the data to intelligently adapt various components of the unit. For example, in some embodiments, the control system can modulate fan speeds, open or close dampers, and regulate the economizer to improve air quality and energy efficiency. It may also initiate protective measures during adverse conditions, such as retracting or shielding components (which may be associated with the SRTU) that may be damaged by severe weather.

[0124] In some embodiments, a SRTU may also be integrated with a building management system (BMS), allowing it to operate in concert with other building systems and to respond to both occupant requirements and external environmental conditions. This level of integration and responsiveness not only enhances occupant comfort and safety but also promotes sustainable operation by reducing energy consumption and extending the service life of the HVAC system.

[0125] Referring now to FIG. 1A, it illustrates an exemplary SRTU system 100A, highlighting the intricate network of components and data flows that enable advanced monitoring, control, and optimization of the SRTU 100 (FIG. 1). The SRTU control system or control panel 112 may be the central hub that receives and processes various data inputs to manage the operation of the SRTU 100 efficiently.

[0126] The SRTU control system 112 may receive SRTU data over a wired or wireless connection 113A. The SRTU data may comprise thermal images from one or more infrared (IR) cameras 110 installed around the SRTU unit100. These IR cameras 110 may strategically be positioned to capture comprehensive thermal images of the SRTU 100, monitoring temperature variations across its surfaces. The thermal imaging data is useful for identifying hot spots, assessing the thermal performance of the unit, and detecting potential issues such as overheating components or inefficient heat distribution. The cameras 110 may utilize high-resolution sensors to provide detailed thermal maps, which are transmitted to the control system 112 for detailed analysis.

[0127] In addition to thermal imaging, the SRTU data may include sensor data from multiple sensors 111 installed on or within the SRTU 100. These sensors can be of various types, each providing helpful information about different operational parameters of the SRTU. For example, temperature sensors measure the heat levels of specific components, humidity sensors monitor the moisture levels within the unit, airflow sensors track the volume and movement of air through the SRTU 100, and pressure sensors assess the internal pressure to prevent overloading and detect air leaks. The continuous flow of data from these sensors may allow the control system 112 to maintain optimal conditions within the SRTU 100, providing efficient and reliable performance.

[0128] The SRTU control system 112 may also integrate a Building Management System (BMS) 115, receiving BMS data 116 over a wired or wireless connection. This integration may enable the SRTU 100 to be part of a broader network of building automation systems, enhancing its ability to respond to the dynamic needs of the building. The BMS data 116 may include internal temperatures of different building zones, occupancy status, air quality metrics, energy usage patterns, and scheduled events. By incorporating this data, the SRTU control system 112 can adjust its operations based on real-time conditions and historical trends, optimizing energy efficiency and occupant comfort.

[0129] For example, in some embodiments, if the BMS 115 indicates that certain areas of the building are currently unoccupied, the SRTU control system 112 can reduce the cooling or heating output to those areas, conserving energy. Conversely, if a zone is heavily occupied, the system can increase ventilation and adjust temperature settings and engagement of HVAC equipment 1C to ensure a comfortable environment. The integration with BMS 115 may also allow the SRTU to participate in demand response programs, where it can adjust its operation during peak energy usage periods to reduce overall building consumption.

[0130] In various embodiments, a communication network for the SRTU system 100A may include both wired and / or wireless connections. Wired connections, such as Ethernet cables, offer robust and reliable data transfer with minimal interference, ideal for important data paths between the SRTU 100 and the control system 112. Wireless connections, including Wi-Fi, Zigbee, or Bluetooth, may provide flexibility in sensor placement and ease of installation, enabling a scalable and adaptable monitoring network.

[0131] The SRTU control system 112 may also interface with cloud-based servers 114 for extended data storage, advanced analytics, and remote access. By uploading data to the cloud 114, the system 100A can leverage powerful computational resources for machine learning and predictive analytics, identifying long-term trends and improving the predictive maintenance capabilities of the SRTU 100. Remote access via cloud servers 114 may allow facility managers to monitor and control the SRTU 100 from anywhere, receiving alerts and updates through mobile devices or web interfaces.

[0132] In some embodiments of the invention, the SRTU control system 112 may interface with cloud-based servers 114 through various networks 113B, enabling enhanced data storage, advanced analytics, and remote monitoring capabilities. These networks can include a range of technologies to ensure reliable and secure communication. For example, the SRTU control system 112 may connect to cloud-based servers 114 via wired connections such as fiber optic or Ethernet cables, which offer high-speed and stable data transfer suitable for transmitting large volumes of sensor and thermal imaging data. Additionally, wireless networks such as Wi-Fi, 4G LTE, and 5G cellular networks provide flexibility and ease of installation, allowing the SRTU to be deployed in various locations without the constraints of physical wiring. Satellite communication networks can also be employed for remote or off-grid installations where traditional wired or cellular networks may not be available. By leveraging these diverse networking options, the SRTU control system 112 may ensure continuous and robust communication with cloud-based servers 114, facilitating real-time data processing, remote diagnostics, and the integration of machine learning algorithms to predict maintenance needs and optimize system performance. This connectivity allows facility managers to access the SRTU data from anywhere, using secure web interfaces or mobile applications, thereby enhancing the overall efficiency and responsiveness of the building's HVAC system.

[0133] Moreover, the SRTU control system 112 may also be equipped with a user-friendly display and interface, providing real-time visualization of thermal images, sensor data, and operational status. This interface can be installed locally on the SRTU 100 or accessed remotely, offering comprehensive insights into the system's performance. Users can configure settings, view historical data, and receive maintenance recommendations through this interface, providing proactive management of the SRTU 100.

[0134] Various other features may also be integrated into the system 100A that include advanced fault detection algorithms, adaptive learning for continuous improvement, and integration with renewable energy sources. Fault detection algorithms may use the thermal and / or sensor data to identify and diagnose issues before they lead to failures, minimizing downtime. Adaptive learning may allow the Controller and / or AI engine to refine its predictions and control strategies based on feedback and new data, continuously enhancing the system's performance. Integration with renewable energy sources, such as solar panels, can further reduce the building's carbon footprint by using green energy to power the SRTU 100.

[0135] In some embodiments of the invention, the BMS data 116 may comprise a comprehensive array of information that is helpful for optimizing the performance of the SRTU 100. This data can include camera feed, which provides real-time visual monitoring of different areas within the building, enabling the detection of occupancy patterns, security incidents, or maintenance needs. Occupancy data indicates the presence and number of individuals in various zones, allowing the SRTU 100 to adjust ventilation and temperature settings dynamically to maintain comfort and air quality. Load requirement data includes the specific heating, cooling, and ventilation demands of different areas within the building, which are essential for balancing the HVAC load and preventing energy wastage.

[0136] Additionally, space usage data may offer insights into how different parts of the building are being utilized, which can influence HVAC zoning strategies and prioritize high-traffic areas. Energy consumption data tracks the real-time and historical usage of electricity, helping in identifying inefficiencies and potential savings opportunities. Indoor air quality metrics such as CO2 levels, particulate matter, and humidity may also be part of the BMS data, ensuring that the air remains healthy and comfortable for occupants. Environmental conditions, both internal and external, such as temperature, humidity, and weather forecasts, may be integrated to allow the SRTU 100 to anticipate and adjust to changing conditions proactively.

[0137] Furthermore, scheduling data, including planned events and peak usage times, may enable the SRTU 100 to prepare for variations in load and occupancy. Security system statuses, fire alarm triggers, and emergency signals may also be monitored, ensuring the HVAC system can respond appropriately during critical situations. By incorporating this diverse and detailed BMS data 116, the SRTU control system 112 can perform real-time optimization, predictive maintenance, and energy-efficient operations, enhancing the overall performance and sustainability of the building's HVAC system.

[0138] In some embodiments of the invention, the Controller and / or AI engine integrated within the SRTU control system 112 may be constructed to analyze trends and historical data to learn and predict periods of increased or decreased heating or cooling requirements. This capability may allow the SRTU 100 to adjust its operations proactively, providing optimal climate control and energy efficiency.

[0139] The Controller and / or AI engine may collect and examine extensive data sets that may include time-specific variables such as the time of day, day of the week, and month or season of the year. By analyzing these data points, the Controller and / or AI engine can identify patterns and trends in the building's HVAC usage. For example, the Controller and / or AI engine may detect that there is a consistently higher cooling demand in the late afternoon during summer weekdays, likely due to increased sunlight exposure and occupancy levels. Similarly, it may observe that heating requirements peak in the early mornings during winter months when temperatures are lower, and occupants are arriving at the building.

[0140] Once these patterns are identified, the Controller and / or AI engine uses this information to adjust the SRTU's operations accordingly. For example, on a hot summer day, the Controller and / or AI engine can pre-cool the building before peak occupancy times to maintain a comfortable indoor environment while avoiding the energy spike that may occur if the cooling system were to ramp up suddenly during high demand periods. Conversely, during winter mornings, the Controller and / or AI engine can initiate the heating system slightly earlier to ensure the building reaches the desired temperature by the time occupants arrive.

[0141] Furthermore, the Controller and / or AI engine may continuously refine its predictive model by incorporating new data, allowing it to adapt to changes in building usage patterns or external weather conditions. It can also factor in external data sources such as weather forecasts to anticipate and respond to sudden changes in environmental conditions, ensuring that the SRTU 100 operates efficiently regardless of external variables.

[0142] The Controller and / or AI engine's ability to predict and adjust for seasonal variations is also significant. For example, during spring and autumn, when temperature fluctuations are more common, the AI can switch between heating and cooling modes as needed throughout the day, maintaining consistent comfort levels without manual intervention. This proactive approach not only enhances occupant comfort but also maximizes energy efficiency by avoiding overuse of the HVAC system.

[0143] Additionally, the Controller and / or AI engine can integrate with other building systems through the BMS, receiving real-time occupancy and usage data. This integration may allow the AI to make more informed decisions based on the current and expected building usage, further optimizing the SRTU's performance. For example, if a large meeting is scheduled in a conference room, the AI can ensure that the room is pre-cooled or pre-heated to the appropriate temperature, providing comfort for the occupants.

[0144] In some embodiments of the invention, the Controller and / or AI engine integrated within the SRTU control system 112 may take into account the geographic location of the building to optimize heating and cooling operations. By considering the location, the Controller and / or AI engine can analyze and learn the specific climatic patterns and seasonal variations that impact the building's heating and cooling requirements. For example, a building located in a region with hot summers and mild winters will have different HVAC demands compared to a building in a colder climate. The Controller and / or AI engine can adjust the SRTU's operations based on these learned patterns to ensure efficient energy use and occupant comfort throughout the year.

[0145] Furthermore, the Controller and / or AI engine can detect and predict occupancy patterns based on scheduled events and typical building usage. For example, in an office building, the AI can analyze historical data to identify peak times when people are likely to arrive, such as weekday mornings, and times when the building is less occupied, such as evenings and weekends. By understanding these patterns, the Controller and / or AI engine can proactively adjust the SRTU's settings to pre-cool or pre-heat the building before occupants arrive, providing a comfortable environment from the moment they enter.

[0146] The Controller and / or AI engine can also integrate with the building's scheduling systems to predict occupancy based on planned meetings, conferences, or other events. For example, if a large meeting is scheduled in a conference room at 10 AM, the AI can ensure that the room is at the optimal temperature and ventilation level by the time the meeting starts. Conversely, during periods of low occupancy, such as lunchtime or after office hours, the AI can reduce heating or cooling to save energy while maintaining basic comfort levels.

[0147] By leveraging occupancy sensors and data from the BMS 115, the Controller and / or AI engine can continuously refine its predictions and adjustments. It can detect real-time changes in occupancy and respond accordingly. For example, if a large number of people unexpectedly gather in a particular area, the AI can increase ventilation and cooling to accommodate the additional heat load generated by the occupants.

[0148] Additionally, the Controller and / or AI engine considers external factors such as weather forecasts and real-time climate data. By predicting temperature fluctuations, humidity levels, and other environmental conditions, the AI can adjust the SRTU's operations to maintain indoor comfort while minimizing energy consumption. For example, on a day when a heatwave is forecasted, the AI can pre-emptively increase cooling capacity to ensure the building remains comfortable despite the extreme external temperatures.

[0149] In some embodiments, the Controller and / or AI engine within the SRTU control system 112 may utilize machine learning to optimize the defrosting process. By analyzing historical data, BMS data, SRTU data and real-time environmental conditions, the Controller and / or AI engine can predict the optimal times and conditions for initiating defrost cycles for the SRTU 100. It learns patterns related to frost accumulation, such as specific weather conditions or operational behaviors that lead to increased frost. Based on this knowledge, the AI can dynamically adjust the defrosting frequency and intensity, providing efficient frost removal without energy expenditure. This adaptive defrosting strategy enhances the overall performance and energy efficiency of the SRTU, preventing frost-related issues and maintaining consistent heating and cooling capabilities.

[0150] In some embodiments, the Controller and / or AI engine that powers the SRTU control system 112 may reside on a cloud-based server 114 itself. By leveraging the computational power and scalability of cloud infrastructure, the Controller and / or AI engine can process vast amounts of data collected from the SRTU 100, including thermal images, sensor data, and BMS inputs. Such a centralized approach may allow for more sophisticated analytics and machine learning models that continuously improve over time. The server-based Controller and / or AI engine can also integrate data from multiple SRTUs across different locations, providing a broader perspective and more robust predictive capabilities. Remote access to the Controller and / or AI engine via the cloud enables real-time monitoring, diagnostics, and updates, ensuring that the SRTU 100 operates at peak efficiency and reliability regardless of its physical location.

[0151] Referring now to FIG. 1B, an exemplary configuration of overlapping fields of view 120 for IR cameras 110A and 110B are illustrated. The cameras 110A and 110B are installed to capture comprehensive thermal images of the SRTU 100 from various directions and angles. These IR cameras are exemplary, and the system can accommodate one or several IR cameras to ensure thorough thermal monitoring of the SRTU 100.

[0152] The IR cameras 110A and 110B may capture different fields of view, each providing corresponding thermal perspectives of the SRTU 100. The overlapping fields of view 120 ensure that all important areas of the SRTU 100 are monitored, minimizing blind spots and providing a complete thermal profile. The captured thermal images are then analyzed by the Controller and / or AI engine, which may process these images to generate detailed heat maps or thermograms.

[0153] The Controller and / or AI engine may use the thermograms to identify specific points, such as 120A and 120B, where higher temperatures are detected (near the exhaust air 109). These points of varying temperature may indicate the operational conditions of the components inside the SRTU 100. For example, a consistently high temperature at point 120A may indicate an overheating compressor, while an elevated temperature at point 120B may signal a failing fan motor. By analyzing these thermal patterns, the Controller and / or AI engine can determine which components require attention or adjustment.

[0154] Additionally, the Controller and / or AI engine can correlate surface temperature data with the internal working conditions of the corresponding components within the SRTU 100. For example, if the exterior surface of the SRTU 100 shows unusual thermal hotspots, it may indicate internal components struggling to dissipate heat effectively, suggesting potential inefficiencies or impending failures. This correlation may allow the Controller and / or AI engine to make informed decisions about controlling the SRTU 100 to optimize its performance.

[0155] Moreover, the Controller and / or AI engine can proactively adjust the SRTU operations based on real-time thermal data. For example, if the thermograms indicate that a particular section of the SRTU 100 is consistently hotter than the rest, the AI can increase airflow to that section, initiate a targeted cooling cycle, or schedule maintenance checks to prevent component failure. This proactive approach may ensure better and more efficient cooling or heating as required, enhancing the overall reliability and lifespan of the SRTU 100.

[0156] The system may also integrate additional features, such as predictive maintenance alerts. By continuously learning from the thermal data, the Controller and / or AI engine can predict when components are likely to fail based on their thermal behavior patterns. This may allow for timely maintenance interventions, reducing unplanned downtime and operational disruptions.

[0157] Furthermore, the Controller and / or AI engine can utilize machine learning algorithms to refine its analysis over time. As it processes more thermal data, it becomes better at recognizing patterns and anomalies, improving its predictive accuracy. This adaptive capability may ensure that the SRTU 100 operates at peak efficiency, even as environmental conditions and usage patterns change.

[0158] In some embodiments, the Controller and / or AI engine within the SRTU control system 112 may analyze the thermograms of the exterior surface of the SRTU 100, where specific sections, points, and / or zones on the exterior surface may correlate with the internal components housed within the SRTU 100. The thermographic analysis may allow the Controller and / or AI engine to infer the operational status and condition of these internal components based on their thermal signatures (For example, 120A-120B) on the exterior surface. Components within the SRTU 100 may include, but are not limited to, compressors, evaporator coils, condenser coils, heating coils, cooling coils, filters, fan motors, electrical circuits, and heat exchangers.

[0159] For example, if the thermogram indicates an unusually high temperature in a zone corresponding to the compressor, this may signify that the compressor is operating under excessive load or is potentially failing. Similarly, thermal anomalies in areas correlating with the evaporator coils may suggest issues such as frost buildup, which may impede airflow and reduce efficiency. By identifying these thermal patterns, the Controller and / or AI engine can pinpoint which components require attention and perform automated adjustments to maintain optimal performance.

[0160] This thermal analysis may particularly be useful for managing defrost cycles. For example, if the thermogram shows consistent cold spots on the exterior surface where the evaporator coils are located inside, the Controller and / or AI engine can infer that frost is accumulating on these coils. Based on this data, the AI can initiate a defrost cycle to melt the frost and restore efficient heat exchange. By optimizing the timing and duration of defrost cycles based on real-time thermal data, the Controller and / or AI engine may ensure that the SRTU 100 operates efficiently, preventing excessive energy consumption and minimizing wear on components.

[0161] Furthermore, the Controller and / or AI engine's ability to correlate exterior thermal patterns with internal component conditions may allow for more targeted and effective maintenance strategies. It can prioritize maintenance tasks based on the severity and urgency of detected issues, ensuring that the most critical problems are addressed promptly. This proactive maintenance approach reduces the risk of unexpected failures and extends the lifespan of the SRTU components.

[0162] In some embodiments, when the Controller and / or AI engine resides on the cloud server 114, it can leverage historical data and trends from a multitude of sources, including numerous SRTUs, various thermograms, and extensive operational data. By aggregating and analyzing data from multiple SRTU units deployed across different locations and environments, the cloud-based Controller and / or AI engine can learn from a vast amount of diverse information. This comprehensive data set allows the AI to identify broader patterns and trends that may not be apparent from a single SRTU.

[0163] For example, the Controller and / or AI engine can compare thermograms from several SRTUs to determine common thermal signatures associated with specific component failures or inefficiencies. It can also analyze historical operational data to understand the effects of different environmental conditions, usage patterns, and maintenance practices on the performance of the SRTUs. By utilizing machine learning algorithms, the Controller and / or AI engine continuously refines its predictive models, enhancing its ability to forecast potential issues and optimize the performance of each SRTU.

[0164] This cloud-based approach may enable the Controller and / or AI engine to provide more accurate and reliable predictions, as it benefits from a wider range of data inputs. It can generate insights and recommendations that are informed by collective knowledge, leading to more effective and proactive maintenance strategies. Additionally, the cloud server's computational power allows for complex data processing and analysis, ensuring that the Controller and / or AI engine can handle the large volumes of data generated by multiple SRTUs efficiently.

[0165] Referring now to FIG. 1C, it illustrates an exemplary process where multiple thermal images (121A, 121B, 121C) may be combined to form a comprehensive single thermal image 121 for advanced AI analysis. Such an integration of thermal data from various perspectives may enhance the accuracy and depth of the thermal profile, allowing the Controller and / or AI engine to make more informed decisions regarding the operational state of the SRTU 100.

