System and methods for HVAC equipment classification based on an energy envelope
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2026-02-05
- Publication Date
- 2026-08-13
Smart Images
Figure US2026014103_13082026_PF_FP_ABST
Abstract
Description
Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 SYSTEM AND METHODS FOR HVAC EQUIPMENT CLASSIFICATION BASED ON AN ENERGY ENVELOPECROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of, and priority to, U.S. Provisional Patent Application No. 63 / 754,255 filed February’ 5. 2025, the entire contents of which are incorporated herein by reference.FIELD OF THE DISCLOSURE
[0002] The present disclosure is generally related to HVAC system efficiency and building energy performance, and more particularly, to a decision intelligence (Dl)-based computerized framework for HVAC sizing classification and building envelope energy loss analysisSUMMARY OF THE DISCLOSURE
[0003] The present disclosure is directed to a system configured to optimize heating, ventilation, and air conditioning (HVAC) systems while enhancing building energy efficiency. As used herein, the term “system” when not used with other modifiers refers to the energy envelope modeling system described herein as a whole, where various other sub-systems that form part of the “system” are denoted with a modifier (e.g., HVAC system, renewable energy system, etc.). In some embodiments, the system gathers climate data related to a location’s activity7, which may include historical weather patterns and / or HVAC runtime data. The data is segmented and categorized based on factors such as HVAC equipment ty pe, geographical region, and / or season of the year for analysis.
[0004] In some embodiments, the system is configured to determine whether an HVAC system is under-sized, over-sized, or correctly-sized for the location based on the analysis of the collected climate data. In some embodiments, the system is configured to determine energy’ control parameters to optimize the current and / or future HVAC system’s operation. Results provide insights and recommendations for potential adjustments or retrofitting are then communicated to users.
[0005] In some embodiments, the system is configured to analyze heat transfer losses within a building’s envelope. In some embodiments, the system is configured to use a framework of computers and / or sensors that collect data on the amount of heat lost from the building envelope during periods when the HVAC system is not actively running. Historical energy performance1ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 records are retrieved to serve as a baseline for comparison and analysis in some embodiments. In some embodiments, the system filters the collected data to exclude variances due to solar gains, internal gains, and weather conditions, ensuring that the analysis is concentrated on actual heat transfer losses. Using the calculated energy envelope, the system is configured to create a model that determines the building's energy' efficiency and heat retention capabilities (i.e., energy envelope). By correlating a type of energy input / output with a type of data (e.g., sensor data, weather data), the system is able to output suggestions for types of improvements that can be made, such as adding insulation, sealing gaps, and / or upgrading windows, as nonlimiting examples.
[0006] For example, excessive HVAC operation (i.e., greater than similar sized home within the system’s monitoring network) on a relatively cool day with heavy cloud cover may cause the system to suggest that there are large air leaks that need to be addressed. In some embodiments, the system is configured to output an amount of solar heat gained based on collected data. For example, for a given temperature, if the HVAC system runs more on a cloudless day than a day with heavy overcast, the model would correlate the respective portion of the energy exchange to solar energy input.
[0007] The integration of the framework within the system allows for a comprehensive approach to HVAC system optimization and building energy management. By combining the analysis of HVAC sizing and heat transfer losses, the system evaluates both the mechanical and structural aspects of energy efficiency. The energy envelope determined through the analysis enables a determination of the HVAC size classification and / or optimum control parameters for each size classification, ensuring that the HVAC system operates in alignment with the building's energy characteristics. In some embodiments, the system is configured to deliver precise recommendations for retrofitting and energy management, facilitating informed decision-making for building owners and managers.
[0008] The system enhances HVAC performance and building energy efficiency by leveraging advanced data analysis and control techniques. The system enables the identification of specific improvements that can be made to reduce energy consumption, lower utility bills, and improve indoor comfort. In some embodiments, through the integration of AI / ML techniques and comprehensive data analysis, the system ensures that HVAC systems are optimally sized and controlled, while also addressing the energy efficiency of the building envelope.2ACTIVE 718784368v1Attorney Docket No. 203863-019601 / PCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 DESCRIPTIONS OF THE DRAWING
[0009] The features, and advantages of the disclosure will be apparent from the following description of embodiments as illustrated in the accompanying drawings, in which reference characters refer to the same parts throughout the various views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating principles of the disclosure:
[0010] FIG. 1 is a block diagram of an example configuration within which the systems and methods disclosed herein could be implemented according to some embodiments of the present disclosure;
[0011] FIG. 2 is a block diagram illustrating components of an exemplary system according to some embodiments of the present disclosure;
[0012] FIG. 3 illustrates an example HVAC sizing workflow according to some embodiments of the present disclosure;
[0013] FIG. 4 illustrates an example heat loss execution workflow according to some embodiments of the present disclosure;
[0014] FIG. 5 depicts an example implementation of an architecture according to some embodiments of the present disclosure;
[0015] FIG. 6 depicts an example implementation of an architecture according to some embodiments of the present disclosure; and
[0016] FIG. 7 is a block diagram illustrating a computing device showing an example of a client or server device used in various embodiments of the present disclosure.DETAILED DESCRIPTION
[0017] The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, which form a part hereof, and which show, by way of non-limiting illustration, certain example embodiments. Subject matter may, however, be embodied in a variety of different forms and, therefore, covered or claimed subject matter is intended to be construed as not being limited to any example embodiments set forth herein; example embodiments are provided merely to be illustrative. Likewise, a reasonably broad scope for claimed or covered subject matter is intended. Among other things, for example, subject matter may be embodied as methods, devices, components, or systems. Accordingly, embodiments may, for example, take the form of hardware, software, firmware or any combination thereof3ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 (other than software per se). The following detailed description is, therefore, not intended to be taken in a limiting sense.
[0018] Throughout the specification and claims, terms may have nuanced meanings suggested or implied in context beyond an explicitly stated meaning. Likewise, the phrase “in some embodiments” as used herein does not necessarily refer to the same embodiment and the phrase “in some embodiments” as used herein does not necessarily refer to a different embodiment. It is intended, for example, that claimed subject matter include combinations of any embodiments, in whole or in part, described herein.
[0019] In general, terminology7may be understood at least in part from usage in context. For example, terms, such as “and”, “or”, or “and / or,” as used herein may include a variety of meanings that may depend at least in part upon the context in which such terms are used. Typically, “or” if used to associate a list, such as A, B or C, is intended to mean A, B, and C, here used in the inclusive sense, as well as A, B, or C, here used in the exclusive sense. In addition, the term “one or more” as used herein, depending at least in part upon context, may be used to describe any feature, structure, or characteristic in a singular sense or may be used to describe combinations of features, structures or characteristics in a plural sense. Similarly, terms, such as “a,” “an,” or “the,” again, may be understood to convey a singular usage or to convey a plural usage, depending at least in part upon context. In addition, the term “based on” may be understood as not necessarily intended to convey an exclusive set of factors and may, instead, allow for existence of additional factors not necessarily expressly described, again, depending at least in part on context.