[0166] In such embodiments, the individual thermal images 121A, 121B, and 121C may be captured by IR cameras from different angles or positions around the SRTU 100. Each image may provide a unique view of the thermal characteristics of the unit, capturing specific details and temperature variations that may not be visible from a single vantage point. These images may then be combined into a single, unified thermal image 121, which offers a complete and detailed thermal map of the SRTU's exterior surface.

[0167] The Controller and / or AI engine may analyze this combined thermal image 121 to identify critical points and / or zones, such as 122A, 122B, and 122C, where significant temperature variations are detected. These points may indicate potential issues or areas that require attention. For example, a hotspot at 122A may suggest an overheating component, while a cold spot at 122B may indicate frost buildup. The Controller and / or AI engine can use this detailed thermal information to optimize the SRTU's performance, adjusting cooling or heating operations to maintain efficiency and prevent component failure.

[0168] Furthermore, a single IR camera can capture a continuous video stream for AI analysis. This continuous stream may provide real-time thermal monitoring, enabling the AI to detect and respond to dynamic changes in temperature more effectively. By capturing multiple frames over time, the IR camera can create a time-lapse thermal profile, which the AI can analyze to understand trends and patterns in the SRTU's thermal behavior. This real-time data is invaluable for proactive maintenance and operational adjustments.

[0169] For example, the Controller and / or AI engine can use the continuous video stream to monitor the defrost cycles of the SRTU 100. By analyzing the thermal changes during these cycles, the AI can determine the optimal timing and duration for defrost operations, ensuring that frost is effectively removed without wasting energy. Additionally, the AI can identify anomalies such as unexpected temperature spikes or drops, which may indicate emerging issues that need to be addressed promptly.

[0170] Moreover, the Controller and / or AI engine's ability to combine multiple images or frames may allow for more sophisticated analysis techniques. For example, it can employ image stitching algorithms to merge the thermal images seamlessly, creating a high-resolution composite image that retains the details and nuances of the individual frames. This composite image can then be processed using advanced machine learning models to detect subtle patterns and anomalies that may not be apparent in a single frame.

[0171] Referring now to FIG. 2, in an exemplary embodiment, the SRTU 100 is situated in its operational environment atop a building structure. The SRTU 100 may be encased within a protective housing, labeled as SRTU Casing 201, which may be mainly constructed from PPR with a protective outer layer that may consist of either a metallic or non-metallic substance as discussed in some embodiments of the invention. The casing 201 is constructed to shield the internal components of the SRTU 100 from various environmental elements.

[0172] The Solar Stress 203, depicted as a wavy arrow pointing towards the SRTU, signifies the impact of solar radiation on the unit 100. This aspect of the design acknowledges the need for the SRTU 100 to withstand prolonged exposure to sunlight, which can contribute to thermal stress and the potential degradation of material over time. Additionally, the unit 100 is also shown in the context of Snow and Rain 204 to illustrate the SRTU's 100 exposure to various forms of precipitation, necessitating a robust and weather-resistant design to ensure consistent operation through diverse, and potentially harsh, weather conditions. The FIG. 2 serves to underscore the SRTU's resilience and the effectiveness of its design in protecting against environmental stressors, aligning with the invention's objective to provide a durable, efficient, and environmentally conscious HVAC solution.

[0173] Solar stress 203 can cause significant temperature increases on the surface of the SRTU casing 201, potentially affecting the internal components' performance and efficiency. The invention may employ multiple infrared (IR) cameras installed around the SRTU 100 to monitor these temperature variations caused by solar exposure. The AI system may use this data to optimize the cooling load and other operational parameters to mitigate the impact of solar stress, providing efficient and reliable operation. The multiple IR cameras installed around the SRTU 100 may continuously monitor the surface for areas with excessive frost or moisture accumulation. The real-time thermal data enables the AI system to dynamically adjust defrost cycles and other control mechanisms to prevent ice buildup and ensure effective drainage, thus maintaining optimal performance and preventing weather-related damage.

[0174] In accordance with various embodiments of the present invention, the SRTU 100 may innovatively be constructed to offer enhanced protection and durability for HVAC systems. At the core of this invention is the use of Polypropylene Random Copolymer (PPR) as the primary material for the construction of the SRTU 100. PPR is selected for its notable characteristics, including its lightweight nature, structural strength, and resistance to environmental factors such as chemical corrosion and temperature variations. These properties make PPR an ideal choice for rooftop applications where exposure to diverse weather conditions is a constant challenge.

[0175] To further reinforce the SRTU 100 and safeguard its internal components, the PPR layer is coated with a protective layer (metallic or non-metallic layer), such as galvanized steel. This metallic coating or layer serves multiple important functions. Firstly, it acts as a robust barrier against environmental elements like rain, snow, and UV radiation, preventing direct contact with the PPR layer and thus averting potential material degradation over time. The galvanized steel coating is particularly effective in shielding the unit 100 from moisture-induced damage and corrosion, a common issue in metallic components exposed to the outdoors.

[0176] Secondly, the protective layer enhances the overall structural integrity of the SRTU 100. Galvanized steel, known for its strength and durability, provides additional rigidity to the unit 100, ensuring it remains stable and secure in various climatic conditions, including high winds or heavy snow loads. This added strength is important in maintaining the unit's shape and functionality over its lifespan.

[0177] Thirdly, the combination of PPR with a galvanized steel coating contributes to the thermal efficiency of the SRTU 100. The metallic layer reflects a significant portion of solar radiation, thereby reducing the heat absorbed by the unit 100. This reflection helps in maintaining a more stable internal temperature, which is beneficial for the optimal performance of the HVAC system housed within the SRTU unit 100.

[0178] In addition, the smooth surface of the galvanized steel coating facilitates easier maintenance and cleaning of the SRTU 100. With this case of maintenance, the unit can be kept in optimal condition, further extending its operational life and reliability. Overall, the use of PPR as the main structural layer, combined with an outer protective layer or coating, provides a superior solution for rooftop HVAC units. With this combination, the components within the SRTU 100 are well-protected from environmental elements, leading to a more durable, efficient, and reliable HVAC system.

[0179] Referring now to FIG. 2A, an exemplary view of a building HVAC system showcasing the interrelation between various components, including the SRTU 100. The SRTU 100 is depicted alongside other important elements of the HVAC system, namely the Air Handler Unit (AHU) 200 and the Air-Cooled Chiller 202. These components are typically found within the mechanical services area of a building's rooftop or a designated utility space. The Air Handler Unit 200 is responsible for the circulation and regulation of air throughout the building's interior spaces. It is typically connected to ductwork that distributes conditioned air through various zones and returns it to the AHU 200. The Air-Cooled Chiller 202 functions to remove heat from the indoor air through the refrigeration cycle, contributing to the cooling requirements of the HVAC system.

[0180] The SRTU 100, as part of this assembly, is strategically positioned to facilitate its role in the overall climate control process. Its construction from PPR with a protective outer layer is essential for withstanding the external rooftop environment, where it works in tandem with the AHU 200 and chiller 202 to provide efficient heating, cooling, and ventilation. The integration of these components into a cohesive system demonstrates the importance of each unit's design and placement in achieving optimal HVAC performance. The FIG. 2A illustrates the SRTU's 100 compatibility and functionality within a larger HVAC network, highlighting its significance in a comprehensive climate control solution for modern buildings.

[0181] The SRTU 100 may be constructed to handle localized cooling and heating needs, leveraging advanced infrared thermal imaging and AI integration to optimize performance, ensure real-time monitoring, and provide predictive maintenance. The SRTU 100 may monitor its own components and the immediate environment, adjusting its operations dynamically based on the data collected to maintain optimal indoor conditions.

[0182] The AHU 200 may be responsible for distributing conditioned air throughout the various floors. The AHU 200 is connected to the air distribution ducts that run vertically through the building, ensuring that each floor receives an adequate supply of conditioned air. The AHU 200 works in conjunction with the SRTU 100, receiving air that has been pre-cooled or pre-heated by the SRTU and further conditioning it before distributing it to the building's interior spaces.

[0183] The chiller 202 may serve as the primary cooling source for the entire HVAC system. It removes heat from the building's air and transfers it to the outside environment. The chiller 201 may operate by circulating a refrigerant through a series of coils, which absorb heat from the air passing over them. The cooled air is then directed to the AHU 200 for distribution. The integration of the chiller 202 with the AHU 200 and the SRTU 100 may ensure a cohesive and efficient cooling system.

[0184] Referring now to FIG. 3, an exemplary representation of the SRTU 300, with a focus on its modular design and component architecture. The modular SRTU 300 may be under the supervision of multiple infrared (IR) cameras constructed to capture comprehensive thermal images from various directions and angles to monitor and optimize the performance of the SRTU 300. The SRTU 300 is shown featuring multiple modular components, referred to as SRTU Casing Side Panels 303, which are integral to the present invention's innovative approach to HVAC system construction. These panels are part of the unit's 300 protective casing, with the SRTU Casing Top 301 and SRTU Casing End Panel 302, delineating the complete enclosure of the unit 300.

[0185] One or more external IR cameras 310 may strategically be installed on the building structure where the SRTU 300 is located. These cameras may be positioned to capture thermal images of the SRTU 300 from multiple directions and angles, providing a holistic view of the unit's surface temperature distribution. The external cameras 310 can monitor the entire surface of the SRTU 300, detecting any hotspots, cold spots, or unusual temperature variations that may indicate potential issues or inefficiencies.

[0186] Additionally, a plurality of internal IR cameras 310A and 310B may be installed within the SRTU 300 itself. These internal cameras may strategically be placed to capture thermal images of the components housed inside the SRTU 300, such as but not limited to, the heating coil, cooling coil, evaporator coils, filters, dampers, centrifugal EC fan, and other important elements. By capturing thermal images of the internal components, the system can monitor their operating temperatures in real-time, ensuring that each component is functioning within optimal temperature ranges.

[0187] The captured thermal images from both external and internal IR cameras may be transmitted to a control system comprising a processor, a memory storing instructions executable by the processor, and an artificial intelligence (AI) engine. The Controller and / or AI engine may process these thermal images to convert them into digital value patterns that represent the temperature distributions across the SRTU 300 and its components.

[0188] Using advanced algorithms, the Controller and / or AI engine may analyze these digital value patterns or the heat signatures to identify zones and / or spots that may indicate operational inefficiencies, equipment failures, or potential maintenance needs. For example, if a particular component exhibits consistently high temperatures, the Controller and / or AI engine may flag this as an anomaly, suggesting that the component is under excessive stress or nearing failure.

[0189] Based on the analysis of the thermal images, the Controller and / or AI engine can control the SRTU 300 by adjusting operational parameters such as fan speed, damper positions, and heating or cooling cycles to optimize performance. For example, if the Controller and / or AI engine detects that certain areas or components of the SRTU 300 are overheating, it can increase airflow to those areas to dissipate heat more effectively.

[0190] Furthermore, the Controller and / or AI engine can also predict future maintenance needs and operational adjustments by continuously learning from the thermal data and historical performance trends. In addition to real-time control and predictive maintenance, the Controller and / or AI engine can also provide automated design suggestions to improve the performance of the SRTU 300. By analyzing thermal patterns and performance data, the Controller and / or AI engine can recommend modifications to the design of certain components or the overall structure of the SRTU 300. These suggestions may include replacing a component with a more efficient one, redesigning airflow pathways, or adjusting the placement of internal components for better thermal management.

[0191] The Controller and / or AI engine may also integrate data from the BMS, considering factors such as building occupancy, usage patterns, and geographic location. This integration may allow the Controller and / or AI engine to tailor its recommendations and control strategies to the specific needs and conditions of the building, ensuring that the SRTU 300 operates optimally within its unique environment.

[0192] The modular components 303 are constructed to facilitate easy assembly and disassembly, which is essential for efficient transportation, installation, and repair. The modularity allows for the SRTU 300 to be disassembled into manageable sections, making it easier to transport the unit 300 to the installation site, particularly when space constraints or access limitations are present. This design feature significantly reduces logistical challenges and costs associated with moving large, unwieldy equipment. Once on-site, the modular nature of the SRTU 300 simplifies the installation process as well. Technicians can quickly assemble the unit 300 piece by piece, which is especially advantageous in rooftop applications where time and space are at a premium. The ability to add or remove modular components also provides flexibility in system configuration and the potential for future expansion or reconfiguration as building needs evolve.

[0193] Furthermore, the modular design enhances the serviceability of the SRTU 300. Maintenance personnel can easily access internal components by removing specific panels, facilitating timely repairs and routine service checks without the need for complete system disassembly. This not only minimizes downtime but also extends the life of the unit by ensuring that all components are readily accessible for maintenance. The modular panels 301-303 of the SRTU 300 allow for a more streamlined and cost-effective lifecycle of the unit 300, from transportation and installation to operation and maintenance, reflecting the adaptability and user-friendly design.

[0194] In some embodiments, the Controller and / or AI engine integrated to the SRTU 300 ay also suggest automated designs for the modular components 303. By analyzing the thermal images captured by the IR cameras, the Controller and / or AI engine identifies thermal patterns and inefficiencies that can be addressed through design modifications. The Controller and / or AI engine may leverage advanced machine learning algorithms and historical performance data to propose optimal configurations for the modular components 303. These suggestions may include adjustments to the size, shape, and material composition of the components 303 to enhance thermal management and airflow efficiency. Additionally, the Controller and / or AI engine can recommend the integration of new materials or technologies that improve the overall performance and durability of the SRTU 300. By continuously learning from operational data and adapting to changing conditions, the Controller and / or AI engine may ensure that the modular components 303 are constructed to meet the specific needs of the HVAC system, thereby maximizing energy efficiency and operational effectiveness.

[0195] In some embodiments of the invention, the SRTU 300 is distinguished by its modular design, featuring an array of interlocking panels, including the SRTU Casing Top 301, the SRTU Casing End Panel 302, and multiple SRTU Casing Side Panels 303. Each panel is constructed as an individual module that can be swiftly assembled or disassembled, providing unparalleled adaptability and ease of maintenance.

[0196] Unique features of this modular design may include specialized sealing mechanisms between panels that may enhance the unit's weather resistance, ensuring that each join is both secure and impervious to environmental elements. This sealing technique may not only protect the interior components of the SRTU 300 but also simplify the process of replacing or repairing individual module panels 301-303 without disturbing the integrity of the entire unit 300.

[0197] Another innovative aspect of the SRTU's modular panels may be their construction with integrated insulation materials that enhance the unit's energy efficiency. These materials may be embedded within the panels themselves, thereby maintaining the SRTU's comparatively lightweight characteristic while optimizing thermal efficiency.

[0198] The modular panels may also be constructed with acoustic dampening properties to reduce operational noise, a feature that is increasingly important in urban or residential areas. Furthermore, the exterior surfaces of the panels may be treated with a reflective coating to minimize solar heat gain, further contributing to the unit's overall energy efficiency.

[0199] For added functionality, certain modular panels within the SRTU may be equipped with quick-release mechanisms that allow for rapid access to the interior of the unit for maintenance or emergency repairs. These quick-release mechanisms are constructed to be operated without specialized tools, emphasizing case of use and efficiency.

[0200] Referring now to FIG. 4, an exemplary SRTU control system 112 providing automated design suggestions for the SRTU (100 or 300) to improve its performance, is illustrated. The SRTU control system 112 is equipped with a Controller and / or AI engine that analyzes thermal images captured by one or both the internal IR cameras and external IR cameras to optimize the design and operation of the SRTU. The thermal images provide real-time data on temperature distributions across the SRTU's surface and internal components, enabling the Controller and / or AI engine to make informed design recommendations.

[0201] As shown in FIG. 4, the SRTU control system 112 may provide a comprehensive suggested design 400 for an SRTU. This suggested design 400 may leverage detailed analysis of one or more of: thermal images captured by both one or both the internal IR cameras and external IR cameras, the BMS data, SRTU operational data, sensor data, environmental data, and the geographic location of the building. The Controller and / or AI engine may process this comprehensive data and propose design modifications to enhance the overall performance and efficiency of the SRTU.

[0202] The external IR cameras, strategically installed on the building structure, capture thermal images of the SRTU from various angles and / or directions. These images provide a holistic view of the surface temperature distribution, allowing the Controller and / or AI engine to detect hotspots, cold spots, and other temperature anomalies. The internal IR cameras, positioned within the SRTU, focus on internal components such as the heating coil, cooling coil, evaporator coil, filters, dampers, EC fans, and other important elements. These cameras monitor the real-time operational temperatures of these components, ensuring they are functioning within optimal ranges (as discussed in FIG. 3 above).

[0203] The Controller and / or AI engine may process the thermal images to generate digital value patterns representing the temperature distributions across the SRTU's surface and internal components. By analyzing these patterns, the Controller and / or AI engine can identify areas where heat or frost buildup occurs, components that are overheating, and zones with insufficient cooling or airflow. Based on this analysis, the Controller and / or AI engine may provide design suggestions to address these issues.

[0204] For example, Controller and / or AI engine may recommend a tubular SRTU 400, with no flat surfaces. This design may enhance aerodynamic properties, reduce air resistance, and improve airflow efficiency. The tubular shape may help in minimizing turbulence and pressure drops, leading to more efficient operation of the HVAC system. The suggested tubular SRTU 400 may be based on a detailed analysis of thermal images and operational data to enhance the overall performance and efficiency of the SRTU.

[0205] The tubular design of the SRTU 400 may offer several key advantages over traditional rectangular or box-shaped units. The tubular form may minimize air resistance and turbulence, which are common issues with flat surfaces. By having a streamlined, rounded shape, the SRTU 400 may facilitate smoother airflow both around and within the unit. This reduction in air resistance may lead to more efficient operation of the HVAC components, as the airflow is less obstructed, and the pressure drops are minimized.

[0206] The tubular SRTU 400 placed on the roof 401 of a building comprises a smooth, tubular exterior with no flat surfaces. The tubular design may particularly be beneficial in maintaining high hygiene standards, as it eliminates corners and crevices where dirt and contaminants can accumulate. The smooth surfaces also facilitate easy cleaning and maintenance, ensuring that the unit 400 can be kept in a pristine condition, which is important for environments where cleanliness is paramount, such as hospitals, laboratories, and food processing facilities.

[0207] In terms of thermal management, the tubular design may help distribute thermal loads more evenly across the unit's surface. Traditional flat surfaces can create hotspots where heat accumulates, leading to inefficiencies and potential component overheating. The curved surfaces of the tubular SRTU 400 allow for better heat dissipation and more uniform temperature distribution. The Controller and / or AI engine, through thermal imaging analysis, can identify areas where heat tends to build up and suggest this tubular form to mitigate such issues.

[0208] Additionally, the tubular shape may also enhance the structural integrity and durability of the SRTU 400. The rounded design can better withstand external environmental stressors such as wind, rain, and debris, compared to flat surfaces that can create points of weakness or catch wind, leading to structural damage over time. This makes the tubular SRTU 400 more robust and long-lasting, particularly in harsh weather conditions.

[0209] The Controller and / or AI engine's recommendations may also include optimizing the internal layout of the SRTU 400. By placing components like the heating coil, cooling coil, dampers, and fans along the inner circumference of the tubular structure, the Controller and / or AI engine enables these components to benefit from the enhanced airflow and temperature regulation. Furthermore, the Controller and / or AI engine may take into account the ease of maintenance and accessibility in its design recommendations. The tubular SRTU 400 can be constructed with modular sections that allow easy access to internal components for maintenance, repairs, or upgrades.