[0020] As used herein, “can” or “may” or derivations there of (e.g., the system display can show X) are used for descriptive purposes only and is understood to be synonymous and / or interchangeable with “configured to” (e.g., the computer is configured to execute instructions X) when defining the metes and bounds of the system. The phrase “configured to” also denotes the step of configuring a structure or computer to execute an algorithm step according to some embodiments.
[0021] The present disclosure is described below with reference to block diagrams and operational illustrations of methods and devices. It is understood that each block of the block diagrams or operational illustrations, and combinations of blocks in the block diagrams or operational illustrations, can be implemented by means of analog or digital hardware and computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer to alter its function as detailed herein, a special4ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 purpose computer, ASIC, or other programmable data processing apparatus, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, implement the functions / acts specified in the block diagrams or operational block or blocks. In some embodiments, the functions / acts noted in the blocks can occur out of the order noted in the operational illustrations. For example, two blocks shown in succession can in fact be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality / acts involved.
[0022] For the purposes of this disclosure a non-transitory computer readable medium (or computer-readable storage medium / media) stores computer data, which data can include computer program code (or computer-executable instructions) that is executable by a computer, in machine readable form. By way of example, and not limitation, a computer readable medium may include computer readable storage media, for tangible or fixed storage of data, or communication media for transient interpretation of code-containing signals. Computer readable storage media, as used herein, refers to physical or tangible storage (as opposed to signals) and includes without limitation volatile and non-volatile, removable and nonremovable media implemented in any method or technology for the tangible storage of information such as computer-readable instructions, data structures, program modules or other data. Computer readable storage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology; optical storage, cloud storage, magnetic storage devices, or any other physical or material medium which can be used to tangibly store the desired information or data or instructions and which can be accessed by a computer or processor.
[0023] For the purposes of this disclosure the term ‘‘server’' should be understood to refer to a service point which provides processing, database, and communication facilities. By way of example, and not limitation, the term “server” can refer to a single, physical processor with associated communications and data storage and database facilities, or it can refer to a networked or clustered complex of processors and associated network and storage devices, as well as operating software and one or more database systems and application software that support the services provided by the server. Cloud servers are examples.
[0024] For the purposes of this disclosure a “network” should be understood to refer to a network that may couple devices so that communications may be exchanged, such as between a server and a client device or other types of devices, including between wireless devices coupled via a wireless network, for example. A network may also include mass storage, such5ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 as network atached storage (NAS), a storage area network (SAN), a content delivery' network (CDN) or other forms of computer or machine-readable media, for example. A network may include the Internet, one or more local area networks (LANs), one or more wide area networks (WANs), wire-line type connections, wireless type connections, cellular or any combination thereof. Likewise, sub-networks, which may employ differing architectures or may be compliant or compatible with differing protocols, may interoperate within a larger network.
[0025] For purposes of this disclosure, a ’‘wireless network” should be understood to couple client devices with a network. A wireless network may employ stand-alone ad-hoc networks, mesh networks, Wireless LAN (WLAN) networks, cellular networks, or the like. A wireless network may further employ a plurality of network access technologies, including Wi-Fi, Long Term Evolution (LTE), WLAN, Wireless Router mesh, or 2nd, 3rd, 4thor 5thgeneration (2G, 3G, 4G or 5G) cellular technology7, mobile edge computing (MEC), Bluetooth, 802.11b / g / n, or the like. Network access technologies may enable wide area coverage for devices, such as client devices with varying degrees of mobility, for example.
[0026] In short, a wireless network may include virtually any type of wireless communication mechanism by which signals may be communicated between devices, such as a client device or a computing device, between or within a network, or the like.
[0027] A computing device, which may include one or more computers, may be capable of sending or receiving signals, such as via a wired or wireless network, or may be capable of processing or storing signals, such as in memory' as physical memory' states, and may, therefore, operate as a server. Thus, devices capable of operating as a server may include, as examples, dedicated rack-mounted servers, desktop computers, laptop computers, set top boxes, integrated devices combining various features, such as two or more features of the foregoing devices, or the like.
[0028] For purposes of this disclosure, a client (or user, entity, subscriber or customer) device may include a computing device capable of sending or receiving signals, such as via a wired or a wireless network. A client device may, for example, include a desktop computer or a portable device, such as a cellular telephone, a smart phone, a display' pager, a radio frequency (RF) device, an infrared (IR) device a near field communication (NFC) device, a personal digital assistant (PDA), a handheld computer, a tablet computer, a phablet, a laptop computer, a set top box. a wearable computer, smart watch, an integrated or distributed device combining various features, such as features of the forgoing devices, or the like.6ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026
[0029] A client device may vary in terms of capabilities or features. Claimed subject matter is intended to cover a wide range of potential variations, such as a web-enabled client device or previously mentioned devices may include a high-resolution screen (HD or 4K for example), one or more physical or virtual keyboards, mass storage, one or more accelerometers, one or more gyroscopes, global positioning system (GPS) or other location-identifying type capability, or a display with a high degree of functionality, such as a touch -sensitive color 2D or 3D display, for example
[0030] Certain embodiments and principles will be discussed in more detail with reference to the figures. According to some embodiments, the disclosed framework provides integrated control and management of one or more devices and / or the applications executing thereon.
[0031] By way of a non-limiting example, according to some embodiments, the framework described herein leverages historical climate data, runtime patterns, and advanced data segmentation techniques to provide accurate assessments and recommendations for HVAC system adjustments and building retrofits.
[0032] According to some embodiments, the discussion herein may focus on embodiments related to HVAC system optimization and building energy efficiency (e.g., HVAC rightsizing classification and building envelope energy loss analysis); however, these examples should not be construed as limiting, as one of skill in the art would understand that the disclosed framework described herein can apply to various scenarios without departing from the scope of the instant disclosure. For example, the system may be configured to integrate with smart home systems to provide real-time energy usage feedback and predictive maintenance alerts. In some embodiments, the framework could be adapted for use in commercial buildings, industrial facilities, or residential complexes as non-limiting examples.
[0033] Moreover, embodiments exist where the disclosed framework can be applied to diverse energy management systems beyond traditional HVAC setups. For example, in some embodiments, the framework could be utilized in renewable energy' systems to optimize the integration of solar or wind energy with existing HVAC systems. In some embodiments, the framework could be adapted for use in smart grid applications, where the framework helps balance energy loads and improve overall grid stability by predicting and adjusting for energy demands.
[0034] With reference to FIG. 1, system 100 is depicted which includes user equipment (UE) 102 (e.g.. a client device, as mentioned above and discussed below in relation to FIG. 7). HVAC system 112, network 104, cloud platform 106, database 108, and analysis engine 200. It should7ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 be understood that while system 100 is depicted as including such components, it should not be construed as limiting, as one of ordinary skill in the art would readily understand that varying numbers of UEs, sensors, HVAC systems, peripheral devices, cloud systems, databases, and networks can be utilized; however, for purposes of explanation, system 100 is discussed in relation to the example depiction in FIG. 1. The analysis engine 200 is responsible for processing data inputs from various sources to provide insights and recommendations for optimizing HVAC system performance and / or building energy efficiency.
[0035] According to some embodiments, UE 102 can be any type of device, such as, but not limited to, a desk top computer, a server, a mobile (smart) phone, tablet, laptop, sensor, loT device, autonomous machine, appliance, and / or any device equipped with a cellular and / or wireless or wired transceiver. For example, UE 102 can be a smart phone with various Apps installed, which as discussed below in more detail, can enable the identification and / or collection of activity7information of the user to guide actual App and / or UE usage.
[0036] In some embodiments, one or more peripheral devices (not shown) can be connected to UE 102, and can be any type of peripheral device, such as. but not limited to, a wearable device (e.g., smart watch), printer, speaker, sensor, and the like. In some embodiments, peripheral device can be any type of device that is connectable to UE 102 via any ty pe of known or to be known pairing mechanism, including, but not limited to, WiFi, Bluetooth™, Bluetooth Low Energy (BLE). NFC, and the like. For example, the peripheral device can be a speaker that connectively pairs with UE 102, which includes a client device in some non-limiting examples.
[0037] According to some embodiments, HVAC system 112 is a device that regulates the climate control for an enclosed environment (e.g., home) a location. According to some embodiments, the HVAC system 112 can be, but is not limited to, a central air conditioning unit, a heat pump, a furnace, and / or any other type of climate control hardware that can manage temperature and air quality in a designated area. In some embodiments, UE 102 may include an interface to control or monitor the HVAC system, and / or to receive the analysis performed by analysis engine 200, which may include data obtained from one or more sensors 110.
[0038] According to some embodiments, the one or more sensors 110 are used to gather data for the analysis engine 200. In some embodiments, the one or more sensors 110 may include temperature sensors configured to monitor the ambient temperature within different zones of a building. In some embodiments, the one or more sensors 110 include humidity7sensors configured to measure the moisture levels in the air, which can affect both comfort and energy efficiency. The one or more sensors 110 can include air quality sensors detect pollutants or8ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 particulates in the air. In some embodiments, the one or more sensors 1100 include pressure sensors configured monitor the pressure within the HVAC ducts, indicating blockages or leaks that may affect system performance and energy efficiency. In some embodiments, motion sensors can be used to detect occupancy in different areas of the building, allowing the system to determine heating or cooling envelopes based on actual usage patterns. In some embodiments, one or more sensors 110 may include light sensors configured to measure sunlight exposure levels, which can be used to determine solar heat gain. While not exhaustive, these example sensors provide a dataset that the analysis engine 200 can use to optimize HVAC performance, improve energy' efficiency, and enhance overall comfort within an enclosed environment, such as a home or building, as further described herein.
[0039] In some embodiments, network 104 can be any type of network, such as, but not limited to, a wireless network, cellular network, the Internet, and the like (as discussed above). Network 104 facilitates connectivity' of the components of system 100, as illustrated in FIG. 1.
[0040] According to some embodiments, cloud platform 106 may be any ty pe of cloud operating platform and / or network-based system upon which applications, operations, and / or other forms of network resources may be located. For example, platform 106 may be a sendee provider and / or network provider from where services and / or applications may be accessed, sourced or executed from. For example, platform 106 can represent the cloud-based architecture associated with a smart home or network provider, which has associated network resources hosted on the internet or private network (e.g., network 104), which enables (via analysis engine 200) the device control and management discussed herein.
[0041] In some embodiments, cloud platform 106 may include a server(s) and / or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud platform 106 may store a dataset of data and metadata associated with local and / or network information related to a user(s) of the components of system 100 and / or each of the components of system 100 (e.g., UE 102, HVAC system 112, and the services and applications provided by cloud platform 106 and / or analysis engine 200).
[0042] In some embodiments, for example, cloud platform 106 can provide a private / proprietary management platform, whereby analysis engine 200, discussed infra, corresponds to the novel functionality cloud platform 106 enables, hosts and provides to a network 104 and other devices / platforms operating thereon.
[0043] Turning to FIG. 5 and FIG. 6. in some embodiments, the exemplary computer-based systems / platforms, the exemplary computer-based devices, and / or the exemplary computer-9ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 based components of the present disclosure may be specifically configured to operate in a cloud computing / architecture 120 such as. but not limiting to: infrastructure as a service (laaS) 610. platform as a service (PaaS) 608, and / or software as a service (SaaS) 606 using a web browser, mobile app, thin client, terminal emulator or other endpoint 604. FIG. 5 and FIG. 6 illustrate schematics of non-limiting implementations of the cloud computing / architecture(s) in which the exemplary computer-based systems for administrative customizations and control of network-hosted application program interfaces (APIs) of the present disclosure may be specifically configured to operate.
[0044] Turning back to FIG. 1, according to some embodiments, database 108 may correspond to a data storage for a platform (e.g., a network hosted platform, such as cloud platform 106, as discussed supra) or a plurality of platforms. Database 108 may receive storage instruct! ons / requests from, for example, analysis engine 200 (and associated microservices), which may be in any type of known or to be known format, such as, for example, standard query language (SQL). According to some embodiments, database 108 may correspond to any type of known or to be known storage, for example, a memory or memory stack of a device, a distributed ledger of a distributed network (e.g., blockchain, for example), a look-up table (LUT), and / or any other type of secure data repository'.
[0045] Analysis engine 200, as discussed above and further below in more detail, can include components for the disclosed functionality. According to some embodiments, analysis engine 200 may be a special purpose machine or processor and can be hosted by a device on network 104, within cloud platform 106, on AP device 112 and / or on UE 102. In some embodiments, analysis engine 200 may be hosted by a server and / or set of servers associated with cloud platform 106.