[0210] Furthermore, the Controller and / or AI engine may also consider, in addition to thermal images, the BMS data, SRTU operational data, sensor data, environmental data, and the geographic location of the building to generate additional automated suggestions, including but not limited to:

[0211] Optimized Airflow Pathways: The Controller and / or AI engine may suggest specific pathways for supply air and return air to optimize airflow. The supply air is delivered through a duct pipe 402, while the return air is channeled through a duct pipe 403. The Controller and / or AI engine may recommend the appropriate diameters for these duct pipes (e.g., diameter 402A for supply air and diameter 403A for return air) based on the AI analysis of airflow patterns and pressure balance. Additionally, the Controller and / or AI engine may propose the use of advanced materials for the duct pipes (402-403), such as lightweight, high-durability composites or insulated materials to minimize thermal losses and reduce energy consumption. The Controller and / or AI engine may also recommend specific duct designs, such as smooth interior surfaces to reduce friction and enhance airflow efficiency, or flexible ducting to accommodate dynamic building layouts and reduce installation complexity.

[0212] Strategic Component Placement: The Controller and / or AI engine may provide recommendations for the placement of internal components 404 housed within the SRTU 400. By analyzing one of more of the comprehensive data (thermal images, the BMS data, SRTU operational data, sensor data, environmental data, and the geographic location of the building), the AI can identify areas where components may be overheating or not receiving adequate cooling. For example, if the cooling coil exhibits higher temperatures in certain areas, the Controller and / or AI engine may suggest repositioning it to improve airflow and enhance cooling efficiency. Similarly, the AI may recommend relocating the heating coil or the centrifugal EC fan to optimize their performance based on thermal data or the comprehensive data.

[0213] Enhanced Insulation and Material Selection: The Controller and / or AI engine may suggest modifications to the insulation and materials used in the SRTU 400. For example, it may recommend additional insulation in areas where heat loss is detected or suggest materials with better thermal conductivity for components that require efficient heat dissipation. These recommendations may help in maintaining optimal internal temperatures and improving energy efficiency.

[0214] Adaptive Control AI gorithms: The Controller and / or AI engine not only provides design suggestions but may also recommend adaptive control algorithms to dynamically adjust the operation of the SRTU 400. These algorithms may take into account real-time data from the IR cameras and other data, adjusting fan speeds, damper positions, and heating / cooling cycles to maintain and / or improve optimal conditions. In some embodiments, the Controller and / or AI engine may update its machine learning algorithm to dynamically adjust the operation of the SRTU 400.

[0215] Predictive Maintenance and Future Upgrades: The Controller and / or AI engine's analysis may extend to predicting future maintenance needs and suggesting design upgrades. By continuously monitoring thermal patterns and performance data, the Controller and / or AI engine can identify components that may require maintenance or replacement soon. It can also recommend design upgrades to accommodate future HVAC demands, ensuring the SRTU 400 remains efficient and reliable over time.

[0216] In some embodiments, the Controller and / or AI engine may consider data from the BMS, which may include occupancy patterns, usage schedules, and geographic location. By integrating this data, the AI can tailor its design recommendations to the specific needs of the building. For example, in areas with high occupancy during certain hours, the AI may suggest enhancing cooling capacity or optimizing airflow to those zones.

[0217] In some embodiments of the present invention, the Controller and / or AI engine integrated within the SRTU control system may provide automated design suggestions to enhance the overall efficiency and performance of the SRTU. For example, based on the analysis of airflow patterns and thermal distributions, the Controller and / or AI engine may suggest redesigning the internal layout of the SRTU to optimize the placement of key components such as the heating coil, cooling coil, and centrifugal electronically commutated (EC) fan. It may recommend repositioning these components to areas with better airflow or less thermal stress, thereby enhancing their performance and lifespan.

[0218] Referring now to FIG. 4A, an exemplary Smart Rooftop Unit (SRTU) 400A is shown, which includes a variety of internal components, strategically designed and positioned to optimize the performance and efficiency of the HVAC system. The SRTU control system 112, equipped with an AI engine provides automated design suggestions for the arrangement and operation of the internal components. The system leverages real-time data, historical performance metrics, and advanced analytics to continually refine the design and functionality of the SRTU 400A.

[0219] The supply air 406 and return air 407 channels are integral to the SRTU's operation, facilitating the movement of air through the system to be heated or cooled as required. The control system 112 may suggest specific pathways and diameters for these ducts to maximize airflow efficiency and minimize pressure loss. For example, the diameter of the supply air duct 406 may be adjusted to allow optimal delivery of conditioned air to the occupied spaces, while the diameter of the return air duct 407 may be optimized to facilitate efficient air recirculation.

[0220] The outer surface 414 of the SRTU 400A may be designed from PPR to be robust and weather-resistant, protecting the internal components from environmental factors. The AI engine may recommend using specific materials or coatings for the surface 414, such as UV-resistant polymers or corrosion-resistant metals, depending on the geographic location and environmental conditions of the installation site. The control system 112 may provide suggestions on the optimal placement and orientation of the SRTU 400A on a roof 417 to enhance airflow dynamics and ease of maintenance.

[0221] The initial filter 416 is the first line of defense against airborne contaminants, capturing large particles and debris before they enter the SRTU. The control system 112 may suggest the type of filter media and the replacement schedule to maintain optimal air quality and system performance.

[0222] The heating and cooling coils 405 are crucial for temperature regulation within the SRTU 400A. The AI engine can analyze thermal images and operational data to suggest improvements in the coil design, such as enhancing the fin density or adjusting the coil size, to improve heat exchange efficiency and reduce energy consumption.

[0223] Additional filters 410 may maintain air quality by removing particulates and contaminants from the air stream. The AI engine can recommend the type and configuration of these filters based on the specific needs of the building and the external environment. For example, in areas with high pollution levels, the system 112 may suggest using high-efficiency particulate air (HEPA) filters for superior air quality.

[0224] The mixing damper 412 provides for blending return air with fresh outdoor air to maintain indoor air quality and comfort. The control system 112 may suggest optimal damper positions and operational schedules to balance energy efficiency with ventilation requirements, allowing that the indoor environment remains comfortable while minimizing energy use.

[0225] Filter 418 may serve as an additional layer of air purification, allowing that the air entering the SRTU 400A is free from harmful particulates. The AI engine may also recommend the placement and maintenance schedule for the filter 418 to maximize its effectiveness and lifespan.

[0226] The heat wheel 413 provides for energy recovery, capturing heat from the exhaust air and transferring it to the incoming fresh air. The AI engine may provide suggestions for optimizing the heat wheel's design and operation, such as adjusting the rotational speed or enhancing the material properties, to improve energy recovery efficiency.

[0227] The exhaust fan 415 and exhaust damper 411 work together to expel stale air from the building while managing the internal pressure and airflow. The AI engine can analyze airflow patterns and recommend optimal fan speeds and damper positions for efficient ventilation and pressure balance within the building.

[0228] The centrifugal electronically commutated (EC) fan 409 is responsible for moving air through the SRTU 400A. The AI engine can monitor the fan's performance and provide recommendations for speed adjustments and maintenance schedules for efficient and reliable operation.

[0229] The compressor chamber 408 houses the components necessary for the refrigeration cycle, including the compressor and associated control mechanisms. The AI engine may analyze operational data and thermal images to suggest improvements in compressor efficiency, such as optimizing the refrigerant charge or adjusting the compressor speed.

[0230] In some embodiments, the SRTU control system 112 may provide automated suggestions for the design and operation of the air hood and grille. By analyzing thermal images captured by IR cameras, along with real-time airflow and pressure data, the AI engine can optimize the shape and placement of the air hood to ensure maximum intake efficiency and minimal resistance. For the grille, the AI engine may recommend the most effective design to distribute air evenly and reduce noise levels, as well as suggest materials that minimize debris accumulation and are easier to maintain. These automated suggestions may help in enhancing the overall performance and longevity of the SRTU.

[0231] Referring now to FIG. 5, it illustrates an exemplary SRTU system integrating an SRTU 500 with an IR camera 510 and a BMS 501, in accordance with some embodiments of the present invention. The SRTU 500 may be constructed to provide advanced HVAC functionality through intelligent monitoring and control mechanisms.

[0232] The SRTU 500 may include a control panel 502, which comprises the Controller and / or AI engine responsible for analyzing data and optimizing the operation of the unit. The Controller and / or AI engine processes information from various sources, including the IR camera 510 and the BMS 501, to ensure efficient and reliable performance.

[0233] The IR camera 510 may be positioned to capture thermal images of the SRTU 500. It continuously monitors the thermal profile of the unit, providing real-time data on temperature variations across different components inside the SRTU 500. The thermal imaging capability may allow the Controller and / or AI engine within the control panel 502 to detect anomalies, such as overheating or inefficient cooling, and take corrective actions promptly.

[0234] The SRTU 500 may be equipped with an air hood 504, which directs air intake into the system. The air hood 504 may ensure that the air entering the unit is properly channeled for optimal cooling or heating, contributing to the overall efficiency of the SRTU.

[0235] The BMS 501 may provide helpful data to the SRTU 500 via BMS signals 503. This data may include internal temperatures, occupancy levels, energy usage patterns, and other relevant metrics as discussed in various embodiments of the present invention. By integrating with the BMS 501, the Controller and / or AI engine in the control panel 502 can adjust the SRTU's operations based on real-time conditions and historical trends. For example, if the BMS indicates that a specific zone in the building is experiencing high occupancy and increased temperature, the Controller and / or AI engine can boost cooling in that area to maintain comfort.

[0236] The BMS signals 503 allow for seamless communication between the SRTU 500 and the BMS 501. This integration may enable the Controller and / or AI engine to consider a wide range of factors when making operational decisions, such as adjusting airflow, initiating defrost cycles, or modifying temperature settings based on occupancy patterns and energy usage trends within the building.

[0237] The control panel 502, equipped with the Controller and / or AI engine, may serve as the central hub for processing all incoming data. It can dynamically adjust the SRTU's settings to optimize performance, reduce energy consumption, and extend the lifespan of the unit. The Controller and / or AI engine's capabilities may include predictive maintenance, where it analyzes data trends to forecast potential issues and schedule maintenance activities proactively.

[0238] Furthermore, the Controller and / or AI engine can leverage historical data from both the IR camera 510 and the BMS 501 to refine its algorithms continually. This continuous learning process allows the SRTU 500 to adapt to changing conditions and improve its efficiency over time.

[0239] The function of the Air Hood 504 is to optimize the introduction of ambient air into the SRTU, leveraging cooler external temperatures to reduce the load on the cooling system, thereby enhancing energy efficiency. This is particularly advantageous during periods when the outside air is sufficiently cool to assist in meeting the cooling requirements of the building without the need for the unit to engage its full refrigerative cooling capabilities.

[0240] In keeping with the innovative aspects of the invention, the Air Hood 504 may be equipped with a series of environmental sensors. These sensors can detect not only temperature but also humidity levels, air quality, and the presence of contaminants. This real-time environmental data allows the SRTU 500 to intelligently determine whether to utilize the economizer mode (of the Economizer Hood 104 or Air Hood 504), wherein the unit increases the use of outdoor air to conserve energy.

[0241] Furthermore, the modular nature of the Air Hood 504 suggests that it may be constructed for easy removal and attachment, facilitating maintenance and potential upgrades. The hood's design may also include adjustable louvers or dampers, which can be automatically or manually adjusted to control the volume and direction of the incoming air, providing optimal performance under varying environmental conditions.

[0242] In some embodiments, the Controller and / or AI engine may provide automated design suggestions specifically for the Air Hood 504. Based on the detailed analysis of thermal images and BMS data, the Controller and / or AI engine can optimize the design and functionality of the Air Hood to enhance the overall performance and efficiency of the SRTU 500.

[0243] For example, Air Hood suggestion 504A may involve modifying the shape and orientation of the Air Hood 504 to improve the intake of ambient air. The Controller and / or AI engine may recommend a more aerodynamic design that reduces air resistance and turbulence, providing smoother and more efficient airflow into the SRTU 500.

[0244] Air Hood suggestion 504B may focus on integrating advanced filtration systems within the Air Hood 504B. Based on the Controller and / or AI engine's analysis of air quality data and particulate levels, it may suggest incorporating high-efficiency particulate air (HEPA) filters or electrostatic precipitators within the Air Hood 504B. These filters can effectively remove airborne contaminants and particulate matter from the incoming air, ensuring that only clean air enters the SRTU 500.

[0245] Additionally, the Controller and / or AI engine may propose the use of smart materials and coatings for the Air Hood 504. For example, it may suggest applying a hydrophobic coating to prevent water accumulation and reduce the risk of corrosion. AI ternatively, the Controller and / or AI engine may recommend using lightweight, high-durability composites that improve the structural integrity of the Air Hood while minimizing weight.

[0246] The Controller and / or AI engine also considers external factors such as environmental conditions and building-specific requirements. By analyzing data from the BMS 501, the Controller and / or AI engine can tailor its design suggestions to optimize the Air Hood 504 for specific climatic conditions, seasonal variations, and occupancy patterns. For example, in regions with high humidity, the Controller and / or AI engine may recommend integrating moisture control features to prevent condensation and improve overall air handling efficiency.

[0247] Furthermore, the Controller and / or AI engine's suggestions can be adaptive and dynamic. It continuously monitors the performance of the Air Hood 504 and provides real-time adjustments based on changing conditions. For example, if the AI detects increased particulate levels or changes in ambient air quality, it may recommend adjusting the filtration settings or implementing additional airflow control measures to maintain optimal performance. In some embodiments, the Controller and / or AI engine may automatically adjust the filtration settings and implement additional airflow control.

[0248] In some embodiments of the invention, the Economizer Hood 104 (or 504) may be constructed with an aerodynamic shape to maximize air intake efficiency while reducing drag, thus minimizing the load on the SRTU's internal fans and conserving energy.

[0249] The Economizer Hood may be constructed from a durable, weather-resistant material compatible with or similar to the rest of the SRTU's casing. It may be constructed to pivot or adjust its opening based on real-time sensor data, effectively capturing optimal air quantities while preventing the entry of debris or precipitation. This dynamic adjustability may be controlled by an intelligent mechanism that responds to changes in outdoor air conditions, such as temperature, humidity, and air quality.

[0250] Within the Economizer Hood (104), a series of high-efficiency filters can be integrated to clean incoming air of particulates and pollutants. These filters are easily accessible for maintenance and can be interchanged with different filtration grades depending on the specific environmental requirements of the installation site.

[0251] Furthermore, the Economizer Hood may include a built-in thermal exchange system, wherein incoming cooler air assists in pre-cooling the refrigerant or air streams within the SRTU, enhancing the unit's overall energy efficiency. This feature is particularly advantageous during transitional seasons when the external air temperature is lower than the indoor air temperature, allowing for natural cooling without engaging the unit's compressor.

[0252] In addition, the Economizer Hood may feature solar-reflective surfaces or coatings to prevent excessive heat absorption, and it may be insulated to maintain the desired temperature of the incoming air. The embodiment may also encompass a smart actuation system that allows the hood to be closed completely, securing the SRTU when outdoor conditions are unfavorable, or when the unit is not in use, thus protecting internal components.

[0253] Referring now to FIG. 5A, an exemplary embodiment of an SRTU system in accordance with the present invention is illustrated. The SRTU 500 may be strategically installed on the rooftop of a building 511. The building 511 may be equipped with a plurality of cameras 512 positioned both inside and outside of the building 511 to capture various activities within and around the building 511. The cameras 512 may be placed to monitor areas such as parking slots 513, people 514 entering and exiting the building 511, and vehicles 515 coming in and out of the premises.

[0254] The images or video feeds captured by these cameras 512 are transmitted to the Building Management System (BMS) 501. The BMS 501 acts as a central hub, collecting and processing the visual data from the cameras 512 and various sensors installed within the building. This data may then be sent to the SRTU control system 502. The control system 502 is equipped with a Controller and / or AI engine that analyzes the visual data in conjunction with other data sources, such as thermal images captured by the IR cameras 510 installed on, around and / or within the SRTU 500.

[0255] The Controller and / or AI engine may use the visual data (images or video feed from cameras 512) to monitor and predict occupancy patterns, vehicle movements, and the influx and outflow of people 514. This information is used for optimizing the HVAC system's performance. For example, the Controller and / or AI engine can adjust the ventilation and air conditioning settings based on the number of people entering the building 511. If a large number of people 514 are detected entering the building 511, the AI can anticipate an increased cooling demand and adjust the SRTU 500 operations accordingly to maintain optimal indoor temperatures.

[0256] Similarly, the cameras 512 monitoring the parking slots 513 may provide data on vehicle occupancy, which can be used to predict peak times for HVAC system usage. The Controller and / or AI engine can use this information to pre-cool or pre-heat the building spaces based on expected occupancy levels, thereby improving energy efficiency and comfort.

[0257] Additionally, the thermal images captured by the IR camera 510 may provide real-time temperature data of the SRTU 500 components. This data is analyzed by the Controller and / or AI engine to detect any anomalies or inefficiencies in the system. The AI can adjust the operation of the SRTU components, such as the heating and cooling coils, fans, and dampers, to optimize performance based on the thermal signatures.

[0258] In some embodiments of the present invention, the Controller and / or AI engine within the SRTU control system 502 may be constructed to learn and analyze patterns of occupancy within the building 511 by continuously monitoring the data captured by the plurality of cameras 512 installed both inside and outside the building 511.

[0259] The Controller and / or AI engine may process the visual data (captured by cameras 512) to identify trends and patterns in building occupancy. By analyzing historical data, the Controller and / or AI engine can determine specific times of the day, days of the week, and seasons when the building 511 experiences higher or lower occupancy levels. For example, the AI may learn that occupancy peaks during weekday mornings and afternoons, coinciding with typical office hours, and that there is a significant drop in occupancy during weekends and holidays.

[0260] Additionally, the Controller and / or AI engine can identify seasonal variations in occupancy. For example, it may detect increased occupancy during the winter months or during the summer when special programs or events are held. By recognizing these patterns, the Controller and / or AI engine can anticipate HVAC demands more accurately.

[0261] Based on these learned patterns, the Controller and / or AI engine optimizes the operation of the SRTU 500 to align with predicted occupancy levels. During times of expected high occupancy, the Controller and / or AI engine can pre-emptively adjust the HVAC settings to ensure that the building 511 is comfortably cooled or heated. Conversely, during periods of low occupancy, the Controller and / or AI engine can scale back the HVAC operation to conserve energy, thereby improving overall efficiency.

[0262] In some embodiments, if the building 511 is a warehouse, the Controller and / or AI engine can intelligently control the SRTU components based on the vehicles 515 entering or exiting the building 511. The plurality of cameras 512 installed around the warehouse monitor the movement of vehicles 515, capturing images and video feeds that are sent to the BMS 501 and subsequently to the SRTU control system 502.

[0263] The Controller and / or AI engine (within the SRTU control system 502) processes this data to identify patterns in vehicle activity. For example, the Controller and / or AI engine may detect specific times of day when delivery trucks or forklifts are most active, indicating periods of high activity within the warehouse. It can learn these patterns over time, noting peak hours for deliveries and shipments.

[0264] Based on this analysis, the Controller and / or AI engine can make real-time adjustments to the SRTU 500 and its components to optimize the indoor climate of the warehouse. For example, when a high volume of vehicles 515 is detected entering the warehouse, the Controller and / or AI engine can increase the airflow and adjust the cooling or heating settings to compensate for the additional heat or cold brought in by frequent door openings.

[0265] In scenarios where vehicles 515 are frequently exiting the warehouse, such as during the dispatch of goods, the Controller and / or AI engine can reduce the cooling or heating load to save energy, knowing that doors will be opened less frequently. This dynamic adjustment based on vehicle activity helps maintain optimal conditions within the warehouse while improving energy efficiency and reducing operational costs. Moreover, the Controller and / or AI engine can integrate this data with other environmental sensors within the warehouse, such as temperature, humidity, and air quality sensors, to further refine the control of the SRTU components.

[0266] Referring now to FIG. 6, an exemplary view of the internal configuration of the SRTU 600, which may align with the innovative principles of the present invention. The depiction showcases the various components of the SRTU 600 and their functions, emphasizing the unit's efficiency and environmental adaptability.

[0267] The journey of air through the SRTU 600 begins at the Air Hood 604, an intelligently constructed intake system that may be equipped with environmental sensors for detecting temperature, humidity, and pollutant levels. The data from these sensors enables the SRTU 600 to adjust the volume and temperature of the incoming air, optimizing the unit's energy usage.

[0268] Air passes through the Damper 605, which is a controllable gate dictating airflow into the system, allowing the SRTU 600 to respond to varying ventilation needs dynamically. The initial Filter 606, possibly a high-efficiency particulate air (HEPA) filter, traps fine particles from the incoming air, which facilitates the maintenance of high indoor air quality.

[0269] The Heat Wheel 603 is a pivotal energy recovery component that may capture thermal energy from the exhaust air and transfer it to the incoming fresh air or vice-versa. This process significantly reduces the energy required to bring the incoming air to a comfortable temperature.

[0270] Subsequent Filters 602 provide an additional level of air purification before the air reaches Fan 601. The fan 601, constructed for variable speed operation, circulates air through the SRTU 600 efficiently, adapting to the system's current load, further contributing to energy savings.

[0271] The Exhaust system, comprised of the Exhaust Damper 605 and the Exhaust Fan 609, manages the removal of indoor air through the Grille 607. The grille 607 design may be adjustable, allowing for directional control of the airflow to distribute the indoor air outside the building. The damper 605 adjusts the amount of air being expelled, maintaining the building's pressure balance and air quality.

[0272] The Filter 610, positioned strategically within the airflow pathway, may serve a dual-purpose role in some embodiments of the invention. While it may primarily act to purify the air being circulated into the building, providing a clean and healthy indoor environment, it may also be constructed to filter the exhaust air leaving the building. This unique feature may ensure that the SRTU 600 not only protects the internal environment from external pollutants but also minimizes the HVAC system's environmental footprint by cleaning the air before it is released back into the atmosphere.

[0273] The Mixing Damper 611 of the SRTU 600 may be constructed to regulate the blend of fresh outdoor air with the return indoor air within the system. The damper 611 may adjust the proportions of air mixed based on the optimal requirements for indoor air quality and temperature control. Its operation is central to the SRTU's energy efficiency, as it can reduce the need for heating or cooling through the Heating / Cooling Coil 612 by taking advantage of the desired properties of the air streams. For example, during cooler periods, the damper 611 can allow more warm return air to mix with the cooler fresh air to minimize the heating requirements. The Heating / Cooling Coil 612 adjusts the air temperature to a desired level. The coil's operation is responsive, with the ability to switch between heating and cooling to maintain consistent indoor conditions.

[0274] In some embodiments of the present invention, the atmospheric air is processed through the SRTU 600 by first passing through the air hood 604, then the damper 605, followed by the filter 606, the heat wheel 607, and additional filters 602, creating an atmospheric conveyance channel towards that heating coil or the cooling coil 612. This atmospheric conveyance channel then directs the air through either the heating coil or the cooling coil 612, or both, depending on the system's requirements. The movement of atmospheric air through this channel is controlled by the operation of the centrifugal electronically commutated fan 601, which adjusts its speed to ensure efficient air distribution and optimal temperature regulation.

[0275] In some embodiments of the invention, each part of the SRTU 600 may be constructed to work in concert, creating an integrated system that prioritizes energy efficiency, environmental impact, and air quality. The unit's modular design further facilitates easy maintenance and replacement of individual components. Further, unique features of this SRTU 600 may include smart diagnostic systems that monitor the performance of each component and alert maintenance personnel of potential issues before they arise. Additionally, the use of advanced composite materials for components like dampers and filters can further enhance durability and performance while maintaining the comparatively lightweight nature of the unit.

[0276] Furthermore, an IR camera 615 can be strategically installed on the roof where the SRTU 600 is placed, providing a comprehensive vantage point to capture thermal images of the entire unit. This placement may ensure that the IR camera can monitor the surface temperature of the SRTU 600 accurately, detecting heat signatures that correlate with the internal components' performance. By analyzing these thermal images, the Controller and / or AI engine can identify potential issues, optimize operations, and schedule maintenance activities proactively, ensuring the SRTU 600 operates efficiently and reliably. For example, the heat signatures captured on the SRTU's surface above the location of the Heat Wheel 603, or the Heating / Cooling Coil 612 can provide insights into their operational status. High temperatures at these spots may indicate excessive load or potential malfunction, prompting the Controller and / or AI engine in the control panel to adjust the SRTU's operations or initiate maintenance procedures.

[0277] The thermal images captured by the IR camera 615 may enable the Controller and / or AI engine to monitor the efficiency of the internal components continually. For example, if the exterior surface above the Exhaust Fan 609 shows an unusually high temperature, it may suggest that the fan is not expelling air efficiently, possibly due to blockage or mechanical failure. Similarly, thermal anomalies around the Mixing Damper 611 may indicate improper air mixing, affecting the overall efficiency of the HVAC system.

[0278] By integrating the IR camera 615 and leveraging its thermal imaging capabilities, the SRTU 600 may ensure that each component operates within optimal temperature ranges, thereby enhancing energy efficiency, reducing wear and tear, and extending the system's lifespan. This advanced thermal monitoring system may allow for real-time adjustments and predictive maintenance, ensuring the SRTU 600 remains reliable and efficient under varying operational conditions.

[0279] Referring now to FIG. 7, an exemplary view of the SRTU unit 700 in accordance with an embodiment of the invention. The SRTU 700 comprises a Damper 701 which is essential for controlling the flow of air into and out of the SRTU 700. The damper 701 can be adjusted to regulate the volume of air based on the system's needs, thereby enhancing the unit's overall energy efficiency. The damper 701 can be automated, responding to signals from the SRTU's control system (not shown, but housed along with other components with the SRTU 700) that dictate the required airflow based on various factors, such as the internal temperature demand, the quality of the outside air, and the specific operational mode of the HVAC system.

[0280] Additionally, the damper's design may include a series of airtight seals to prevent energy losses and maintain the integrity of the air being processed. This contributes to the sustainable nature of the SRTU 700, as minimal energy is wasted during operation.

[0281] An IR camera 710 may strategically be installed on or around the SRTU 700 to capture thermal images of at least one surface of the SRTU 700. For example, the IR camera 710 can be positioned to capture thermal images of the top surface 702 of the SRTU 700. The thermal images provide a visual representation of the temperature distribution across the surface of the SRTU 700, highlighting areas of varying heat signatures.

[0282] These thermal images are then transmitted to the SRTU control system, where a Controller and / or AI engine processes the images to identify specific heat signatures corresponding to the internal components of the SRTU 700. For example, the heat signatures 710A detected on the top surface 702 may be indicative of the operating condition of the dampers 701 located inside the SRTU 700. By analyzing the heat signatures 710A, the Controller and / or AI engine can determine whether the dampers 701 are functioning optimally or if there are any anomalies that need to be addressed.

[0283] The Controller and / or AI engine may utilize advanced algorithms to compare the detected heat signatures against predefined optimal temperature ranges for each SRTU component. If the heat signature 710A deviates from the expected range, it indicates a potential issue with the dampers 701. The Controller and / or AI engine then takes appropriate actions to control the SRTU 700 and its components to rectify the issue. For example, if the dampers 701 are overheating, the Controller and / or AI engine may adjust the airflow or activate cooling mechanisms to bring the temperature back within the desired range.

[0284] Moreover, the Controller and / or AI engine continuously monitors the thermal images to ensure real-time responsiveness to any changes in the heat signatures. This dynamic monitoring allows the system to maintain optimal performance and efficiency of the SRTU 700. The Controller and / or AI engine can also predict potential maintenance needs by identifying gradual changes in heat signatures over time, enabling proactive maintenance, and reducing the risk of component failure.

[0285] In addition to controlling the SRTU 700, the Controller and / or AI engine can integrate with the building's HVAC system to optimize overall climate control. For example, if the thermal images indicate that the dampers 701 are not operating efficiently, the Controller and / or AI engine can adjust the HVAC settings to compensate, providing consistent and comfortable indoor conditions.

[0286] In some embodiments, the Controller and / or AI engine within the control system of the SRTU 700 may leverage thermal data captured by an IR camera positioned on the roof or nearby to monitor heat signatures on the surface of the SRTU 700. By analyzing these thermal images, the Controller and / or AI engine can infer the operational status of internal components, including the damper 701. For example, if the thermal images indicate an unusual heat buildup on the SRTU's surface above and / or near the location of the damper 701, it may suggest that the damper is not functioning optimally, possibly due to blockage or mechanical failure.

[0287] The Controller and / or AI engine can then take proactive measures to adjust the damper 701 to ensure efficient airflow. For example, if the heat signatures suggest that the airflow through the damper 701 is restricted, the Controller and / or AI engine can signal the damper to open wider to increase air volume and improve cooling efficiency. Conversely, if excessive cooling is detected, the AI can close the damper slightly to reduce airflow and maintain the desired temperature, thereby optimizing energy usage.

[0288] Moreover, the Controller and / or AI engine can use the thermal data to detect patterns over time, learning the typical thermal behavior associated with different damper positions and operational states. This learning may enable the AI to predict the most efficient damper settings for varying conditions, such as changes in external temperature, occupancy levels, and internal heat generation. For example, during peak occupancy, the AI can pre-emptively adjust the damper 701 to maximize airflow and cooling capacity, providing comfort without waiting for temperature sensors alone to trigger adjustments.

[0289] Referring now to FIG. 8, an exemplary view of the SRTU unit 800 in accordance with another embodiment of the invention, showcasing its filtration system. The Filters 801 are constructed to purify the incoming air, removing particulates, allergens, and other airborne contaminants to ensure a high standard of air quality within the building.

[0290] The design of the Filters 801 may include multiple stages with different filtration media to address a variety of contaminants. The first stage may consist of a pre-filter for larger particles, followed by higher-grade filters, such as HEPA filters, for fine particulates. This multi-stage approach enables comprehensive air purification and contributes to the health and comfort of the building's occupants. Given the modular nature of the SRTU 800 as discussed in the invention, the Filters 801 are likely constructed for easy access and maintenance. They may be housed in a removable panel or drawer-like component, allowing for quick replacement or cleaning, which aligns with the need for user-friendly operation and serviceability.

[0291] The positioning of the Filters 801 at the air intake point further suggests that the SRTU 800 is engineered to address environmental sustainability. By ensuring that the exhaust air is also filtered, the SRTU 800 can minimize the impact on the external environment.

[0292] An IR camera 810 may strategically be installed on or around the SRTU 800 to capture thermal images of at least one surface of the SRTU 800. For example, the IR camera 810 can be positioned to capture thermal images of the top surface 802 of the SRTU 800. These thermal images provide a detailed visual representation of the temperature distribution across the top surface 802, highlighting areas of varying heat signatures.

[0293] The thermal images are then transmitted to the SRTU control system, where a Controller and / or AI engine may process the thermal images to identify specific heat signatures corresponding to the internal components of the SRTU 800. For example, the heat signature 810A detected on the surface 802 may be indicative of the operating condition of the filters 801 located inside the SRTU 800. By analyzing the heat signatures, the Controller and / or AI engine can determine whether the filters 801 are functioning optimally or if there are any anomalies that need to be addressed.

[0294] The Controller and / or AI engine may utilize advanced algorithms to compare the detected heat signatures against predefined optimal temperature ranges for each SRTU component. If the heat signature 810A deviates from the expected range, it indicates a potential issue with the filters 801. The Controller and / or AI engine then takes appropriate actions to control the SRTU 800 and its components to rectify the issue. For example, if the filters 801 are clogged or not functioning efficiently, the Controller and / or AI engine may adjust the airflow or initiate a maintenance alert to replace or clean the filters 801.

[0295] In some embodiments, the Controller and / or AI engine within the control system of the SRTU 800 can utilize thermal data captured by an IR camera to monitor the condition of the Filters 801. By analyzing heat signatures on the surface of the SRTU 800, the Controller and / or AI engine can detect changes in airflow and potential blockages within the filters. For example, if the thermal images reveal a consistent increase in temperature around the filters, it may indicate reduced airflow due to clogged or dirty filters.

[0296] Based on this analysis, the Controller and / or AI engine can optimize the filtration system's operation. It can also send alerts for maintenance when it detects that the filters need cleaning or replacement, ensuring that the air purification process remains efficient. Additionally, the AI can adjust the speed of the fans to compensate for any detected airflow reduction, maintaining the desired indoor air quality without compromising energy efficiency.

[0297] The Controller and / or AI engine can also learn from historical thermal data to predict when the filters will likely require maintenance. By identifying patterns in how quickly the filters become dirty under different conditions, the AI can create a maintenance schedule that minimizes downtime and maximizes the SRTU's operational efficiency.

[0298] Furthermore, the Controller and / or AI engine can integrate data from the BMS to enhance its analysis. For example, it can correlate occupancy data with filter usage, understanding that higher occupancy levels may lead to faster accumulation of contaminants. This may allow for more precise and responsive adjustments to the filtration system, providing optimal air quality at all times.

[0299] Referring now to FIG. 9, an exemplary view of the SRTU unit 900 in accordance with an embodiment of the invention, focusing on the temperature modulation components within the system. A Cooling Coil 901 is constructed to reduce the temperature of the air as it flows through the unit 900. The Cooling Coil 901 may utilize an eco-friendly refrigerant and advanced materials for enhanced heat exchange efficiency, contributing to the SRTU's energy-saving features. The coil's design may also allow for variable cooling rates, adapting to the current thermal load and external temperatures to optimize energy consumption.

[0300] Adjacent to the cooling component is a Heating Coil 902, which raises the temperature of the air during colder conditions. The Heating Coil 902 may incorporate technology such as low-emission burners or energy-efficient heat pumps, aligning with the environmentally conscious approach. The modularity of the design means that both the Cooling Coil 901 and Heating Coil 902 can be easily accessed for maintenance or replaced as part of the SRTU's serviceable design. Both the Cooling Coil 901 and the Heating Coil 902 are important for maintaining the desired indoor environment, responding to the demands set by the SRTU's integrated control system. The system can manage the operation of the coils based on inputs from various sensors, ensuring that indoor temperature and humidity levels remain comfortable for occupants.

[0301] An IR camera 910 may strategically be installed on or around the SRTU 900 to capture thermal images of the top surface of the SRTU 900. The IR camera 910 can be positioned to capture detailed thermal images, highlighting areas with different heat signatures across the top surface. These thermal images are then transmitted to the SRTU control system for analysis by a Controller and / or AI engine.

[0302] The Controller and / or AI engine processes the thermal images to identify specific heat signatures corresponding to the internal components of the SRTU 900. For example, heat signature 910A detected on the surface of the SRTU 900 corresponds to the Cooling Coil 901, while heat signature 910B corresponds to the Heating Coil 902. These heat signatures may provide real-time data on the operational temperatures of these coils, allowing the Controller and / or AI engine to monitor their performance continuously.

[0303] The Controller and / or AI engine may utilize advanced algorithms to analyze the temperature distributions represented by the heat signatures. By comparing these heat signatures to predefined optimal temperature ranges, the Controller and / or AI engine can identify any deviations or anomalies. For example, if heat signature 910A indicates that the cooling coil 901 is operating at a higher temperature than expected, the Controller and / or AI engine may determine that the coil 901 is not functioning efficiently or that there is an issue with the refrigerant flow.

[0304] Based on the analysis of the heat signatures, the Controller and / or AI engine can take several actions to control the SRTU 900 and its components. If the cooling coil 901 is not performing optimally, the Controller and / or AI engine can adjust the airflow, increase the refrigerant flow, or initiate a maintenance alert to inspect the coil 901. Similarly, if the heating coil 902 shows an unusual heat signature 910B, the Controller and / or AI engine can modify the heating parameters to ensure efficient operation or schedule a maintenance check.

[0305] Furthermore, the Controller and / or AI engine can predict potential maintenance needs by tracking gradual changes in the heat signatures over time. The Controller and / or AI engine may also provide recommendations for design modifications based on the analysis of the thermal images. For example, it may suggest changes to the placement or design of the cooling coil 901 and heating coil 902 to improve heat dissipation and enhance overall efficiency.

[0306] In some embodiments, the Controller and / or AI engine integrated within the SRTU's control system may leverage data from an IR camera to monitor the thermal performance of both the Cooling Coil 901 and the Heating Coil 902. By capturing thermal images of the SRTU's exterior, the Controller and / or AI engine can identify specific heat signatures that correlate with the operation of these coils. For example, if the IR camera detects an unusually high temperature on the surface area above the Heating Coil 902, it may indicate that the coil is overworking or experiencing a malfunction.

[0307] The Controller and / or AI engine can then use this thermal data to make real-time adjustments to the operation of the coils. For example, if the Cooling Coil 901 shows signs of inefficiency through elevated surface temperatures, the AI can increase the flow rate of the refrigerant to enhance cooling performance. Similarly, if the Heating Coil 902 is not generating sufficient heat, the AI can activate supplementary heating elements or adjust the airflow to improve heating efficiency.

[0308] The Controller and / or AI engine may also analyze historical thermal data to predict maintenance needs for the coils. By identifying patterns such as gradual increases or decreases in surface temperature over time, the AI can forecast when the coils are likely to require cleaning or other maintenance. This predictive maintenance capability helps prevent unexpected failures and enables the SRTU 900 to operate reliably.

[0309] In some embodiments, an indirect burner 903 may be incorporated into the SRTU 900 to provide an efficient means of heating. The indirect burner 903 may operate by transferring heat through a heat exchanger rather than directly exposing the air to combustion gases. This method may ensure that the air circulated within the building remains free of combustion by-products, enhancing indoor air quality and safety. The indirect burner 903 can utilize various fuels, such as natural gas, propane, or biofuels, aligning with the environmentally conscious design principles of the SRTU 900.

[0310] The incorporation of the indirect burner 903 within the SRTU 900 may offer several advantages. Firstly, it may allow for precise control over the heating process. The Controller and / or AI engine within the control system can regulate the burner's output based on real-time data from temperature sensors and thermal images captured by the IR camera. This may ensure that the heating coil 902 maintains the desired temperature efficiently, even under varying load conditions. The AI can adjust the burner's fuel flow rate and ignition cycles to optimize performance and energy consumption, minimizing operational costs while maintaining comfort levels.

[0311] Moreover, the indirect burner 903 may enhance the system's flexibility and reliability. In colder climates, the burner 903 provides a robust and responsive heating solution that can quickly adapt to changing weather conditions. The Controller and / or AI engine can predict heating demands based on historical data and external weather forecasts, ensuring that the SRTU 900 pre-heats the indoor space before occupancy periods, thus enhancing occupant comfort.

[0312] The indirect burner's design may also include safety features such as flame detection sensors, pressure monitors, and automatic shutoff valves. These safety mechanisms may be integrated with the Controller and / or AI engine, which continuously monitors the burner's operation and can take immediate action in case of any abnormalities, such as extinguishing the flame if an unsafe condition is detected.

[0313] Additionally, the use of the indirect burner 903 aligns with the SRTU 900's modular design, allowing for easy maintenance and replacement. The burner and its associated components can be accessed and serviced without disrupting the rest of the unit, providing minimal downtime. Advanced materials used in the construction of the burner 903 and heat exchanger may improve durability and thermal efficiency, contributing to the long-term sustainability of the SRTU 900.

[0314] In some embodiments of the invention, the placement of the indirect burner 903 can be either inside or outside the SRTU 900, each configuration offering distinct advantages based on specific operational requirements and design considerations.