[0046] According to some embodiments, as discussed in more detail below, analysis engine 200 may be configured to implement and / or control a plurality of services and / or microsendees, w here each of the plurality of services / microservices are configured to execute a plurality of workflows associated with performing the disclosed application control and management framework. Non-limiting embodiments of such workflows are provided below.
[0047] According to some embodiments, as discussed above, analysis engine 200 may function as an application provided by cloud platform 106. In some embodiments, analysis engine 200 may function as an application installed on a server(s), network location and / or other type of network resource associated with platform 106. In some embodiments, analysis engine 200 may function as application installed and / or executing on UE 102. In some embodiments, such10ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 application may be a web-based application accessed by UE 102 over network 104 from cloud platform 106. In some embodiments, analysis engine 200 may be configured and / or installed as an augmenting script, program or application (e.g., a plug-in or extension) to another application or program provided by cloud platform 106 and / or executing on UE 102. In some embodiments, a portion of the analysis engine 200 is stored on and / or executed by a combination of one or more of the afore mentioned portions of the framework.
[0048] As illustrated in FIG. 2, according to some embodiments, analysis engine 200 includes data acquisition module 202, data pre-processing module 204, analysis module 206, and / or control module 208.
[0049] In some embodiments, the data acquisition module 202 is configured for collecting and inputting all relevant data required for analysis, which may include gathering climate data, heat transfer loss data, and historical energy' performance records, as non-limiting examples. In some embodiments, data acquisition module 202 is configured to interface with one or more sensors 110, database 108, and / or external data sources, and / or is configured to prepare the data for further processing by segmenting and categorizing the data that is received.
[0050] In some embodiments, the data pre-processing module 204 processes the collected data, which may include steps to segment, categorize, and filter out variances, ensuring accuracy and relevance when determining an energy envelope by excluding variances due to solar gains, internal gains, and weather conditions, for example.
[0051] In some embodiments, the analysis module 206 performs the computational analysis of the HVAC system, which may include conducting statistical analysis, pattern recognition, and / or predictive modeling, as non-limiting examples. In some embodiments, the analysis module 206 is configured to determine the HVAC classification and / or calculate the energy envelope performance, providing insights into the building’s energy’ efficiency.
[0052] In some embodiments, the control module 208 implements control actions based on the analysis results and outputs the findings, establishing energy control parameters and executing control commands to optimize HVAC system operation. In some embodiments, the control module 208 outputs classification results and energy envelope data, displaying them on a graphical user interface (GUI) and providing actionable recommendations for system improvements.
[0053] It should be understood that the engine(s) and modules discussed herein are non-exhaustive. as additional or feyver engines and / or modules (or sub-modules) may be applicable to the embodiments of the systems and methods discussed. More detail of the operations.11ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 configurations, and functionalities of analysis engine 200 and each of its modules, and their role within embodiments of the present disclosure, can generally be described as being executed by the system without reference to a particular module or the framework.
[0054] Turning to FIG. 3, process 300 provides a non-limiting example according to some embodiments for the disclosed system. In some embodiments, process 300 provides some nonlimiting embodiments for applications for which the disclosed framework (e.g., via analysis engine 200) can control, manage, and manipulate data obtained for the analysis.
[0055] Steps described in the figures represent both an execution of a computer algorithm and a method of implementing the system via the framework. According to some embodiments, steps 302-304 of process 300. which involve initializing the HVAC sizing process and collecting climate data, can be performed by the data acquisition module 202 of analysis engine 200.
[0056] Step 306, which involves segmenting and categorizing the data, can be performed by the data processing and filtering module 204.
[0057] Steps 308-310, which include performing data analysis and determining HVAC classification, can be performed by the analysis and classification module 206.
[0058] Steps 312-316, which involve establishing energy control parameters, outputting classification results, and controlling the HVAC system based on control parameters, can be performed by the control and output module 208.
[0059] It should be understood that while the discussion herein will be with reference to specific applications, it should not be construed as limiting, as any type of program, website, network resource, platform, or device (e.g., any of the UEs discussed above) can form the basis of the system without departing from the scope of the instant disclosure.
[0060] According to some embodiments, process 300 begins with step 302 where the analysis engine 200 can initialize the HVAC sizing process, ensuring that all necessary systems and interfaces are ready for operation. As mentioned previously, any program can be executed by UE 102 (e.g., a client device or control interface). By way of non-limiting examples, the initialization can include any type of known or to be known software setup such as, but not limited to, system configuration, data input preparation, and the like, or some combination thereof.
[0061] In some embodiments, the analysis engine 200 is configured to collect and input data in Step 304. In some embodiments, this includes gathering climate data related to a location’s activity, which may include historical weather patterns and / or HVAC runtime data. The data12ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 collection can be automated, obtaining data associated with sensors 110, accessing database 108, and / or querying external data sources, such as historical weather websites, to ensure comprehensive data acquisition.
[0062] In step 306, the analysis engine 200 is configured to segment and categorize the collected data, which involves using algorithms to organize the data based on factors such as HVAC equipment type, geographical region, and season of the year. The segmentation process ensures that the data is structured in a way that facilitates detailed analysis, allowing for more precise insights into the HVAC system’s performance.
[0063] In step 308, the analysis engine 200 performs data analysis on the segmented data. The analysis can involve any type of known or to be known computational techniques that enable the engine to derive, determine, extract, retrieve, or otherwise assess the HVAC system’s performance. In some embodiments, step 308 includes statistical analysis, pattern recognition, and / or predictive modeling to evaluate the efficiency and suitability of the current HVAC setup. In some embodiments, step 308 includes execution of one or more the steps of the heat transfer analysis depicted in FIG. 4, discussed infra. In some embodiments, the data analysis includes an output of performance degradation of an HVAC system over time, where correlation between maintenance events (e.g., filter changes, cooling fin cleaning) enables the system to discern between a wrongly sized HVAC system and one that is not properly maintained.
[0064] In step 310, the analysis engine 200 determines the HVAC classification based on the analysis results. This classification indicates whether the HVAC system is under-sized, oversized, or correctly -si zed for the location, where a correctly-sized HVAC system is configured to maintain a specific environmental (e.g., temperature, humidity) setpoint range using the classification. The classification is determined using predefined criteria and thresholds, at least part of which are defined by the heat transfer loss analysis in accordance with some embodiments.
[0065] A correctly sized HVAC system is configured to operate in longer, steady cycles rather than short, frequent cycles, thereby preventing frequent cycling. Over-sized systems are prone to short-cycling, which can lead to increased wear and tear on system components and inefficient temperature control. Conversely, under-sized systems tend to run continuously, resulting in higher energy consumption and an inability' to maintain comfort effectively. Additionally, a properly / correctly-sized system ensures even temperature distribution throughout the building, preventing hot or cold spots.13ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026
[0066] A correctly -sized system may also maintain desired humidity levels by having sufficient capacity to dehumidify during cooling mode and sustain optimal humidity levels, typically between 30-50%. Over-sized systems often fail to operate long enough to adequately remove humidity7, while under-sized systems struggle to achieve the necessary' comfort levels. Moreover, the correct sizing of an HVAC system optimizes energy efficiency by ensuring the system operates within its designed efficiency parameters, thereby minimizing energy consumption and reducing utility costs.
[0067] Furthermore, a correctly-sized HVAC system supports indoor air quality (IAQ) by managing filtration and ventilation effectively without overloading the system's capacity. This includes facilitating fresh air exchange and maintaining clean air circulation. In some embodiments, a correctly-sized HVAC system allows for future scalability, taking into account potential changes such as room additions or increased occupancy, ensuring long-term adaptability and performance.
[0068] In step 312, the analysis engine 200 outputs the classification results. In some embodiments, this includes generating and displaying insights and recommendations for potential adjustments or retrofitting to obtain the benefits described above. The output can be communicated to relevant personnel, such as HVAC contractors or homeowners, through a notification (e.g., email, display output) providing actionable information to guide decisionmaking and system improvements.
[0069] In step 314, the analysis engine 200 determines energy' control parameters needed to maintain a desired climate within an enclosed environment based on the determined classification. These parameters optimize the future / current HVAC system’s operation and efficiency, which may include adjustments to system settings, scheduling, and operational modes. This step allows for the system to choose the most energy efficient HVAC system for a particular environment, and / or enables the framework to generate a control plan to improve the energy efficacy of an existing HVAC system, in accordance with some embodiments.
[0070] In step 316, the analy sis engine 200 implements automatic control of an HVAC system (current or newly installed) based on the determined energy control parameters. In some embodiments, this step includes executing control commands to adjust the HVAC system’s operation (e.g., in real-time), ensuring optimal performance and energy efficiency. For example, the system may adjust the thermostat settings to maintain a consistent temperature that aligns with the energy efficiency goals. In some embodiments, the system can schedule HVAC operation during off-peak hours to reduce energy costs while maintaining comfort levels.14ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 Another non-limiting example includes dynamically adjusting airflow distribution to different zones within a building based on occupancy data obtained from motion sensors, ensuring that energy is not wasted in unoccupied areas.
[0071] In some embodiments, the computational analysis performed by the analysis engine 200 can involve executing any ty pe of known or to be known computational analysis technique, algorithm, mechanism, or technology; The analysis engine 200 may include a specifically trained artificial intelligence or machine learning model (AI / ML), utilizing a particular machine learning model architecture or type, such as convolutional neural networks (CNN), recurrent neural networks (RNN), autoencoders, support vector machines (SVM), and the like, or any suitable combination thereof. In some embodiments, the analysis engine 200 is configured to utilize one or more AI / ML techniques selected from, but not limited to, computer vision, feature vector analysis, decision trees, boosting, support-vector machines, neural networks, nearest neighbor algorithms, Naive Bayes, bagging, random forests, logistic regression, and similar methodologies. By way of a non-limiting example, the analysis engine 200 can implement an XGBoost algorithm for regression and / or classification to analyze the sensor data, as discussed herein.
[0072] According to some embodiments, the AI / ML computational analysis algorithms implemented can be applied and / or executed in a time-based manner, where collected sensor data for specific time periods is allocated to those periods to determine relevant insights. For example, the analysis engine 200 can execute a Bayesian determination for a predetermined time span, at preset intervals (e.g., a 24-hour time span, every78 hours), based on learned or understood patterns (e.g., daily usage trends, peak energy7consumption times), and the like. This segmentation of the day can be leveraged to determine, derive, extract, or otherwise analyze key performance indicators, which can be used to optimize HVAC system operations and improve energy efficiency.
[0073] In some embodiments and, optionally, in combination of any embodiment described above or below7, a neural netw ork technique may be one of, without limitation, feedforw ard neural netw ork, radial basis function network, recunent neural network, convolutional network (e.g., U-net) or other suitable network. In some embodiments and, optionally, in combination of any embodiment described above or below7, an implementation of Neural Netw ork may be executed as follows:a. define Neural Network architecture / model for the control framework, b. transfer the input data to the neural network model,15ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 c. train the model incrementally,d. determine the accuracy for a specific number of timesteps,e. apply the trained model to process the newly received input data,f. optionally and in parallel, continue to train the trained model with a predetermined periodicity.
[0074] In some embodiments and, optionally, in combination of any embodiment described above or below, the trained Al model may specify a neural network by at least a neural network topology, a series of activation functions, and connection weights. For example, the topology7of a neural network may include a configuration of nodes of the neural netw ork and connections between such nodes. In some embodiments and, optionally, in combination of any embodiment described above or below, the trained Al model may also be specified to include other parameters, including but not limited to, bias values / functions and / or aggregation functions. For example, an activation function of anode may be a step function, sine function, continuous or piecewise linear function, sigmoid function, hyperbolic tangent function, or other ty pe of mathematical function that represents a threshold at which the node is activated. In some embodiments and, optionally, in combination of any embodiment described above or below, the aggregation function may be a mathematical function that combines (e.g., sum, product, and the like) input signals to the node. In some embodiments and, optionally, in combination of any embodiment described above or below, an output of the aggregation function may be used as input to the activation function. In some embodiments and, optionally, in combination of any embodiment described above or below, the bias may be a constant value or function that may be used by the aggregation function and / or the activation function to make the node more or less likely to be activated.
[0075] Turning to FIG. 4. process 400 provides non-limiting example embodiments for the disclosed system. According to some embodiments, process 400 provides non-limiting embodiments for applications for which the disclosed framework (e.g., via analysis engine 200) can control, manage, and manipulate the data for the heat loss analysis.
[0076] Steps described in the figures represent both an execution of a computer algorithm and a method of implementing the system. According to some embodiments, steps 402-404 of process 400, which involve initializing the heat transfer loss analysis and collecting heat transfer loss data, can be performed by the data acquisition module 202 of analysis engine 200.
[0077] Step 406-408, which involves retrieving historical energy7performance records and / or include filtering out heat variances, can be performed by the data pre-processing module 204.16ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026
[0078] Step 410, which determines the energy envelope, can be performed by the analysis module 206.
[0079] Steps 412-414, which involve storing and outputting the energy envelope data, can be performed by the control module 208.
[0080] In some embodiments, process 400 begins with step 402, where the analysis engine 200 initializes the heat transfer loss analysis. The initialization may include configuring software settings, preparing data input channels, and establishing connections with relevant data sources.