[0315] When placed inside the SRTU 900, the indirect burner 903 may typically be located near the heating coil 902 to facilitate efficient heat transfer. The burner 903 heats the air indirectly through a heat exchanger, which then warms the air as it passes over the heating coil 902. Such a configuration may ensure that the heat generated by the burner 903 is effectively utilized within the SRTU 900, minimizing heat losses and maximizing energy efficiency. The placement inside the unit may also allow for compact and integrated design, reducing the overall footprint of the HVAC system.

[0316] The internal placement of the indirect burner 903 requires careful design to ensure proper ventilation and safe operation. The burner compartment must be isolated from the air handling areas to prevent any combustion by-products from entering the airstream. Additionally, the compartment may be equipped with safety features such as flame detection sensors, pressure monitors, and automatic shutoff valves to ensure safe operation. The Controller and / or AI engine can monitor these safety features and adjust the burner's operation based on real-time data to maintain optimal performance and safety.

[0317] AI ternatively, when the indirect burner 903 is placed outside the SRTU 900, it can be located in a separate mechanical room or adjacent to the unit 900. In such a configuration, the burner 903 heats a fluid (such as water or a glycol mixture) that is circulated through a heat exchanger inside the SRTU 900. This setup may allow for flexibility in system design, as the burner can be placed in a location that is more convenient for maintenance and fuel supply. It also reduces the risk of combustion-related issues within the SRTU 900, as the burner 903 is physically separated from the air handling components of the SRTU 900.

[0318] The external placement of the indirect burner 903 may require a robust piping system to transport the heated fluid to and from the SRTU 900. The heat exchanger inside the SRTU 900 transfers the heat from the fluid to the air, providing efficient heating. The Controller and / or AI engine can control the flow rate of the heated fluid and the burner's operation to match the heating demand, providing precise temperature control.

[0319] Referring now to FIG. 10, an exemplary view of the SRTU 1000 in accordance with an embodiment of the invention, showcasing a Centrifugal EC (Electronically Commutated) Fan 1001. This fan is integral to the HVAC system, as it is responsible for moving air through the unit 1000 for both heating and cooling processes.

[0320] The Centrifugal EC Fan 1001 is chosen for its energy-efficient operation and its ability to provide variable airflow. Electronically commutated motors are known for their high efficiency, especially when compared to traditional motors, as they can adapt their speed to the system's demand, significantly reducing power consumption. The fan's design can be optimized for quiet operation, which maintains a comfortable environment both inside and outside the building. Additionally, the fan's centrifugal design allows it to work effectively against the resistance caused by ductwork and filters within the SRTU 1000, providing consistent airflow and pressure throughout the system.

[0321] A plurality of infrared (IR) cameras may be strategically installed within the SRTU 1000 to capture thermal images of the internal components of the SRTU 1000. For example, an IR camera 1010 may be positioned within the SRTU 1000 to monitor the heating coil 1002. The IR camera 1010 captures detailed thermal images 1010A of the heating coil 1002, providing real-time data on its temperature distribution and operational state.

[0322] The captured thermal images 1010A are then transmitted to the SRTU control system, where a Controller and / or AI engine may process these images 1010A to generate thermal profiles of the heating coil 1002. The thermal profiles reveal temperature variations across the heating coil 1002, identifying hotspots, cold spots, and areas of potential concern. By analyzing these thermal profiles, the Controller and / or AI engine can assess the heating coil's performance, detect anomalies, and predict maintenance needs.

[0323] The Controller and / or AI engine may use advanced image processing algorithms to convert the thermal images into digital value patterns representing the temperature distribution across the heating coil 1002. These digital value patterns are then mapped against predefined optimal temperature ranges for the heating coil 1002. If the Controller and / or AI engine detects temperature deviations outside the acceptable range, it can trigger alerts or initiate corrective actions to address the issue.

[0324] For example, if the thermal images 1010A indicate that a section of the heating coil 1002 is significantly hotter than the rest, this may suggest a blockage or inefficiency in that part of the coil 1002. The Controller and / or AI engine can respond by adjusting the airflow, modulating the heating power, or scheduling a maintenance check to inspect and clean the coil 1002. With this proactive approach, the heating coil 1002 operates efficiently and prevents potential failures.

[0325] Furthermore, the Controller and / or AI engine can use historical data and real-time thermal images to track the heating coil's performance over time. By identifying gradual changes in the temperature distribution, the Controller and / or AI engine can predict when the coil 1002 may require maintenance or replacement, allowing for timely intervention and reducing the risk of unexpected breakdowns. The integration of IR cameras within the SRTU 1000 may enhance the unit's ability to monitor and optimize its internal components continuously. With the AI-driven analysis of thermal images, the heating coil 1002, along with other important components, operates at peak efficiency.

[0326] In addition to monitoring the heating coil, the plurality of IR cameras can be positioned to capture thermal images of other internal components such as the cooling coil, evaporator coil, filters, dampers, and fans. Each component's thermal profile is analyzed by the Controller and / or AI engine to ensure optimal performance and detect any anomalies that may impact the SRTU's efficiency. In some embodiments, a plurality of IR cameras may be placed on, around or inside the SRTU 1000.

[0327] The Controller and / or AI engine can also provide recommendations for design modifications (for the SRTU components, ductwork, duct-pipes, and / or the SRTU itself) based on the analysis of thermal images. For example, it may suggest changes to the placement of the heating coil or adjustments to the airflow pathways to enhance heat dissipation and improve overall efficiency. These automated design suggestions may help in optimizing the SRTU's configuration for better performance and energy efficiency.

[0328] In some embodiments, the Controller and / or AI engine integrated within the SRTU 1000's control system can leverage data from an IR camera and various sensors to monitor the performance of the Centrifugal EC Fan 1001. The IR camera can capture thermal images of the SRTU's exterior surface, focusing on the areas corresponding to the fan and its motor. By analyzing these thermal images, the Controller and / or AI engine can predict or detect abnormal heat patterns that may indicate issues such as overheating or mechanical stress.

[0329] For example, if the IR camera detects an elevated temperature around the fan motor, the Controller and / or AI engine can interpret this as a sign of potential overloading or bearing failure. The AI can then adjust the fan's speed or operational parameters to alleviate the stress, providing continued efficient performance while preventing damage. Additionally, the Controller and / or AI engine can trigger maintenance alerts, prompting technicians to inspect the fan before a minor issue escalates into a significant problem.

[0330] The Controller and / or AI engine can also optimize the operation of the Centrifugal EC Fan 1001 based on real-time airflow and pressure data from sensors within the SRTU 1000. By continuously adjusting the fan speed to match the current demand, the AI enables the system to maintain optimal airflow and pressure, contributing to the overall energy efficiency of the HVAC system. For example, during periods of low cooling or heating demand, the AI can reduce the fan speed to conserve energy, whereas, during peak demand, it can increase the speed to ensure adequate air circulation.

[0331] The Controller and / or AI engine can also utilize historical data and predictive analytics to anticipate future airflow needs based on patterns such as occupancy levels, time of day, and external weather conditions. This allows the SRTU 1000 to pre-emptively adjust the fan's operation, ensuring that the indoor environment remains comfortable and energy efficient.

[0332] Referring now to FIG. 11, an exemplary view of the SRTU 1100 in accordance with an embodiment of the invention, highlighting a Damper 1101 with an innovative design and a placement feature “Damper Open”. This feature is indicative of the SRTU's energy-efficient design, which allows for the modulation of air circulation to minimize heating requirements when conditions permit.

[0333] The Damper 1101 can adjust to allow for the recirculation of air within the system. By recirculating warmer indoor air, instead of solely relying on outside air that may be cooler, the SRTU 1100 can reduce the demand on its heating components. This is especially beneficial during periods of mild outdoor temperatures, where the need for additional heating is lessened, thereby conserving energy and reducing operational costs. In “Damper Open” mode, the system can accept fresh air intake based on specific requirements and considering the differential between indoor-outdoor temperatures. During this mode, the system can also recirculate the air as needed to minimize heating or cooling requirements.

[0334] The Damper's capacity to recirculate air also demonstrates the SRTU's responsiveness to the internal climate conditions of the building, dynamically adjusting to maintain comfort levels with optimal energy usage. This process can be managed automatically by the SRTU's control system, which may process data from temperature sensors within the building to make real-time adjustments to the damper positions.

[0335] The Damper 1101 demonstrates an innovative design that may contrast with the exhaust damper 605 as shown in FIG. 6. The damper 1101 represents a design where the damper 1101 can be adjusted to an open position, allowing for the recirculation of indoor air. This recirculation is a strategic function that takes advantage of the thermal energy already present within the building's environment, thereby minimizing the need for additional heating and reducing energy consumption.

[0336] In comparison, the exhaust damper 605 in FIG. 6 may be constructed primarily (although not necessarily) to manage the expulsion of air from the building's interior. Its operation may typically involve releasing stale air and maintaining air quality, but it may not contribute directly to the heating efficiency of the system.

[0337] The damper 1101's design and placement may allow for a more dynamic and responsive air handling strategy within the SRTU 1100. When the indoor temperature is higher than the outside air temperature, the damper opens to recirculate the warmer indoor air, thus conserving heat and reducing the demand on the heating coil. The control systems for both dampers (1101&605), although not detailed in the figures, may likely be different. The control system for the recirculating damper 1101 may be responsive to temperature variations and capable of precise modulation to balance indoor air temperature efficiently. The control system for the exhaust damper 605 may be simpler, focusing on air quality parameters and possibly building pressurization.

[0338] In some embodiments, the Controller and / or AI engine within the SRTU 1100 leverages thermal data captured by an IR camera to optimize the operation of Damper 1101. By monitoring the heat signatures on the exterior surface of the SRTU 1100, the Controller and / or AI engine can infer the efficiency of air recirculation and heating processes. For example, if the thermal images show a consistent temperature increase near the damper, it may indicate that the damper 1101 is effectively recirculating warm indoor air, reducing the need for additional heating.

[0339] The Controller and / or AI engine can make real-time adjustments to the damper position based on the analyzed thermal data and / or inputs from temperature sensors installed within the SRTU 1100 as well as within the building. If the AI detects that the indoor air temperature is higher than the outdoor temperature, it can open the damper to maximize air recirculation, conserving energy. Conversely, if the indoor temperature drops, the AI can close the damper 1101 to limit recirculation and initiate additional heating.

[0340] Additionally, the Controller and / or AI engine can predict the optimal times for damper operation by analyzing historical temperature data and occupancy patterns. By understanding when the building is typically occupied or unoccupied, the AI can pre-emptively adjust the damper 1101 to maintain a comfortable indoor climate with minimal energy use.

[0341] Referring now to FIG. 12, an exemplary view of the SRTU 1200 in accordance with an embodiment of the invention. It specifically details the air management pathways within the HVAC system. The Fresh Air Intake 1201 through an Air Hood (e.g., 504) is an important component that indicates where outside air enters the SRTU 1200. This air intake may include filtration and possibly pre-heating or pre-cooling functions as part of the unit's energy-efficient design.

[0342] The Return Air Exhaust 1202 is where the indoor air, which has been circulated through the building and is now being exhausted, exits the SRTU 1200. This design may also incorporate energy recovery systems to retain some of the thermal energy from the exhaust air, which may then be transferred to the incoming fresh air to improve overall efficiency.

[0343] The Damper 1203 having a specific placement feature “Damper Closed” (when compared to the Damper Open feature of the damper 1101 as discussed in FIG. 11), illustrates a mode where the unit 1200 is not taking in outside air and is recirculating the indoor air. This may be used during peak heating or cooling periods when the outside air temperature is far from the desired indoor conditions, or when the air quality outside is poor. In this mode, the SRTU 1200 may rely solely on its internal heating and cooling mechanisms to maintain the indoor climate.

[0344] The integration of dampers (1101 or 1203) in the SRTUs (1100 or 1200) suggests a level of control and adaptability in the operation of the SRTUs. The system can modify the balance of fresh air to return air to optimize air quality and energy usage. These dampers may be part of the modular design of the SRTUs, allowing for easy access and maintenance, consistent with the emphasis on serviceability described throughout the invention.

[0345] In some embodiments, the Controller and / or AI engine integrated within the SRTU 1200 can leverage thermal data captured by an IR camera to optimize the operation of Damper 1203. By analyzing the heat signatures on the SRTU's exterior surface, the Controller and / or AI engine can infer the effectiveness of air recirculation and identify any potential inefficiencies. For example, if the thermal images indicate an unusual temperature gradient near the damper, it may suggest that the damper is not sealing properly when closed, leading to unwanted air exchange and energy loss.

[0346] The Controller and / or AI engine can make real-time adjustments to the damper positions based on this thermal data and inputs from indoor temperature and air quality sensors. If the AI detects that the indoor air quality is degrading due to high levels of CO2 or other pollutants, it can open the damper 1203 to allow fresh air intake, even if the outside temperature is not ideal. Conversely, if maintaining indoor temperature is the priority, the AI can ensure the damper 1203 remains closed to maximize recirculation and minimize energy consumption.

[0347] Moreover, the Controller and / or AI engine can also predict optimal damper operation times by analyzing historical data and forecasting environmental conditions. For example, it can anticipate periods of high occupancy or external weather changes, adjusting the damper positions in advance to maintain optimal indoor conditions with minimal energy use.

[0348] In an embodiment of the invention, an SRTU may incorporate an advanced damper mechanism capable of automatic or manual modulation to optimize environmental conditions within a building. The SRTU features a sophisticated control system integrated with sensors that continuously monitor various parameters such as indoor air quality, temperature, humidity, and outdoor air conditions.

[0349] In some embodiments of the invention, the dampers may play a pivotal role in regulating the airflow within the SRTU. Dampers can be automatically adjusted to either an open or closed position, dictating the flow of air based on real-time data collected by the sensors. For example, when the indoor air temperature is lower than desired, the dampers may automatically close, reducing the intake of cooler outside air and enabling the system to efficiently recirculate and warm the indoor air. Conversely, if the sensors detect that the indoor air quality is compromised or the indoor air temperature exceeds the desired threshold, the dampers can open to allow fresh outside air to enter, facilitating the dilution of indoor pollutants and assisting in temperature control.

[0350] The damper operation may not solely be reliant on automation. Users have the capability to manually override the automatic settings, providing flexibility in operation. This can be particularly useful in scenarios where specific ventilation requirements are needed, such as in response to occupancy changes or particular indoor activities that may affect air quality or temperature.

[0351] Moreover, the SRTU can operate in various modes, depending on the damper positions. In the ‘Damper Open’ mode, the system prioritizes fresh air intake, which is essential for maintaining air quality and managing internal CO2 levels. In the ‘Damper Closed’ mode, the emphasis is on air recirculation, which is energy efficient and can be beneficial for maintaining consistent thermal conditions within the building.

[0352] The SRTU can dynamically adjust to the least energy-intensive operation required to maintain comfort. Additionally, it contributes to the building's environmental sustainability by reducing the need for mechanical heating or cooling when the external conditions are favorable for natural ventilation or air recirculation. With the inclusion of user control, the SRTU can adapt to the diverse and changing needs of the building's occupants, providing a responsive and user-friendly climate control solution.

[0353] In some embodiments of the invention, a Smart Roof Top Unit (SRTU) suitable for roof-mounted applications on commercial buildings or positioned proximally may provide fluid communication with an internal HVAC system. The SRTU and its associated components are constructed to deliver heating, cooling, and ventilation to spaces within the associated building.

[0354] The cooling process within the SRTU involves drawing air from the building's interior into the unit. This air passes through filters, removing particulates, and then flows over cooling coils. Inside these coils, a refrigerant absorbs heat from the air, thereby cooling it. The refrigerant circulates to an external cooling unit, and the cooled air is then distributed back into the building through ductwork.

[0355] Referring now to FIG. 13, an exemplary block diagram of an SRTU system 1300, constructed in accordance with the innovative features discussed throughout the invention. The diagram encapsulates only a few of the primary components and systems that the SRTU system 1300 may include, showcasing its sophisticated structure and functionality. In some embodiments, a number of other components may also be integrated within the SRTU system 1300.

[0356] The Outer Shell 1302 represents a durable exterior of the SRTU 1300, meticulously constructed from a PPR core layer intricately bonded with various protective layers. These layers have been elaborated upon across various embodiments of the invention. With this advanced, composite construction of the Outer Shell 1302, the SRTU 1300 is well-defended against a multitude of environmental challenges, including extreme weather conditions, UV exposure, and physical impacts, thereby providing the longevity and reliability of the unit.

[0357] HVAC Components 1304 constitute the core operational elements of the HVAC system housed within the SRTU 1300, encompassing a broad array of parts facilitating its multi-faceted climate control capabilities. This may include, but is not limited to, precision dampers that meticulously regulate airflow, advanced heating and cooling coils that ensure effective temperature modulation, and strategically placed fans that facilitate optimal air circulation throughout the system. Additionally, the component suite features high-efficiency air filtration units, such as HEPA filters, which are instrumental in purifying the air by trapping fine particulates and maintaining superior air quality. The HVAC components may also integrate an economizer for harnessing external air for cooling under suitable conditions, variable frequency drives for energy-efficient operation of motors, and a refrigeration circuit complete with compressors and expansion valves that play a pivotal role in the thermodynamic processes of the SRTU 1300.

[0358] The Control System 1306 serves as the sophisticated brain of the SRTU 1300, adeptly managing and synthesizing data from an array of sensors to orchestrate the unit's operations. The Control System 1306 enables the maintenance of optimal indoor environmental conditions by dynamically adjusting HVAC components in response to real-time feedback from various sensors. The Control System 1306 may optimize energy use while maintaining comfort, integrating advanced algorithms for predictive maintenance and adaptive response to changing conditions. The Control System 1306 may also be constructed for seamless integration with building management systems (BMS), facilitating remote monitoring, diagnostics, and control, which allows for pre-emptive adjustments and swift resolution of potential issues. Furthermore, it supports user interfaces that enable customized settings and preferences, ensuring that the SRTU 1300 operates not only with precision but also with a high degree of user-friendly interactivity.

[0359] The Controller and / or AI engine 1307 is a component integrated within the Control System 1306. The Controller and / or AI engine 1307 may employ machine learning algorithms to analyze trends and historical data, learning from various operational scenarios to enhance predictive maintenance, optimize energy efficiency, and adapt the SRTU's performance to real-time conditions. For example, the Controller and / or AI engine 1307 can predict periods of high occupancy or temperature fluctuations and adjust the HVAC operations, accordingly, providing optimal comfort and energy usage. Additionally, the Controller and / or AI engine can analyze thermal images captured by IR cameras to detect potential issues such as overheating or component failures, enabling proactive maintenance and reducing downtime.

[0360] Sensors 1308 are the SRTU's sensory organs, encompassing devices such as temperature sensors to monitor heat levels, pressure sensors to maintain optimal airflow, and air quality sensors to detect and respond to the presence of pollutants or particulates. Temperature sensors constantly assess thermal conditions, ensuring the system responds effectively to maintain desired heat levels. Pressure sensors play a vital role in managing airflow dynamics within the HVAC system, maintaining an equilibrium that maximizes efficiency and comfort. Air quality sensors are important in detecting a spectrum of pollutants, from volatile organic compounds to particulate matter, triggering the control system 1306 to initiate appropriate filtration and ventilation responses. Additionally, humidity sensors maintain balanced moisture levels, helpful for both comfort and the prevention of mold and mildew. Together, these sensors form an integrated network that feeds real-time data to the Control System 1306, enabling the SRTU 1300 to adapt its operations to the ever-changing indoor environment, thus preserving a healthy and comfortable atmosphere. Apart from these sensors, there can also be various other sensors integrated to the SRTU 1300.