[0081] In step 404, the analysis engine 200 collects heat transfer loss data. For example, in some embodiments, the analysis engine gathers data related to the amount of heat lost within the building envelope from a time period the HVAC system was not running one or more components (e.g., the compressor). In some embodiments, the analysis uses data from sensors 110 and / or other data sources as previously described in relation to process 300.
[0082] In step 406, the analysis engine 200 retrieves historical energy' performance records. In some embodiments, this step includes accessing and retrieving past energy' usage data for the location, providing a baseline for comparison and analysis, and / or enabling generation of longterm (e.g., months, years) energy performance trends and identifying potential areas for improvement.
[0083] In step 408, the analysis engine 200 filters out heat variances. In some embodiments, the analysis engine is configured to exclude variances due to solar gains, internal gains, and / or weather conditions, refining the data to focus on actual heat transfer losses. The filtering process ensures that the analysis is accurate and relevant to the building’s energy performance.
[0084] In step 410, the analysis engine 200 determines the energy' envelope of the location. This step involves calculating the building's overall energy efficiency and heat retention capabilities, providing insights into the effectiveness of the building envelope in minimizing energy loss. In some embodiments, the energy envelope determination includes an evaluation of a building’s ability to maintain thermal comfort by keeping heat inside during cold weather and / or preventing heat from entering during hot weather. In some embodiments, the energy envelope is used by the system to determine a properly sized HVAC system and / or control methods for reducing energy consumption, lowering utility bills, and improving overall indoor comfort. The energy' envelope determination provides insights into areas where the building may be losing energy, such as through poorly insulated walls or drafty windows. In some embodiments, the energy envelope enables the analysis engine 200 to determine improvements17ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 that can be made to enhance the building's energy efficiency, such as outputting where to add insulation, seal gaps, and / or upgrade windows, as non-limiting examples.
[0085] In step 412, the analysis engine 200 stores the energy envelope data. In step 414, the analysis engine 200 outputs the energy envelope data. In some embodiments, outputting the envelope data includes displaying the energy envelope data on a graphical user interface (GUI), and / or notification through some other medium (e.g., email). In some embodiments, output step 414 includes providing the output to the analysis engine 200 for step 308 of process 300.
[0086] For example, the data analysis performed in step 308 may incorporate the heat transfer loss data collected in step 404 and the historical energy’ performance records retrieved in step 406. Additionally, the filtering techniques used in step 408 can be applied to refine the data analysis in step 308, ensuring that the HVAC classification is based on accurate and relevant information.
[0087] FIG. 7 is a schematic diagram illustrating a client device showing an example embodiment of a client device that may be used within the present disclosure and / or the framework illustrated in FIG. 1. Client device 700 may include many more or less components than those shown in FIG. 7, such as a plurality7of computers. However, the components shown are sufficient to disclose an illustrative embodiment for implementing the present disclosure. Client device 700 may represent, for example, UE 102 discussed above at least in relation to FIG. 1.
[0088] As shown in the figure, in some embodiments, client device 700 includes one or more processors (CPU) 722 in communication with one or more non-transitory computer readable media 730 via a bus 724. Client device 700 also includes a power supply 726, one or more network interfaces 750, an audio interface 752, a display 754, a keypad 756, an illuminator 758, an input / output interface 760. a haptic interface 762, an optional global positioning systems (GPS) receiver 764 and a camera(s) or other optical, thermal or electromagnetic sensors 766. Device 700 can include one camera / sensor 766, or a plurality7of cameras / sensors 766, as understood by those of skill in the art. Pow er supply 726 provides power to Client device 700.
[0089] Client device 700 may optionally communicate with a base station (not shown), or directly with another computing device. In some embodiments, network interface 750 is sometimes known as a transceiver, transceiving device, or netw ork interface card (NIC).
[0090] Audio interface 752 is arranged to produce and receive audio signals such as the sound of a human voice in some embodiments. Display 754 may be a liquid crystal display (LCD), gas plasma, light emitting diode (LED), or any other type of display used with a computing18ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 device. Display 754 may also include a touch sensitive screen arranged to receive input from an object such as a stylus or a digit from a human hand.
[0091] Keypad 756 may include any input device arranged to receive input from a user. Illuminator 758 may provide a status indication and / or provide light.
[0092] Client device 700 also includes input / output interface 760 for communicating with external. Input / output interface 760 can utilize one or more communication technologies, such as USB, infrared, Bluetooth™, or the like in some embodiments. Haptic interface 762 is arranged to provide tactile feedback to a user of the client device.
[0093] Optional GPS transceiver 764 can determine the physical coordinates of client device 700 on the surface of the Earth, which typically outputs a location as latitude and longitude values. GPS transceiver 764 can also employ other geo-positioning mechanisms, including, but not limited to, triangulation, assisted GPS (AGPS), E-OTD, CI, SAI, ETA, BSS or the like, to further determine the physical location of client device 700 on the surface of the Earth. In one embodiment, however, client device may through other components, provide other information that may be employed to determine a physical location of the device, including for example, a MAC address, Internet Protocol (IP) address, or the like.
[0094] Mass memory 730 includes a RAM 732, a ROM 734, and / or other non-transitory storage means. Mass memory 730 illustrates another example of computer storage media for storage of information such as computer readable instructions, data structures, program modules, usage data, or other data. Mass memory 730 stores a basic input / output system (‘’BIOS”) 740 for controlling low-level operation of client device 700. The mass memory also stores an operating system 741 for controlling the operation of client device 700.
[0095] Memory 730 further includes one or more data stores, which can be utilized by client device 700 to store, among other things, applications 742 for executing transformation engine 200, and / or other information or data. For example, data stores may be employed to store information that describes various capabilities of client device 700. The information may then be provided to another device based on any of a variety of events, including being sent as part of a header (e.g., index file of the HLS stream) during a communication, sent upon request, or the like. At least a portion of the capability information may also be stored on a disk drive or other storage medium (not shown) within client device 700.
[0096] Applications 742 may include computer executable instructions which, when executed by client device 700, transmit, receive, and / or otherwise process audio, video, images, and enable telecommunication with a server and / or another user of another client device.19ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 Applications 742 may further include a client that is configured to send, to receive, and / or to otherwise process gaming, goods / services and / or other forms of data, messages and content hosted and provided by the platform associated with analysis engine 200 and its affiliates.
[0097] As used herein, the term “engine” identifies at least one software component and / or a combination of at least one software component and at least one hardware component which are designed / programmed / configured to manage / control other software and / or hardware components (such as the libraries, software development kits (SDKs), objects, and the like).