[0361] Communication Interface 1310 is the gateway for external communication, facilitating remote control, integration with Building Management Systems (BMS), integration with a cloud server, and transmitting alerts for maintenance or repair needs, thus allowing for smart, responsive management of the HVAC system. The seamless remote control allows facility managers or occupants to adjust settings and respond to HVAC needs from afar. Integral to smart building operations, it provides robust integration with Building Management Systems (BMS), providing synchronized and harmonized control across various building systems for enhanced efficiency and comfort. The interface 1310 is also responsible for broadcasting timely maintenance and repair alerts, which are essential for proactive system management and minimizing downtime. Moreover, it supports the transmission of performance data to cloud-based analytics platforms, allowing for the utilization of big data and AI-driven insights for predictive maintenance and energy optimization strategies. In essence, the Communication Interface 1310 is pivotal in transforming the SRTU 1300 into an intelligent, interactive component of the modern, smart building ecosystem.

[0362] Further enhancing its sophisticated design, the SRTU 1300 may also integrate a suite of additional components (not shown) to elevate its operational efficiency and sustainability. An Economizer may ingeniously be incorporated to exploit cooler external air for natural ventilation, substantially curtailing energy expenditure during suitable weather conditions. Photovoltaic Solar Cells may strategically be embedded to capture solar energy, thus supplementing the SRTU's power supply and underscoring its commitment to renewable energy utilization. A Rainwater Harvesting System may be included to collect and repurpose rainwater, aligning with sustainable water resource practices and contributing to the building's eco-friendly initiatives. The system may also include a meticulously constructed Condensate Drainage system that enables effective management and disposal of moisture accumulation, a byproduct of the cooling process, thereby preventing potential water damage and maintaining system integrity. To ensure reliable operation, the SRTU 1300 may be outfitted with versatile Power Supplies that can seamlessly switch between conventional grid electricity and alternative energy sources, providing uninterrupted service and energy resilience. User Interfaces may thoughtfully be developed, featuring intuitive touchscreens or tactile buttons, allowing end-users to effortlessly interact with the system for manual adjustments, personalized settings, and system diagnostics, thereby offering a user-centric approach to HVAC system management.

[0363] In some embodiments of the invention, cooling components that may be housed in the SRTU may include one or more: Compressors that drive the refrigeration cycle. The compressors are operative to compress low-pressure, low-temperature refrigerant gas, turning it into high-pressure, high-temperature gas; Condenser Coils where high-temperature refrigerant gas releases its heat to the outside atmosphere, turning it into high-pressure liquid; Expansion Valves that transform high-pressure liquid refrigerant into a low-pressure, low-temperature liquid; Evaporator Coils positioned to have air from the building pass over Evaporator Coils such that refrigerant inside Evaporator Coils absorbs heat from the air, cooling the air. The refrigerant evaporates, turning back into a low-pressure gas; Blower Fans circulate air from the building over the evaporator coil to form conditioned air and then push the conditioned air back into the building; and Filters that capture dust, pollen, and other particulate matter from the air before the air is cooled or heated. Other components associated with a cooling process may also be present in the SRTU, such as, by way of example, an Economizer which is an optional component that may be included in an SRTU. The Economizer allows for reduced carbon footprint cooling when outside atmospheric temperatures are appropriate for cooling a building interior by drawing in cool outside air to reduce indoor temperatures.

[0364] Heating is accomplished by drawing air from an interior of the building and into the SRTU and passing the air through filters over heating apparatus. The heating apparatus may include one or more electric heating units and gas-fired heating units. Electric heating units include electric resistance devices to warm the air. Gas-fired units provide one or more burners to heat a heat exchanger such that air is warmed as the air passes over and / or through the heat exchanger.

[0365] Heating components that may be housed in the SRTU may include one or more: Heat Exchangers (for gas-fired units) with burners to heat air as the air is circulated over the heat exchanger to warm the air; and Burners (for gas-fired units) to produce a flame that heats the heat exchanger.

[0366] The SRTU may also encompass Controls, such as one or more of: thermostats, sensors, and controller units. The Controls may be operative to regulate the operation of components with the SRTU based upon desired conditions which may include, for example, one or more of; temperatures, airborne particulates, and humidity.

[0367] An SRTU provides significant advantages by reducing roof loading which allows for reduced structural support. Structural support is typically accomplished with a considerable carbon footprint impact, increased costs, and increased time to construct the building. In addition, the SRTU according to the present invention provides for optimum space usage since the SRTU is light enough to be located on a roof of a building with relatively low structural support and the SRTU does not require area interior to the building; or occupy ground space.

[0368] While the SRTU does not require an area interior to the building, the SRTUs may be assembled with multiple disparate modular components. SRTU's may be manufactured with diverse manufacturing processes including, but not limited to, one or more of: extrusion of synthetic material and bonding to a weather-resistant surface coating; three-dimensional (“3D”) printing of one or both of synthetic material and a weather resistant surface coating; and injection molding of synthetic material and bonding to a weather resistant surface coating.

[0369] Referring now to FIGS. 14, 14A, and 14B, an exemplary flow chart 1400 of method steps that may be performed in some embodiments of the present invention are illustrated. The flow chart 1400 outlines exemplary process for controlling a Smart Roof Top Unit (SRTU), integrating advanced technologies such as IR temperature monitoring, AI-based analysis, and predictive maintenance strategies to enhance the efficiency and performance of HVAC systems.

[0370] At step 1402, the process begins by providing a Smart Roof Top Unit (SRTU) that comprises various HVAC or SRTU components essential for efficient climate control within a building. The SRTU may be strategically placed on the roof to optimize space usage within the building while providing effective distribution of conditioned air. The SRTU integrates a range of components constructed to work together seamlessly, providing optimal heating, ventilation, and air conditioning (HVAC) performance.

[0371] The HVAC or SRTU components (housed within the SRTU) may include, but not limited to: heating and cooling coils, evaporator coils, fans, filters, dampers, economizers, compressors, expansion valves, heat exchangers, sensors for temperature, humidity, and pressure, air quality monitors, variable frequency drives, energy recovery ventilators, control panels with AI integration, infrared cameras for thermal monitoring, UV germicidal irradiation systems, high-efficiency particulate air (HEPA) filters, sound-dampening insulation, condensate drainage systems, vibration isolation mounts, photovoltaic solar panels, and integrated communication interfaces for remote monitoring and control.

[0372] The modular design of the SRTU may allow for easy installation, maintenance, and scalability. Each component can be accessed and serviced individually, reducing downtime and maintenance costs. This flexibility also facilitates upgrades and expansions, enabling the SRTU to adapt to changing building requirements and advancements in HVAC technology. By integrating these various HVAC components into a single, cohesive unit, the SRTU provides a comprehensive solution for modern building climate control, combining efficiency, reliability, and case of maintenance.

[0373] At step 1404, the process involves providing at least one infrared (IR) camera to capture thermal images of the SRTU. These IR cameras play an important role in monitoring the thermal performance and health of the SRTU by capturing detailed thermal images. These images are used to analyze the temperature distribution and detect any anomalies that may indicate issues with the unit's operation.

[0374] The placement of IR cameras can vary based on the specific monitoring needs and design of the SRTU. IR cameras may be positioned outside the SRTU, either mounted on adjacent structures or on the rooftop itself, to capture thermal images of the SRTU's surface. The external placement allows the IR cameras to monitor the overall thermal profile of the SRTU, identifying hot or cold spots that may correspond to underlying issues with internal components. By mapping zones, points, or areas on the SRTU's surface to specific internal components, the thermal data from these cameras can help predict the condition of those components. For example, a hot spot on the surface above a cooling coil may indicate a malfunction or inefficiency within that coil.

[0375] AI ternatively, IR cameras can be directly attached to the SRTU, providing a closer and more detailed view of specific areas. These cameras can focus on important components such as compressors, heat exchangers, evaporator coils, heating / cooling coils, and fan motors, capturing thermal images that reveal their operating temperatures. By being attached to the SRTU, the cameras can provide continuous, precise monitoring of these components, ensuring that any temperature anomalies are quickly detected and addressed.

[0376] Additionally, IR cameras may also be placed inside the SRTU itself to directly capture thermal images of the internal components. This internal placement may allow for detailed monitoring of the actual operating temperatures of the components, providing real-time data that facilitates optimal performance. By capturing thermal images from within the SRTU, these cameras can provide insights into the health and efficiency of components that are otherwise difficult to monitor, such as internal sections of heat exchangers or the inner workings of compressors.

[0377] The thermal images captured by both external and internal IR cameras may be processed by the SRTU's control system, which uses the data to predict the condition of the internal components. This predictive capability is important for proactive maintenance and operational optimization, allowing the SRTU to maintain high efficiency and reliability by addressing issues before they lead to significant problems. By strategically placing IR cameras both inside and outside the SRTU, a comprehensive thermal profile can be obtained, providing thorough monitoring and precise control of the unit's performance.

[0378] At step 1406, the process involves providing a control system comprising a Controller and / or AI engine for processing the thermal images captured by the IR cameras. The control system is a pivotal component of the SRTU, as it leverages advanced computational capabilities to analyze the thermal data and derive actionable insights that optimize the unit's performance.

[0379] The control system can be integrated directly into the SRTU, allowing for on-site processing of thermal images. Such an integration may ensure that the thermal data is processed in real-time, enabling immediate responses to any detected anomalies or inefficiencies. The Controller and / or AI engine within the control system uses machine learning algorithms to interpret the thermal images, identifying patterns and trends that indicate the operating condition of various components. By continuously analyzing the thermal data, the Controller and / or AI engine can predict potential issues, recommend maintenance actions, and adjust operational parameters to maintain optimal efficiency.

[0380] AI ternatively, the control system may also reside on a cloud server, where the thermal images captured by the IR cameras are transmitted for processing. The cloud-based approach may offer several advantages, including the ability to leverage more powerful computational resources and access to a broader dataset for more accurate analysis. By sending thermal images to the cloud server, the SRTU benefits from advanced AI processing without the need for extensive on-site hardware. The cloud server processes the thermal images, runs predictive analytics, and sends back control commands or maintenance recommendations to the SRTU.

[0381] Whether integrated into the SRTU or hosted on a cloud server, the Controller and / or AI engine processes the thermal images to assess the temperature distribution across the SRTU's components. It maps the thermal patterns against historical data and operational benchmarks to detect deviations that may indicate issues such as overheating, frost buildup, or component failures. By continuously learning from the data, the Controller and / or AI engine improves its predictive capabilities over time, ensuring that the SRTU operates efficiently and reliably.

[0382] At step 1408, the process involves capturing thermal images of the SRTU using the at least one IR camera. The IR camera operates by detecting infrared radiation emitted by the SRTU's surfaces and components. Since different materials and components emit varying levels of infrared radiation based on their temperatures, the camera produces a thermal image where each pixel corresponds to a specific temperature value. These thermal images provide a visual representation of heat patterns, enabling the identification of hotspots, cold spots, and other thermal anomalies.

[0383] The captured thermal images offer several insights into the SRTU's operation. For example, areas with abnormally high temperatures may indicate overheating components, while areas with unexpected cold spots may signify inefficient cooling or frost buildup. By capturing these images continuously, the IR camera allows for constant monitoring of the SRTU's thermal state, ensuring that any deviations from normal operating conditions are quickly detected.

[0384] At step 1410, the process involves converting the captured thermal images into digital value patterns. Each thermal image consists of a multitude of pixels, with each pixel representing a specific temperature value based on the infrared radiation detected from the SRTU's components.

[0385] The conversion process begins with the thermal images captured by the IR cameras. These images are initially in a visual format, where different colors or shades represent varying temperature levels. To transform these images into a format suitable for detailed analysis, the visual data may be converted into numerical data. Each pixel in the thermal image may be assigned a corresponding temperature value, creating a digital matrix of temperature readings.

[0386] This digital matrix, or digital value pattern, may provide a precise representation of the temperature distribution across the SRTU. By converting the thermal images into numerical data, the control system (or the Controller and / or AI engine) can perform more accurate and complex analyses. The digital value patterns enable the system to detect even subtle temperature variations and trends that may not be easily visible in the raw thermal images.

[0387] At step 1412, the process involves analyzing the digital value patterns using a Controller and / or AI engine to assess temperature distribution and identify anomalies. The Controller and / or AI engine receives the thermal images and / or digital value patterns, which represent the precise temperature readings of the SRTU's components. These patterns are essentially a matrix of numerical data that maps the thermal state of the unit in real-time. The Controller and / or AI engine employs sophisticated machine learning algorithms to analyze this data, searching for patterns, trends, and deviations from normal operating conditions.

[0388] The primary goal of the AI analysis is to assess the temperature distribution across the SRTU. The Controller and / or AI engine creates a comprehensive thermal profile of the unit, identifying the typical temperature ranges for different components under various operating conditions. By establishing these baseline profiles, the Controller and / or AI engine can effectively monitor for any deviations that may indicate potential issues.

[0389] One of the key functions of the Controller and / or AI engine is to identify anomalies within the temperature distribution. These anomalies can manifest as hotspots, cold spots, or unexpected temperature fluctuations. For example, a hotspot on the surface of the SRTU may indicate an overheating component, which may lead to a failure if not addressed promptly. Conversely, a cold spot may suggest inefficient cooling or frost buildup on a coil, which can compromise the unit's performance.

[0390] The Controller and / or AI engine uses historical data, real-time monitoring, and predictive analytics to detect these anomalies. It continuously compares the current thermal data against historical trends and predefined thresholds. When an anomaly is detected, the Controller and / or AI engine can trigger alerts and / or recommend corrective actions. For example, if the Controller and / or AI engine identifies a component that is consistently overheating, it may suggest a maintenance check or an adjustment to the operating parameters to prevent failure.

[0391] At step 1414, the process involves mapping the digital value patterns against variable trends, including defrost cycles, power use, equipment status, and operational efficiency. The Controller and / or AI engine begins by correlating the digital value patterns derived from the thermal images with historical and real-time operational data. This mapping process may involve creating a multidimensional dataset where temperature readings are analyzed for variables such as defrost cycles, power consumption, and equipment performance metrics.

[0392] By mapping thermal data against defrost cycle trends, the Controller and / or AI engine can optimize the timing and duration of defrost operations. For example, if the thermal data indicates excessive frost buildup on the evaporator coils, the AI can trigger a defrost cycle. Conversely, by analyzing patterns over time, the AI can adjust defrost schedules to prevent additional cycles, thereby saving energy and reducing wear on the system.

[0393] The Controller and / or AI engine may also analyze how temperature variations correlate with power consumption, identifying opportunities for energy savings. For example, if certain components are consistently operating at higher temperatures, the AI may suggest or perform adjustments to reduce power usage without compromising performance. This analysis helps in fine-tuning the SRTU's operations to achieve optimal energy efficiency.

[0394] The Controller and / or AI engine may also detect early signs of potential failures by identifying anomalies in temperature trends that precede equipment malfunctions. For example, a gradual increase in temperature in a specific component may indicate wear and tear or impending failure. By recognizing these patterns early, the AI can prompt preventive maintenance actions, reducing the likelihood of unexpected breakdowns and costly repairs.

[0395] The Controller and / or AI engine also evaluates how effectively the SRTU maintains desired temperature levels while balancing energy use and system health. This may include optimizing airflow, adjusting fan speeds, and modulating heating and cooling output based on real-time conditions. By mapping thermal data against efficiency metrics, the AI enables the SRTU to operate at peak performance with minimal resource consumption.

[0396] At step 1416, the process involves initiating defrost cycles based on the analysis of thermal images and frost accumulation. The Controller and / or AI engine continuously monitors the thermal images captured by the IR cameras to assess the temperature distribution across the SRTU's components. These thermal images provide detailed visual data that helps identify areas where frost is accumulating on the evaporator coils. Frost buildup can significantly impair the heat exchange efficiency of the coils, leading to reduced cooling performance and increased energy consumption.

[0397] When the Controller and / or AI engine detects frost accumulation through the thermal images or their digital value patterns, it analyzes the extent and distribution of the frost. The Controller and / or AI engine may also use this data to determine the optimal timing and duration for initiating a defrost cycle. The goal is to remove the frost efficiently without unnecessarily disrupting the cooling process or wasting energy.

[0398] The defrost cycle may be initiated by the Controller and / or AI engine when specific thresholds for frost accumulation are met. These thresholds may be set automatically based on historical data and real-time monitoring to ensure that defrosting occurs. The Controller and / or AI engine may also consider factors such as ambient temperature, humidity levels, and the operational load on the SRTU to fine-tune the defrost initiation process.

[0399] Once the defrost cycle is triggered, the SRTU system temporarily switches from cooling mode to defrost mode. The SRTU may employ various defrosting methods, such as reversing the refrigerant flow, using electric heaters, indirect burners, louvers, jets, multiple fans, or circulating warm air over the coils. The choice of method depends on the specific design and requirements of the SRTU.

[0400] Throughout the defrost cycle, the Controller and / or AI engine continues to monitor the thermal images to track the progress of frost removal. It enables the coils to be adequately defrosted and ready to resume efficient cooling operation. By dynamically adjusting the defrost process based on real-time data, the Controller and / or AI engine minimizes the energy consumption and time required for defrosting. In addition to optimizing the defrost cycles, the Controller and / or AI engine can also schedule preventive defrost operations based on historical patterns of frost accumulation.

[0401] At step 1418, the process involves optimizing power use and operational efficiency by adjusting HVAC components based on AI analysis. The Controller and / or AI engine continuously analyzes the thermal images and other operational data collected from the SRTU. By leveraging machine learning algorithms, the AI identifies patterns and trends that indicate how the system is performing under various conditions.

[0402] One of the primary goals of the Controller and / or AI engine is to reduce energy consumption without compromising comfort and efficiency. The AI achieves this by monitoring the power usage of different components, such as compressors, fans, and heating / cooling coils, and identifying opportunities to reduce energy consumption. For example, the AI may detect that certain components are operating at higher power to maintain the desired temperature. In such cases, the AI can adjust the settings to lower the power usage, thus conserving energy.

[0403] Additionally, the Controller and / or AI engine can optimize the operational efficiency of the SRTU by dynamically adjusting the airflow, temperature setpoints, and humidity levels. For example, if the AI detects that certain areas within the building require more cooling while others need less, it can modulate the airflow to direct more conditioned air to the hotter zones and reduce it in the cooler zones.

[0404] At step 1420, the SRTU system receives commands for additional cooling or heating requirements. These commands can originate from various sources, including building management systems (BMS), facility managers, or even occupants through user interfaces or wirelessly. The BMS may issue commands based on pre-set schedules, detected occupancy levels, or real-time environmental conditions. For example, if a conference room is scheduled to be used in an hour, the BMS may request additional cooling to ensure a comfortable environment. Similarly, occupants may manually request changes via a thermostat or a mobile app to suit their immediate comfort needs.

[0405] Upon receiving these commands, the system (or Controller and / or AI engine) may utilize predictive analytics to anticipate the temperature changes required to meet the new demands. This may involve creating detailed temperature maps based on the expected load. The Controller and / or AI engine uses historical data, current conditions, and the specifics of the request to generate these predictions. For example, if the system anticipates a significant increase in occupancy in a particular zone, it will predict a corresponding rise in temperature and humidity, prompting pre-emptive cooling adjustments to maintain comfort.

[0406] Step 1422 involves the continuous monitoring of ambient conditions within the building spaces to be cooled or heated. This monitoring may be conducted using a network of sensors and / or cameras strategically placed throughout the building. The sensors may measure various parameters, including temperature, humidity, occupancy, and airflow.

[0407] This comprehensive monitoring allows the system to maintain an accurate and dynamic understanding of the building's environmental conditions. The data collected by these sensors or cameras is continuously fed into the control system, where the Controller and / or AI engine analyzes it to make informed adjustments to the HVAC operations, providing optimal comfort and efficiency.

[0408] At step 1424, the system assesses the status of HVAC equipment and occupancy trends using infrared imaging, camera feeds and various sensors. Infrared cameras installed in and around the SRTU capture thermal images of the unit's components, providing detailed insights into their operating conditions. These images help identify any anomalies, such as overheating or underperformance, which may indicate potential failures or inefficiencies.

[0409] Additionally, occupancy sensors or cameras throughout the building detect the presence and movement of people in different zones. The sensors may include motion detectors, CO2 sensors, and even thermal cameras that identify human heat signatures. By analyzing this data, the Controller and / or AI engine can determine which areas of the building are currently occupied and may also predict future occupancy patterns.

[0410] Combining data from infrared imaging and occupancy sensors allows the system to adjust HVAC operations proactively. For example, if an infrared camera detects that a compressor is running hotter than usual, the system can pre-emptively schedule maintenance or adjust its operation to prevent failure. Similarly, if occupancy sensors indicate that a particular area will soon be filled with people, the system can adjust cooling or heating to ensure comfort upon their arrival.

[0411] Step 1426 involves adjusting HVAC operations based on predicted demand, taking into account various factors such as the time of day, day of the week, seasonality, geographic location, and historical data. The Controller and / or AI engine uses these variables to create predictive models that anticipate the building's HVAC needs with high accuracy.

[0412] For example, the system may recognize that mornings typically require increased heating during winter due to lower overnight temperatures, while afternoons may need more cooling as the building's occupancy and external temperatures rise. On weekdays, the demand pattern may differ significantly from weekends, influenced by typical office hours and occupancy levels.

[0413] Seasonality may also play a role in determining the HVAC requirements. The system may adjust its operations based on seasonal variations, such as higher cooling demands in summer and increased heating needs in winter. Geographic location may also influence these adjustments, as buildings in different climates experience varying external temperature ranges and humidity levels.

[0414] Historical data may provide a valuable reference for understanding recurring patterns and anomalies. By analyzing past performance and environmental conditions, the Controller and / or AI engine fine-tunes its predictions and adjustments, providing optimal efficiency and comfort. For example, if historical data shows that a particular area of the building tends to overheat in the afternoon during summer months, the system can pre-emptively increase cooling in that zone.

[0415] At step 1428, the thermal images captured by the IR cameras installed on the SRTU unit may be transmitted to a cloud server. This centralized storage facilitates the cumulative analysis of thermal data from multiple SRTU units. By uploading these images to the cloud, the system can leverage advanced computational resources and AI algorithms that are more powerful than those available on individual units. The cloud-based Controller and / or AI engine may aggregate and analyze the thermal images, identifying common patterns, trends, and anomalies across different units. This collective analysis enhances the predictive accuracy and reliability of the system, as it benefits from a larger dataset and more diverse operational scenarios. The insights gained from this cumulative analysis are used to optimize the performance of all connected SRTU units, providing a scalable and highly efficient monitoring solution.

[0416] At step 1430, the Controller and / or AI engine continuously determines the optimum defrost state for the SRTU based on several predefined criteria. These criteria may include cooling and heating power requirements, energy efficiency targets, and system responsiveness. The Controller and / or AI engine analyzes real-time thermal data to assess frost accumulation on components such as evaporator coils. It then calculates the ideal timing and duration for defrost cycles to ensure that the SRTU maintains its efficiency and performance. By optimizing the defrost state, the system minimizes energy consumption, reduces wear and tear on components, and enables the unit to quickly return to its optimal operating condition. The continuous nature of this assessment allows for real-time adjustments and proactive maintenance, preventing frost-related performance degradation.

[0417] At step 1432, the control parameters of the SRTU and / or the control system may be updated based on real-time data and AI analysis. The Controller and / or AI engine continuously monitors the thermal images, ambient conditions, and operational data from the SRTU. Using this information, it dynamically adjusts the control settings to maintain optimal performance. For example, if the AI detects a drop in cooling efficiency, it may increase airflow or adjust the refrigerant flow rate. Similarly, if energy consumption is higher than expected, the AI may fine-tune the system to operate more efficiently.

[0418] At step 1434, the Controller and / or AI engine predicts HVAC equipment failures, power usage, heating and cooling requirements, and maintenance schedules. By analyzing the digital value patterns from thermal images and other operational data (from SRTU sensors or from BMS), the AI can identify early signs of potential failures, such as abnormal temperature rises or inconsistent performance. It may also forecast power usage trends based on historical data and real-time monitoring, allowing for more accurate energy budgeting. Additionally, the AI also predicts future heating and cooling demands by considering factors such as occupancy patterns, weather forecasts, and historical usage. This predictive capability enables the system to schedule maintenance proactively, reducing downtime and preventing unexpected breakdowns. By forecasting these parameters, the AI enables the SRTU to operate smoothly and efficiently.

[0419] At step 1436, the SRTU and its HVAC components may be controlled based on the predictions and analyses performed by the Controller and / or AI engine. The AI-driven control system adjusts the operation of key components such as fans, filters, coils, compressors, and dampers to optimize performance. For example, if the AI predicts a peak cooling demand in the afternoon, it may pre-cool the building in the morning to reduce the load during peak hours. Similarly, if an equipment failure is predicted, the AI can adjust the system to prevent overloading the affected component. These real-time adjustments ensure that the SRTU maintains optimal indoor conditions while operating efficiently and reliably.

[0420] At step 1438, the Controller and / or AI engine may suggest modifications to the SRTU to improve efficiency and performance. Based on its continuous analysis of thermal images, operational data, and performance trends, the AI identifies opportunities for enhancements. These suggestions may include hardware upgrades, such as installing more efficient fans or adding insulation to reduce thermal losses. The AI may also recommend software updates to optimize control algorithms or introduce new features. Additionally, the AI can suggest changes to maintenance routines or operational strategies to prolong the lifespan of components and improve overall system performance.

[0421] In some embodiments of the invention, a method for controlling an HVAC system incorporating a Smart Roof Top Unit (SRTU) is developed, focusing on the utilization of advanced sensor technology and environmental condition monitoring to optimize system performance and efficiency.

[0422] The method comprises integration of a diverse array of sensors within the SRTU. These sensors are strategically placed to continuously monitor various environmental parameters including indoor and outdoor temperatures, humidity levels, air quality, and pressure. The purpose of this extensive sensor network is to gather detailed real-time data about the environmental conditions both inside and outside the building. This data collection is vital for ensuring that the HVAC system operates in a manner that is both responsive and efficient.

[0423] Temperature sensors play a key role in this system, providing accurate readings of the indoor environment as well as external conditions. These readings enable the SRTU to adjust its heating or cooling output to match the desired indoor temperature set by the occupants, thereby maintaining a comfortable indoor climate.

[0424] Humidity sensors add another layer of environmental monitoring, assessing the moisture content in the air. Maintaining optimal humidity levels is essential not only for comfort but also for the health of building occupants and the integrity of the building structure.

[0425] Air quality sensors monitor the presence of pollutants and particulates in the indoor air. These sensors ensure that the air quality remains within safe and comfortable levels, triggering the HVAC system to increase ventilation or filtration.

[0426] Pressure sensors within the SRTU monitor the air pressure in different parts of the HVAC system. Proper air pressure balance is important for efficient air distribution and for preventing undue stress on the system components. The SRTU may further be equipped with CO2 sensors, ultraviolet (UV) light sensors, and wind speed and direction sensors.

[0427] Additionally, this method encompasses remote monitoring capabilities. The sensor data can be transmitted to a centralized control system, which can be accessed by facility managers or maintenance personnel remotely. This feature allows for real-time adjustments to the system settings from off-site locations, enhancing the flexibility and responsiveness of the HVAC management.

[0428] Furthermore, the method may include predictive maintenance algorithms that analyze sensor data over time to identify potential issues before they become significant problems. With this proactive approach to maintenance, the SRTU operates reliably and efficiently, reducing downtime and extending the lifespan of the system.

[0429] Such an SRTU control method represents a sophisticated approach to HVAC system management. By leveraging advanced sensor technology and remote monitoring capabilities, the system not only provides a comfortable and healthy indoor environment but also operates with enhanced efficiency and reliability.

[0430] Referring now to FIG. 15, an exemplary block diagram of an LRTU 1500, with innovative features included in the present invention. FIG. 15 illustrates a few of the primary components and systems that the LRTU 1500 may include, showcasing the LRTUs 1500 sophisticated structure and functionality. In some embodiments, a number of other components may also be integrated within the LRTU system 1500.

[0431] The Outer Shell 1502 represents a durable exterior of the LRTU 1500, including a PPR core layer intricately bonded with various protective layers. These layers have been elaborated upon across various embodiments of the invention. This advanced, composite construction of the Outer Shell 1502 ensures the LRTU 1500 is well-defended against a multitude of environmental challenges, including extreme weather conditions, UV exposure, and physical impacts, thereby providing the longevity and reliability of the unit.

[0432] HVAC Components 1504 constitute the core operational elements of the HVAC system housed within the LRTU 1500, encompassing a broad array of parts useful for its multi-faceted climate control capabilities. This may include, but is not limited to, precision dampers that meticulously regulate airflow, advanced heating and cooling coils that ensure effective temperature modulation, and strategically placed fans that facilitate optimal air circulation throughout the system. Additionally, the component suite features high-efficiency air filtration units, such as HEPA filters, which are instrumental in purifying the air by trapping fine particulates and maintaining superior air quality. The HVAC components may also integrate an economizer for harnessing external air for cooling under suitable conditions, variable frequency drives for energy-efficient operation of motors, and a refrigeration circuit complete with compressors and expansion valves that play a pivotal role in the thermodynamic processes of the LRTU 1500.

[0433] The Control System 1506 serves as the sophisticated brain of the LRTU 1500, adeptly managing and synthesizing data from an array of sensors to orchestrate the unit's operations. The Control System 1506 ensures the maintenance of optimal indoor environmental conditions by dynamically adjusting HVAC components in response to real-time feedback from various sensors. The Control System 1506 may optimize energy use while maintaining comfort, integrating advanced algorithms for predictive maintenance and adaptive response to changing conditions. The Control System 1506 may also be seamless integrated with building management systems (BMS), facilitating remote monitoring, diagnostics, and control, which allows for pre-emptive adjustments and swift resolution of potential issues. Furthermore, it supports user interfaces that enable customized settings and preferences, ensuring that the LRTU 1500 operates not only with precision but also with a high degree of user-friendly interactivity.

[0434] In some embodiments, the Control System 1506 of the LRTU may comprise an Artificial Intelligence (AI) engine 1506A operative to control performance of the HVAC system by intelligently controlling heating, cooling, and ventilation based on real-time and predicted environmental and operational requirements.

[0435] The AI engine 1506A within the Control System 1506 may be equipped with advanced machine learning algorithms capable of processing vast amounts of data from various sensors 1508 embedded throughout the HVAC system. These sensors 1508 may collect data on temperature, humidity, air quality, occupancy levels, and external weather conditions. By analyzing this data, the AI engine 1506A is operative to generate logical commands comprising one or both of electrical and digital transmissions to adjust the heating, cooling, and airflow settings in real-time, controlling indoor climate conditions and increasing energy efficiency.

[0436] In some embodiments, the AI engine may learn from historical data and identify trends in system performance and environmental conditions. For instance, the AI can learn typical occupancy patterns within a building and adjust the HVAC operations to ramp up heating or cooling shortly before occupants arrive, or scale back during off-hours or when the building is unoccupied. This predictive capability may allow for more proactive management of the HVAC system, reducing energy waste and improving the overall comfort levels for building occupants.

[0437] Furthermore, the AI engine may be programmed to continuously monitor the performance of the HVAC components, such as the efficiency of the heating coils, the operational health of the cooling system, and the integrity of the ventilation pathways. By detecting anomalies or deviations from expected performance benchmarks, the AI engine can trigger maintenance alerts, recommending preventive maintenance or urgent repairs, thereby avoiding costly downtimes and extending the lifespan of the equipment.

[0438] The Control System 1506, through its AI engine, may also interface with other building management systems (BMS) to ensure holistic management of the building's utilities and services. This integration may allow the AI engine to consider additional factors such as energy consumption patterns, security systems, and even external data feeds like weather forecasting services, to dynamically adjust the HVAC operations, further enhancing the building's efficiency and the comfort of its occupants.

[0439] In addition to operational control, the AI engine may incorporate user-friendly interfaces that allow building managers and maintenance personnel to interact with the system. Through an interactive user interface, a user may view detailed reports, including, for example, one or more of: system performance, energy usage, and receive real-time notifications on any issues or adjustments made by the AI. In some embodiments, a user may interact with the interactive user interface to manually override AI decisions, providing flexibility and human oversight to the automated system.

[0440] Imaging devices and / or Sensors 1508 encompassing devices such as infrared imaging capture devices, or other devices capable of generating a quantification of various temperatures of one or more items within a designated area, such as a field of view of an image capture device, and / or temperature sensors to monitor heat levels, pressure sensors to maintain optimal airflow, and air quality sensors to detect and respond to the presence of pollutants or particulates. Temperature sensors constantly assess thermal conditions, ensuring the system responds effectively to maintain desired heat levels. Pressure sensors play a vital role in managing airflow dynamics within the HVAC system, maintaining an equilibrium that maximizes efficiency and comfort. Air quality sensors are crucial in detecting a spectrum of pollutants, from volatile organic compounds to particulate matter, triggering the Control System 1506 to initiate appropriate filtration and ventilation responses.

[0441] Additionally, humidity sensors maintain balanced moisture levels, facilitating both comfort and the prevention of mold and mildew. Together, these sensors form an integrated network that feeds real-time data to the Control System 1506, enabling the LRTU 1500 to adapt its operations to the ever-changing indoor environment, thus preserving a healthy and comfortable atmosphere. Apart from these sensors, there can also be various other sensors integrated to the LRTU 1500.

[0442] Communication Interface 1510 is the gateway for external communication, facilitating remote control, integration with Building Management Systems (BMS), integration with a cloud server, and transmitting alerts for maintenance or repair needs, thus allowing for smart, responsive management of the HVAC system. The seamless remote control allows facility managers or occupants to adjust settings and respond to HVAC needs from afar. Integral to smart building operations, it provides robust integration with Building Management Systems (BMS), providing synchronized and harmonized control across various building systems for enhanced efficiency and comfort.

[0443] The Interface 1510 may also be responsible for broadcasting timely maintenance and repair alerts, which are essential for proactive system management and minimizing downtime. Moreover, it supports the transmission of performance data to cloud-based analytics platforms, allowing for the utilization of big data and AI-driven insights for predictive maintenance and energy optimization strategies. In essence, the Communication Interface 1510 is pivotal in transforming the LRTU 1500 into an intelligent, interactive component of the modern, smart building ecosystem.

[0444] Further, the LRTU 1500 may integrate a suite of additional components (not shown) to elevate its operational efficiency and sustainability. An Economizer may ingeniously be incorporated to exploit cooler external air for natural ventilation, substantially curtailing energy expenditure during suitable weather conditions. Photovoltaic Solar Cells may strategically be embedded to capture solar energy, thus supplementing the LRTU's power supply and underscoring its commitment to renewable energy utilization. A Rainwater Harvesting System may be included to collect and repurpose rainwater, aligning with sustainable water resource practices and contributing to the building's eco-friendly initiatives. The system may also include a Condensate Drainage system that ensures effective management and disposal of moisture accumulation, a byproduct of the cooling process, thereby preventing potential water damage and maintaining system integrity.

[0445] To ensure reliable operation, the LRTU 1500 may be outfitted with versatile Power Supplies that can seamlessly switch between conventional grid electricity and alternative energy sources, providing uninterrupted service and energy resilience. User Interfaces may thoughtfully be developed, featuring intuitive touchscreens or tactile buttons, allowing end-users to effortlessly interact with the system for manual adjustments, personalized settings, and system diagnostics, thereby offering a user-centric approach to HVAC system management.

[0446] Referring now to FIG. 16, an automated controller is illustrated that may be used to implement various aspects of the present invention in various embodiments, and for various aspects of the present invention. Controller 1600 may be included in one or more of: a wireless tablet or handheld smart device, a server, an integrated circuit incorporated into a Node, appliance, equipment item, machinery, or other automation. The controller 1600 includes a processor unit 1602, such as one or more semiconductor-based processors, coupled to a communication device 1601 configured to communicate via a communication network (not shown in FIG. 16). The communication device 1601 may be used to communicate, for example, with one or more online devices, such as a smart device, a Node, personal computer, laptop, or a handheld device.

[0447] The processor unit 1602 is also in communication with a storage device 1603. The storage device 1603 may comprise any appropriate information storage device, including combinations of digital storage devices (e.g., an SSD), optical storage devices, and / or semiconductor memory devices such as Random Access Memory (RAM) devices and Read Only Memory (ROM) devices.

[0448] The storage device 1603 can store a software program 1604 with executable logic for controlling the processor unit 1602. The processor unit 1602 performs instructions of the software program 1604, and thereby operates in accordance with the present invention. The processor unit 1602 may also cause the communication device 1601 to transmit information, including, in some instances, timing transmissions, digital data and control commands to operate apparatus to implement the processes described above. The storage device 1603 can additionally store related data in a database 1605 and database 1606, as needed.

[0449] Referring now to FIG. 17, in some embodiments, a RTU according to the present invention may be based upon Magnetocaloric Technology (sometimes referred to herein as “MGT”). MGT utilizes a temperature change in certain materials when exposed to a magnetic field, and be included in the present invention as an alternative and / or a supplement to traditional vapor-compression cooling systems. Unlike conventional systems that rely on compressors, refrigerants, and expansion valves, magnetocaloric RTUs use solid-state magnetocaloric materials and a moving magnetic field to drive heat exchange, resulting in a sealed system with no chemical refrigerants.

[0450] Use of a MGT based RTU may significantly reduce maintenance requirements by eliminating refrigerant leakage issues and compressor failures, which are among the most common service calls in traditional units.

[0451] Some MGT designs using optimized rare earth materials and permanent magnet arrays include compact footprints. The compact footprint allows for an RTU that is comparable in weight, and in some embodiments less weight as compared to a standard RTU system.

[0452] Some embodiments additionally include MGT RTU systems with improved weather resistance as compared to traditional RTUs since magnetocaloric systems can be more fully enclosed and sealed from environmental exposure. Longevity is another benefit of MGT RTUs. The MGT RTU includes fewer moving parts and no high-pressure refrigerant cycles. Magnetocaloric RTUs may offer extended operational life and reduced degradation over time. Additionally, their operation is quieter and potentially more energy-efficient at partial loads.

[0453] MGTs may be favorable for use in sustainability-focused buildings where mechanical simplicity, energy efficiency, and environmental safety are paramount based upon MGT in rooftop units (RTUs) presenting lower environmental impact compared to conventional RTUs that rely on vapor-compression cycles and hydrofluorocarbon (HFC) refrigerants. Traditional RTUs commonly may use synthetic refrigerants like R-410A or R-134a, which are viewed as greenhouse gases with high global warming potentials (GWPs). In contrast, magnetocaloric RTUs operate without any refrigerants, using solid-state magnetocaloric materials and magnetic fields to achieve cooling, thereby eliminating the risk of refrigerant emissions entirely. Additionally, the absence of compressors and complex piping systems may reduce mechanical wear, and the need for frequent servicing.

[0454] As illustrated in FIG. 17, a RTU that is based upon MGT components (MGT RTU 1700). The MGT RTU 1700 components may include a magnetocaloric cooling module 1701 which acts as the prevailing temperature regulating core subsystem. Cooling may be generated on demand via the magnetocaloric effect via the magnetocaloric cooling module 1701. The magnetocaloric cooling module 1701 may replace an / or supplement conventional refrigerant-based compressors by using solid-state materials that respond thermally to changes in magnetic fields. The magnetocaloric cooling module 1701 houses the magnetocaloric material stack and associated mechanical and thermal components required to generate and transfer heat through cyclical magnetization and demagnetization.