[0098] Examples of hardware elements may include processors, microprocessors, circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, application specific integrated circuits (ASIC), programmable logic devices (PLD), digital signal processors (DSP), field programmable gate array (FPGA), logic gates, registers, semiconductor device, chips, microchips, chip sets, and so forth. In some embodiments, the one or more processors may be implemented as a Complex Instruction Set Computer (CISC) or Reduced Instruction Set Computer (RISC) processors; x86 instruction set compatible processors, multi-core, or any other microprocessor or central processing unit (CPU). In various implementations, the one or more processors may be dual-core processor(s), dual-core mobile processor(s), and so forth.
[0099] Computer-related systems, computer systems, and systems, as used herein, include any combination of hardware and software. Examples of software may include software components, programs, applications, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application program interfaces (API), instruction sets, computer code, computer code segments, words, values, symbols, or any combination thereof. Determining whether some embodiment are implemented using hardware elements and / or software elements may vary in accordance with any number of factors, such as desired computational rate, power levels, heat tolerances, processing cycle budget, input data rates, output data rates, memory resources, data bus speeds and other design or performance constraints.
[0100] For the purposes of this disclosure a module is a software, hardware, or firmware (or combinations thereof) system, process or functionality', or component thereof, that performs or facilitates the processes, features, and / or functions described herein (with or without human interaction or augmentation). A module can include sub-modules. Software components of a module may be stored on a computer readable medium for execution by a processor. Modules20ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 may be integral to one or more servers or be loaded and executed by one or more servers. One or more modules may be grouped into an engine or an application.
[0101] One or more aspects of some embodiments may be implemented by representative instructions stored on a machine-readable medium which represents various logic within the processor, which when read by a machine causes the machine to execute logic to perform the techniques described herein. Such representations, known as ‘IP cores,” may be stored on a tangible, machine readable medium and supplied to various customers or manufacturing facilities to load into the fabrication machines that make the logic or processor. Of note, various embodiments described herein may, of course, be implemented using any appropriate hardw are and / or computing software languages (e.g., C++, Objective-C, Swift, Java, JavaScript, Python, Perl, QT, and the like).
[0102] For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may be downloadable from a netw ork, for example, a w ebsite, as a stand-alone product or as an add-in package for installation in an existing software application. For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may also be available as a client-server software application, or as a web-enabled software application. For example, exemplary software specifically programmed in accordance w ith one or more principles of the present disclosure may also be embodied as a software package installed on a hardware device.
[0103] For the purposes of this disclosure the term “user”, “subscriber” “provider”, “supplier”, or “customer” should be understood to refer to a user of an application or applications as described herein and / or a consumer of data supplied by a data provider. By w ay of example, and not limitation, the term “user” or “subscriber” can refer to a person who receives data provided by the data or service provider over the Internet in a browser session, or can refer to an automated software application which receives the data and stores or processes the data. Those skilled in the art wall recognize that the methods and systems of the present disclosure may be implemented in many manners and as such are not to be limited by some embodiments and examples. In other words, functional elements being performed by single or multiple components, in various combinations of hardware and software or firmware, and individual functions, may be distributed among software applications at either the client level or server level or both. In this regard, any number of the features of some embodiments described herein may be combined into single or multiple configurations, and some embodiments having fewer than, or more than, all of the features described herein are possible.21ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026
[0104] “Substantially’' and “approximately’' when used in conjunction with a value encompass a difference of 5% or less of the same unit and / or scale of that being measured.
[0105] “Simultaneously” as used herein includes lag and / or latency times associated with a conventional and / or proprietary computer, such as processors and / or networks described herein attempting to process multiple ty pes of data at the same time. “Simultaneously” also includes the time it takes for digital signals to transfer from one physical location to another, be it over a wireless and / or wired network, and / or within processor circuitry.
[0106] It is understood that the system is not limited in its application to the details of construction and the arrangement of components set forth in the previous description or illustrated in the drawings. The system and methods disclosed herein fall within the scope of numerous embodiments. The previous discussion is presented to enable a person skilled in the art to make and use embodiments of the system. Any portion of the structures and / or principles included in some embodiments can be applied to any and / or all embodiments: it is understood that features from some embodiments presented herein are combinable with other features according to some other embodiments. Thus, some embodiments of the system are not intended to be limited to what is illustrated but are to be accorded the widest scope consistent with all principles and features disclosed herein.
[0107] Some embodiments of the system are presented with specific values and / or setpoints. These values and setpoints are not intended to be limiting and are merely examples of a higher configuration versus a lower configuration and are intended as an aid for those of ordinary skill to make and use the system.
[0108] Any text in the drawings is part of the system’s disclosure and is understood to be readily incorporable into any description of the metes and bounds of the system. Any functional language in the drawings is a reference to the system being configured to perform the recited function, and structures shown or described in the drawings are to be considered as the system comprising the structures recited therein. It is understood that defining the metes and bounds of the system using a description of images in the drawing does not need a corresponding text description in the written specification to fall with the scope of the disclosure.
[0109] Furthermore, acting as Applicant’s own lexicographer. Applicant imparts the explicit meaning and / or disavow of claim scope to the following terms:
[0110] The previous detailed description is to be read with reference to the figures, in which like elements in different figures have like reference numerals. The figures, which are not22ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 necessarily to scale, depict some embodiments and are not intended to limit the scope of embodiments of the system.
[0111] Any of the operations described herein that form part of the system are useful machine operations. The system also relates to a device or an apparatus for performing these operations. All flowcharts presented herein represent computer implemented steps and / or are visual representations of algorithms implemented by the system. The apparatus can be specially constructed for the required purpose, such as a special purpose computer. When defined as a special purpose computer, the computer can also perform other processing, program execution or routines that are not part of the special purpose, while still being capable of operating for the special purpose. Alternatively, the operations can be processed by a general-purpose computer selectively activated or configured by one or more computer programs stored in the computer memory, cache, or obtained over a network. When data is obtained over a network the data can be processed by other computers on the network, e.g., a cloud of computing resources.
[0112] The embodiments of the system can also be defined as a machine that transforms data from one state to another state. The data can represent an article, that can be represented as an electronic signal and electronically manipulate data. The transformed data can, in some cases, be visually depicted on a display, representing the physical object that results from the transformation of data. The transformed data can be saved to storage generally, or in particular formats that enable the construction or depiction of a physical and tangible object. In some embodiments, the manipulation can be performed by a processor. In such an example, the processor thus transforms the data from one thing to another. Still further, some embodiments include methods can be processed by one or more machines or processors that can be connected over a network. Each machine can transform data from one state or thing to another, and can also process data, save data to storage, transmit data over a network, display the result, or communicate the result to another machine. Computer-readable storage media, as used herein, refers to physical or tangible storage (as opposed to signals) and includes without limitation volatile and non-volatile, removable and non-removable storage media implemented in any method or technology for the tangible storage of information such as computer-readable instructions, data structures, program modules or other data.