[0455] A heat exchanger 1711 may include a Hot Side 1702 and a Cold Side 1703. The Hot Side 1703 is functional to remove heat from the magnetocaloric material after it has been magnetized and has absorbed thermal energy. Positioned at the exhaust side of the heat exchanger 1711. The Hot Side 1702 transfers rejected heat to an outside environment. The Hot Side 1702 functions similarly to a condenser in a traditional HVAC system but operates with solid-state heat and mass flow.

[0456] The cold-side 1702 acts like an evaporator in conventional systems. It absorbs thermal energy from an indoor air stream or return air. As magnetocaloric material in the Magnetocaloric Cooling Module 1701 cools during demagnetization, the cold-side 1702 draws heat from the airstream, effectively lowering its temperature before it is re-circulated through the building.

[0457] The Magnetocaloric Cooling Module 1701 may include an array of magnetocaloric materials (such as gadolinium-based alloys or lanthanides) that physically change temperature when exposed to a magnetic field. The Magnetocaloric Cooling Module 1701 may include a stack of such magnetocaloric materials that are cyclically magnetized and demagnetized to alternately absorb and reject heat The Magnetocaloric Cooling Module 1701 may be operational as a thermodynamic engine of the cooling module.

[0458] A control and sensor system 1709 serves as a digital brain of the MGT RTU 1700, managing operation parameters such as timing, magnetic field modulation, airflow rates, and temperature control. The control and sensor system 1709 if operational to integrate sensor inputs and command outputs for example to: optimize performance, ensure safe operation, and / or communicate with external systems like building automation systems (BAS).

[0459] Thermal sensors 1707 are operational to provide functions such as, one or more of: measure air and component temperatures at various points within the RTU. The thermal sensors 1707 are capable of providing real-time feedback (e.g., no artificial delay) to the control sensor system 1709 for maintaining setpoints, preventing overheating or overcooling, and adjusting fan speeds and magnetization cycles accordingly.

[0460] Additional sensors, such as, for example pressure and / or flow sensors 1708 are operational to perform useful functions, such as, one or more of: monitor airflow rates, static pressure, and differential pressure across filters and heat exchangers. They are essential for ensuring efficient operation, identifying clogs or performance degradation, and enabling predictive maintenance or automated alerts.

[0461] An outdoor air intake / exhaust component 1705 may be operational to allow the MGT RTU 1700 to exchange air with an external environment. The outdoor air intake / exhaust component 1705 is functional to draw in fresh outdoor air for ventilation and / or expels heat-laden air processed by the hot-side heat exchanger. It may include dampers or economizers for energy-efficient operation.

[0462] A supply fan and blower 1704 provides a mechanical force necessary to circulate air through the MGT RTU 1700 and a building serviced by the MGT RTU 1700. The supply fan and blower 1704 moves cooled air from the cold-side heat exchanger into a supply duct, overcoming resistance and maintaining desired airflow rates throughout the building.

[0463] A duct interface 1706 provides for mechanical connections between the duct interface 1706 and a building's HVAC duct system. The duct interface 1706 enables the integration of the MGT RTU 1700 airflow with interior conditioned space, typically through metal flange or curb-mounted connections. For example, duct interface 1706 may include an outlet point where cooled air exits the RTU and enters the building's supply ductwork. It connects to downstream registers or diffusers and is responsible for delivering conditioned air to interior spaces. A return duct interface may include an inlet where warm air from the building re-enters the RTU for cooling. It may connect the building's return air path to the intake of the air handling portion of the unit.

[0464] The Return Air Intake 1710 gathers used indoor air (return air) and channels it back into the MGT RTU 1700 for re-cooling. The Return Air Intake 1710 may contain filters or dampers and plays a critical role in maintaining airflow balance and system efficiency. The “ALR” label likely stands for “Air-Return,” denoting this point as the return air pathway into the unit.

[0465] Pressure and Flow Sensors 1708 may include an integrated set of pressure and airflow monitoring devices within the MGT RTU 1700. The Pressure and Flow Sensors 1708 play the role of ensuring that the MGT RTU 1700 operates within optimal airflow and static pressure ranges. Pressure and Flow Sensors 1708 detect real-time changes in air velocity, volumetric flow rate, and differential pressure across filters, coils, and duct sections. This data is sent to the control system to regulate fan speed, detect airflow blockages, and maintain balanced operation. In magnetocaloric systems, precise thermal exchange may be important to efficiency, therefore accurate flow monitoring facilitates that heat exchangers function correctly and that the MGT RTU 1700 is capable of adapting to varying load conditions. Additionally, Pressure and Flow Sensors 1708 may be functional to trigger alerts for preventative maintenance when abnormal pressure drops or inconsistent flow patterns are detected, helping to extend system life and maintain performance.

[0466] In some embodiments, a Magnetocaloric based RTU will also operate more quietly and potentially more efficient at part-load conditions.

[0467] In some embodiments, a MGT RTU will include sealed systems so that end-of-life disposal is simpler and safer, avoiding the hazardous recovery of refrigerants.

[0468] In another aspect, a RTU based upon MGT may offer significant advantages in installation and maintenance simplicity compared to conventional RTUs, particularly in light of a projected decline in the availability of highly skilled HVAC technicians. Traditional RTUs rely on complex vapor-compression systems that require precise handling of refrigerants, specialized brazing and vacuuming procedures, pressure testing, and compliance with EPA regulations related to refrigerant recovery and charging. These tasks demand extensive training and certification, and mistakes can lead to system inefficiency, refrigerant leaks, or even equipment failure. In contrast, magnetocaloric RTUs are closed-loop, solid-state systems with no refrigerants and fewer mechanical components such as compressors, expansion valves, or accumulators.

[0469] Embodiments include installation of magnetocaloric units using simple modular equipment with steps such as: position, connect to power, interface with ductwork and controls, and commission, thereby requiring fewer specialized skills.

[0470] From a maintenance perspective, the absence of moving parts like belts, pulleys, and refrigerant circuits drastically reduces the number of failure points. This aligns well with a less skilled or semi-skilled future workforce, as tasks will likely be limited to basic diagnostics, sensor replacement, or firmware updates rather than in-depth refrigeration cycle troubleshooting. Moreover, magnetocaloric systems may offer greater reliability and less routine service, which reduces the dependency on frequent technician intervention. As the HVAC industry adapts to labor shortages and skill gaps, magnetocaloric RTUs could represent a more resilient and workforce-friendly solution, especially in large-scale commercial deployments where case of maintenance and system uptime are critical.

[0471] Installing a magnetocaloric rooftop unit (RTU) follows many of the physical steps used in traditional RTU installations but is simplified due to the absence of refrigerant systems and compressors. The process begins with structural preparation on the roof, where a pre-fabricated roof curb is installed to support the unit and align with duct openings. The curb may be secured to the roof deck, and penetrations are made for supply and return air ducts, electrical conduits, and control cabling. In embodiments with a MGT systems comprising fewer moving parts and generate less vibration than compressor-based systems, vibration isolation and structural reinforcement requirements may be reduced, potentially lowering installation complexity and cost.

[0472] With a curb in place, a magnetocaloric RTU may be lifted onto the rooftop using a crane. The unit is positioned onto the curb and aligned with the duct and mounting openings. Final anchoring is done according to building codes, including wind uplift compliance. Depending on the specific design, magnetocaloric units may be lighter than traditional RTUs, which can reduce crane size and case handling during placement.

[0473] Electrical connections may be made to provide power to the unit, typically using standard commercial voltages such as 208V or 480V. Control wiring is connected either to the building automation system (BAS) or to a standalone thermostat. One advantage at this stage is that refrigerant piping, pressurization, or leak testing may not be required, as magnetocaloric systems do not use chemical refrigerants. This may eliminate a step in traditional HVAC commissioning and reduces a need for EPA-certified personnel.

[0474] Ductwork is connected, and supply and return lines may be routed through the curb or into side-mounted plenums, depending on the unit design. Ducts may be sealed and insulated to minimize energy loss and ensure optimal airflow. With fewer mechanical integration requirements than vapor-compression systems, these connections can typically be completed more quickly.

[0475] With the MGT RTU powered on, a magnetocaloric cycle is initiated through a solid-state system that moves heat using magnetic fields and magnetocaloric materials. Installers check airflow rates, actuator function, sensor outputs, and basic system diagnostics. Since there are no refrigerant pressures to balance or compressors to stage, start-up may be faster and more straightforward, making it easier for less-experienced technicians to perform correctly.

[0476] While the invention has been described in conjunction with specific embodiments, it is evident that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the foregoing description. Accordingly, this description is intended to embrace all such alternatives, modifications and variations as fall within its spirit and scope.

[0477] The headings utilized in this document serve solely for organizational purposes and should not be interpreted as limiting the scope of either the description or the claims. Throughout this application, the term “may” is employed in a permissive sense, implying the potential for an action or feature, rather than a mandatory sense. Additionally, the words “include,”“including,” and “includes” are used in an inclusive manner, meaning “including, but not limited to”. To aid clarity, similar reference numerals have been used, where feasible, to denote similar elements across different figures.

[0478] The expressions “at least one,”“one or more,” and “and / or” are open-ended and operate both conjunctively and disjunctively. For example, the phrases “at least one of A, B, and C,”“at least one of A, B, or C,”“one or more of A, B, and C,”“one or more of A, B, or C,” and “A, B, and / or C” encompass various combinations: A alone, B alone, C alone, A and B, A and C, B and C, or A, B, and C together.

[0479] The term “a” or “an” entity implies one or more of that entity. Consequently, the terms “a” (or “an”), “one or more,” and “at least one” are used interchangeably in this document. It is also important to note that the terms “comprising,”“including,” and “having” are used synonymously.

[0480] Features described in this specification in the context of separate embodiments can also be integrated into a single embodiment. Conversely, features described within a single embodiment can be implemented in multiple separate embodiments, either alone or in any suitable sub-combination. Furthermore, while certain features may be described and initially claimed in combination, it is possible to remove one or more features from the combination, resulting in a claimed sub-combination or variation thereof.

[0481] AI though method steps may be illustrated in a specific order, this should not be construed as a requirement that these operations must be performed in the depicted order or sequentially, nor that all illustrated operations are necessary for achieving the desired outcomes.

[0482] The separation of system components in the described embodiments is not mandatory for all embodiments. The components and systems described can typically be integrated into a single product or distributed across multiple products. Therefore, while specific embodiments have been detailed, other embodiments fall within the scope of the appended claims. In some instances, the actions recited in the claims can be performed in a different order and still yield desirable results. Moreover, the methods, systems or apparatuses shown in the accompanying figures do not necessarily require the depicted order or sequential progression to achieve beneficial outcomes. In certain implementations, selective arrangements may prove beneficial. However, it should be understood that various modifications can be made without departing from the spirit and scope of the claimed disclosure.

Examples

Embodiment Construction

[0059]The present invention provides a system, apparatus and methods for a Smart Roof Top Unit (SRTU) that integrates advanced infrared (IR) temperature monitoring to enhance its operational efficiency and reliability. The system utilizes IR cameras strategically placed on or around the SRTU unit to continuously capture thermal images or video feed of the SRTU. These thermal images are useful for identifying temperature variations and detecting potential issues such as overheating or frost accumulation.

[0060]The captured IR thermal images may be converted into digital value patterns, allowing for precise quantitative analysis by a Controller and / or AI engine. Each pixel in the thermal image corresponds to a specific temperature value, which is digitized to form a detailed thermal map of the SRTU. This digital representation of thermal data is essential for the subsequent analysis and control processes managed by the Controller and / or AI engine integrated within the SRTU or on a clou...

Claims

1. A Smart Rooftop Unit (SRTU) for a Heating, Ventilation, and Air Conditioning (HVAC) system, the SRTU comprising:a plurality of SRTU components comprising two or more of: an air hood, an economizer hood, a high efficiency particulate air (HEPA) filter, a heat wheel, a subsequent filter, a mixing damper, a heating coil, a cooling coil, an evaporator coil, and a centrifugal electronically commutated (EC) fan;at least one infrared (IR) camera strategically positioned on or within the SRTU to capture thermal images of at least one of: a surface of the SRTU, and at least one of the plurality of SRTU components; anda control system comprising: a processor; a memory storing instructions executable by the processor; and an artificial intelligence (AI) engine; wherein the Control System and / or AI engine is configured to analyze the thermal images captured by the at least one IR camera to control at least one of: the SRTU, the HVAC system, and at least one of the plurality of SRTU components.

2. The SRTU of claim 1, wherein the Control System and / or AI engine is configured to analyze the thermal images captured by the at least one IR camera to perform one or more of:a. convert the thermal images into digital value patterns representing temperature distributions;b. assess the digital value patterns to identify temperature anomalies and operational inefficiencies;c. map the digital value patterns against variable operational trends including defrost cycles, power use, and equipment performance;d. optimize operation of at least one of the plurality of SRTU components by adjusting control parameters based on the assessed digital value patterns and mapped trends to enhance energy efficiency and system performance;e. predict maintenance needs and potential equipment failures based on historical and real-time analysis of the thermal images;f. provide real-time updates and actionable recommendations for SRTU modifications to improve efficiency and performance of the SRTU;g. receive and process commands, for additional cooling or heating requirements, from a user or a building management system (BMS) and anticipate temperature maps based on expected load; andh. continuously monitor and adjust the SRTU based on ambient conditions including temperature, humidity, and airflow within building spaces to ensure optimal indoor climate control.

3. The SRTU of claim 1, further comprising a plurality of IR cameras positioned externally around the SRTU to capture thermal images of outer surface of the SRTU from different directions and angles.

4. The SRTU of claim 1, wherein the SRTU is constructed from a Polypropylene Random Copolymer (PPR) core layer, and at least one protective layer affixed to the PPR core layer; wherein the at least one protective layer is selected from at least one of: a metallic layer, a non-metallic layer, and a nanocomposite coating.

5. The SRTU of claim 1, wherein the control system comprises machine learning algorithms to improve thermal image analysis over time.

6. The SRTU of claim 1, wherein the control system optimizes operation of the heating coil during defrost cycles based on thermal image analysis.

7. The SRTU of claim 1, wherein the AI engine provides predictive analytics for maintenance scheduling based on analysis of the thermal images.

8. The SRTU of claim 7, wherein the AI engine is capable of self-learning to improve the analysis of the thermal images over time.

9. The SRTU of claim 1, wherein the control system is capable of sending alerts and notifications to maintenance personnel when anomalies are detected in the thermal images.

10. The SRTU of claim 1, further comprising at least one sensor comprising one or more of: a temperature sensor, a pressure sensor, a humidity sensor, and an air-quality sensor.

11. The SRTU of claim 1, wherein the AI engine provides automated recommendations for design modifications related to one or both of: the SRTU and at least one of the plurality of SRTU components.

12. The SRTU of claim 1, wherein the air hood is configured to guide atmospheric air into the SRTU.

13. The SRTU of claim 1, wherein the economizer hood is configured to utilize external air for cooling when conditions allow.

14. The SRTU of claim 1, wherein the HEPA filter is configured to remove fine particulates from incoming air.

15. The SRTU of claim 1, wherein the evaporator coil facilitates cooling process by absorbing heat from air.

16. The SRTU of claim 15, wherein the Control System controls defrost cycles of the evaporator coil based on analysis of the thermal images captured by the at least one IR camera.

17. The SRTU of claim 16, wherein the Control System and / or AI engine dynamically adjusts timing and duration of the defrost cycles based on the analysis of the thermal images to prevent frost buildup and maintain optimal cooling efficiency.

18. The SRTU of claim 2, wherein the control system is configured to integrate with the BMS of a building for enhanced operational control of the SRTU.

19. The SRTU of claim 18, wherein the Control System and / or AI engine receives real-time data from the BMS, including temperature, humidity, air-quality, and occupancy level within the building to optimize HVAC operations.

20. The SRTU of claim 18, wherein the control system can receive commands from the BMS to adjust heating or cooling of different zones within the building.

21. The SRTU of claim 18, wherein the control system can adjust airflow and temperature settings based on occupancy patterns for different zones within the building.

22. The SRTU of claim 18, wherein the BMS integration allows the Control System and / or AI engine to schedule HVAC operations based on one or more or: planned building activities, occupancy patterns, day of a week, time of day, seasonal variations, and geographic location of the building to optimize energy usage and maintain optimal indoor climate conditions within the building.

23. A method for controlling a Smart Roof Top Unit (SRTU) for a Heating, Ventilation, and Air Conditioning (HVAC) system, the method comprising:providing multiple SRTU components housed within the SRTU, wherein the multiple SRTU components comprising one or more of: an air hood, a damper, a filter, a heat wheel, subsequent filters, a mixing damper, a heating coil, a cooling coil, an evaporator coil, and a centrifugal electronically commutated (EC) fan;capturing thermal images of the multiple SRTU components using at least one infrared (IR) camera positioned on, around, or within the SRTU, the thermal images comprising temperature signatures of at least one of: a surface of the SRTU, and at least one component of the multiple SRTU components;transmitting the captured thermal images to a control system comprising a processor, a memory storing instructions executable by the processor, and an artificial intelligence (AI) engine;converting, by a Controller and / or AI engine, the captured thermal images into digital value patterns representing temperature distributions across the at least one of: the surface of the SRTU, and the at least one component of the multiple SRTU components;analyzing, by the Controller and / or AI engine, the digital value patterns to analyze the temperature distributions and identify anomalies indicative of operational inefficiencies, equipment failures, or potential maintenance needs; andcontrolling one or both of the SRTU and the HVAC system based on the analysis of the temperature distributions and the identified anomalies in the temperature distributions.

24. The method of claim 23, further comprising mapping the digital value patterns against variable operational trends, including defrost cycles, power use, and efficiency metrics, to optimize HVAC operations.

25. The method of claim 24, further comprising adjusting control parameters of the multiple SRTU components based on the mapping to enhance energy efficiency, reduce wear and tear, and maintain optimal performance of the SRTU.

26. The method of claim 23, further comprising initiating a defrost cycle for the evaporator coil based on the analysis of the digital value patterns, including dynamically adjusting timing and duration of the defrost cycle to prevent frost buildup and maintain cooling efficiency.

27. The method of claim 23, further comprising receiving commands for additional cooling or heating requirements from a user or a building management system (BMS), and controlling at least one of: the SRTU, the multiple SRTU components, and HVAC system based on the received commands.

28. The method of claim 23, further comprising continuously monitoring ambient conditions within a building, including temperature, humidity, air-quality, and airflow, using multiple sensors integrated within different spaces of the building.

29. The method of claim 28, further comprising using the AI engine to predict HVAC demand based on real-time and historical data, including day of a week, time of day, seasonal variations, and geographic location of the building.

30. The method of claim 29, further comprising adjusting HVAC operations dynamically based on the predicted HVAC demand to maintain optimal indoor climate conditions and energy efficiency.

31. The method of claim 23, further comprising transmitting thermal images and operational data to a cloud server for storage and cumulative AI analysis of thermal images from a plurality of SRTU units.

32. The method of claim 23, further comprising providing actionable recommendations for modifications to the SRTU or the multiple SRTU components to improve efficiency and performance of the SRTU.

33. The method of claim 23, wherein the AI engine uses machine learning algorithms to improve an accuracy in identifying the anomalies in the temperature distributions over time.

34. The method of claim 23, further comprising mapping the digital value patterns representing temperature distributions across the surface of the SRTU to corresponding SRTU components housed within the SRTU.

35. The method of claim 34, wherein the mapping comprises identifying specific temperature zones on the surface of the SRTU that correspond to individual SRTU components inside the SRTU.

36. The method of claim 35, wherein the Controller determines working conditions of the multiple SRTU components by analyzing the mapped temperature distributions across the surface of the SRTU.

Images