[0113] Although method operations are presented in a specific order according to some embodiments, the execution of those steps do not necessarily occur in the order listed unless explicitly specified. Also, other housekeeping operations can be performed in between operations, operations can be adjusted so that they occur at slightly different times, and / or23ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 operations can be distributed in a system which allows the occurrence of the processing operations at various intervals associated with the processing, as long as the processing of the overlay operations are performed in the desired way and result in the desired system output.
[0114] It will be appreciated by those skilled in the art that while the system has been described above in connection with particular embodiments and examples, the system is not necessarily so limited, and that numerous other embodiments, examples, uses, modifications and departures from the embodiments, examples and uses are intended to be encompassed by the claims attached hereto. The entire disclosure of each patent and publication cited herein is incorporated by reference, as if each such patent or publication were individually incorporated by reference herein. Various features and advantages of the system are set forth in the following claims.24ACTIVE 718784368v1
Claims
Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 CLAIMSWhat is claimed is:
1. A method comprising:collecting, at a location, climate data related to activity at the location, the location comprising heating, ventilation and air conditioning (HVAC) equipment, the activity corresponding to climate control of the location via the HVAC equipment;analyzing the collected climate data, the analysis based on a set of factors related to at least one of the HVAC equipment or location;determining, based on the analysis of the collected climate data, a classification of the HVAC equipment, the classification corresponding to a manner in which the HVAC equipment is capable of performing the climate control;determining, based on the determined classification, energy' controls for the HVAC equipment at the location; andcausing, based on the determined energy controls, operation of the HVAC equipment.
2. The method of claim 1, further comprising:determining a time related to the HVAC equipment having ceased running at the location; andperforming the collection of climate data for a time period based on the determined time.
3. The method of claim 2, further comprising:collecting, based on the determined time, heat transfer loss data that corresponds to an amount of heat lost within the location from the time the HVAC equipment ceased running to a current time;collecting, based on the determined time, historical records of energy performance for the location;analyzing the heat transfer loss data based on the historical records; and determining an energy envelope of the location.
4. The method of claim 3, further comprising:25ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 determining the classification based on the energy envelope, the classification providing an indication as to a retrofitting of the HVAC equipment; and communicating, with an account of the HVAC equipment, an electronic message comprising a recommendation for the retrofitting.
5. The method of claim 3, further comprising the determination of the energy controls based further on the energy envelope.
6. The method of claim 3, further comprising storing the energy' envelope within an account on a cloud, the storage enabling redemption of rebates with third parties, the storage further enabling services for the HVAC equipment at the location based on the energy envelope.
7. The method of claim 3, further comprising:filtering from the historical records and the collected climate data heat variances corresponding to at least one of solar heat gains, internal heat gains or variances due to weather; and performing the analysis of the collected historical records based on the filtering.
8. The method of claim 2, further comprising the determined time being at least a threshold period of time after the HVAC equipment stopped actively performing the climate control.
9. The method of claim 1, further comprising the set of factors selected from a group consisting of a type of the HVAC equipment, geographical region of the location and season of the year of the location.
10. The method of claim 1, further comprising the classification corresponding to the HVAC unity being under-sized for the location, over-sized for the location or right-sized for the location, such that such sizing corresponds to an energy usage of the HVAC equipment in relation to an energy threshold.
11. A system comprising:one or more computers comprising one or more processors and one or more non-transitory computer readable media, the one or more non-transitory computer readable media26ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 including program instructions stored thereon that when executed cause the one or more computers to:collect climate data related to activity' at a location, the location comprising heating, ventilation, and air conditioning (HVAC) equipment, the activity corresponding to climate control of the location via the HVAC equipment;analyze the collected climate data, the analysis based on a set of factors related to at least one of the HVAC equipment or location;determine, based on the analysis of the collected climate data, a classification of the HVAC equipment, the classification corresponding to a manner in which the HVAC equipment is capable of performing the climate control;determine, based on the determined classification, energy controls for the HVAC equipment at the location; andcontrol, based on the determined energy' controls, operation of the HVAC equipment.
12. The system of claim 11 , further comprising instructions configured to cause the one or more computers to:determine a time related to the HVAC equipment having ceased running at the location; andperform the collection of climate data for a time period based on the determined time.
13. The system of claim 12, further comprising instructions configured to cause the one or more computers to:collect, based on the determined time, heat transfer loss data that corresponds to an amount of heat lost within the location from the time the HVAC equipment ceased running to a cunent time;collect, based on the determined time, historical records of energy performance for the location;analyze the heat transfer loss data based on the historical records; anddetermine an energy envelope of the location.
14. The system of claim 13, further comprising instructions configured to cause the one or more computers to:27ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 determine the classification based on the energy envelope, the classification providing an indication as to a retrofitting of the HVAC equipment; andcommunicate, with an account of the HVAC equipment, an electronic message comprising a recommendation for the retrofitting.
15. The system of claim 13, further comprising instructions configured to cause the one or more computers to:determine the energy controls based further on the energy envelope.
16. The system of claim 13, further comprising instructions configured to cause the one or more computers to:store the energy7envelope within an account on a cloud, the storage enabling redemption of rebates with third parties, the storage further enabling services for the HVAC equipment at the location based on the energy envelope.
17. The system of claim 13, further comprising instructions configured to cause the one or more computers to:filter from the historical records and the collected climate data heat variances corresponding to at least one of solar heat gains, internal heat gains, or variances due to weather; andperform the analysis of the collected historical records based on the filtering.
18. The system of claim 17, further comprising instructions configured to cause the one or more computers to:determine a performance degradation of the HVAC equipment over time; wherein the performance degradation is a result of the loss of efficiency of an HVAC system component; and;wherein the system is configured to include the performance degradation in the determination of the classification of the HVAC equipment.
19. The system of claim 11 , further comprising instructions configured to cause the one or more computers to:28ACTIVE 718784368v1Attorney Docket No. 203863-019601ZPCT Resideo Ref. No. R214538- WO Electronically Filed: February 5, 2026 select the set of factors from a group consisting of a type of the HVAC equipment, geographical region of the location, and season of the year of the location.
20. The system of claim 11 , further comprising instructions configured to cause the one or more computers to:determine the classification corresponding to the HVAC unit being under-sized for the location, over-sized for the location, or right-sized for the location, such that such sizing corresponds to an energy' usage of the HVAC equipment in relation to an energy threshold.29ACTIVE 718784368v1