Built environment management system and method for monitoring, controlling and optimizing built environment

Abstract

Disclosed is a built environment management system (100, 200) for monitoring, controlling and optimizing a built environment. The built environment management system comprises environment monitoring unit (102, 208A) configured to monitor indoor environment; energy monitoring unit (104, 208B) communicably coupled to built environment infrastructure (218) for monitoring energy consumption thereof; and control unit (106, 216) communicably coupled to data source(s), environment monitoring unit and energy monitoring unit. Control unit is configured to: receive data from data source(s); determine set of optimal operational values corresponding to built environment infrastructure, based on data received; and adjust operational setting(s) of built environment infrastructure, based on set of optimal operational values determined, thereby optimizing built environment. Built environment management system is also configured to provide, in real-time, carbon dioxide equivalent (CO2e) data, energy consumption data and operational costing data of built environment infrastructure based on data received. Disclosed here is also a method thereof.

Description

[0001] BUILT ENVIRONMENT MANAGEMENT SYSTEM AND METHOD FOR MONITORING, CONTROLLING AND OPTIMIZING BUILT ENVIRONMENT

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to built environment management systems for monitoring, controlling and optimizing built environments. Moreover, the present disclosure relates to methods for monitoring, controlling and optimizing built environments.

[0004] BACKGROUND

[0005] With increased use of heating, ventilation, and air conditioning (HVAC) systems in buildings and structural installations, various indoor environment monitoring and controlling facilities are integrated into building management, to enhance comfort and ensure safety of occupants therewithin. However, conventional indoor environment monitoring and controlling facilities are inefficient in terms of energy efficiency. Moreover, such conventional indoor environment monitoring and controlling facilities do not take energy variables (such as electricity prices, grid mix, and load scenario that changes frequently) into account while optimizing operational settings of HVAC systems.

[0006] Notably, for the indoor environment, discomfort means overcooling or overheating. If HVAC temperature is set outside an optimal range (particularly, for a specific indoor requirement), then higher energy may be consumed, and comfort of occupants may be compromised. Typically, a 1°C deviation in temperature setting from optimal HVAC settings, leads to 2 to 15% increase in energy consumption and simultaneously increases carbon dioxide equivalent (CO2e) (Cai et al., IEEE 2019). Conventional indoor monitoring and controlling facilities are not equipped to optimize performance thereof based on energy consumption value and CO2e emission.

[0007] Furthermore, as quantifying comfort is a subjective measure, conventional indoor monitoring and controlling facilities lack proper measures to incorporate comfort as a part of built environment management. In addition, creating a control system that operates to optimize comfort, indoor environment, energy consumption, and carbon emissions requires gathering and processing large amount data, that pose risk of error.

[0008] Furthermore, use of conventional indoor monitoring and controlling facilities without optimizing operation and various operational parameters thereof, leads to high environment impact, because of the increased energy consumption of inefficient operational states of the units . Whereas conventional indoor monitoring and controlling facilities which are using standardized comfort models, still lack efficiency in managing energy consumption and thereby are missing out a potential on energy savings.

[0009] Furthermore, the majority of conventional indoor environment monitoring and controlling facilities do not consider human comfort as a parameter for adjusting various indoor facilities such as, HVAC system, lighting, appliances and so on. In this regard, conventional indoor environment monitoring and controlling facilities are configured to set a fixed HVAC temperature for heating and cooling, which typically lies within a range of 20 to 24°C. Such arrangement leaves a large fraction of occupants in the indoor environment such as commercial offices and other commercial communal spaces in thermal discomfort (Sci Rep 23684-2021). Furthermore, conventional indoor environment monitoring and controlling facilities do not incorporate demography subjective comfort parameters such as gender of occupants and metabolic rate indices of the occupants such as Resting metabolic rate (RMR) and Basal metabolic rate (BMR) into account for controlling indoor environment. For example, a standard temperature settings in an indoor environment may often be set based on male metabolic rates, which might not be as comfortable for women demographics therewithin.

[0010] Therefore, in light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks.

[0011] SUMMARY

[0012] The aim of the present disclosure is to provide a built environment management system and a method thereof, for monitoring, controlling and optimizing a built environment by incorporating real-time as well as historical data associated with various relevant parameters such as indoor temperature, outdoor temperature, indoor humidity, outdoor humidity, carbon dioxide concentration, carbon monoxide concentration, other harmful gas concentration, indoor air quality, outdoor temperature, energy consumption, occupancy, comfort of occupants and so on within a built environment. The aim of the present disclosure is achieved by a built environment management system and a method for monitoring, controlling and optimizing a built environment as defined in the appended independent claims to which reference is made to. Advantageous features are set out in the appended dependent claims.

[0013] Throughout the description and claims of this specification, the words "comprise" , "include", "have", and "contain" and variations of these words, for example "comprising" and "comprises" , mean "including but not limited to" , and do not exclude other components, items, integers, or steps not explicitly disclosed also to be present. Moreover, the singular encompasses the plural unless the context otherwise requires. In particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise.

[0014] BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG. 1A is an illustration of block diagram of a built environment management system for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure;

[0016] FIG. IB is an illustration of block diagram of a built environment management system for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure;

[0017] FIG. 2 is a schematic illustration of workflow of a built environment management system for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure; and

[0018] FIG. 3 is an illustration of a flowchart depicting steps of a method for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure.

[0019] DETAILED DESCRIPTION OF EMBODIMENTS

[0020] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practicing the present disclosure are also possible.

[0021] In a first aspect, the present disclosure provides a built environment management system for monitoring, controlling and optimizing a built environment, the built environment management system comprising: an environment monitoring unit configured to monitor an indoor environment; an energy monitoring unit communicably coupled to a built environment infrastructure for monitoring energy consumption thereof, wherein the built environment infrastructure comprises at least one of: a lighting arrangement, an amenity-appliance arrangement, a heating- ventilation-air conditioning (HVAC) arrangement; and a control unit communicably coupled to at least one data source, environment monitoring unit and the energy monitoring unit, the control unit configured to: receive data from the at least one data source; determine a set of optimal operational values corresponding to the built environment infrastructure, based on the data received; and adjust one or more operational settings of the built environment infrastructure, based on the set of optimal operational values determined, thereby optimizing the built environment, wherein the built environment management system is configured to provide, in real-time, at least one of: a carbon dioxide equivalent (CO2e) data, an energy consumption data of the built environment, an operational costing data of the built environment based on the data received.

[0022] The aforementioned built environment management system is configured to adjust one or more operational settings of the built environment infrastructure based on a historical trend of energy consumption and realtime energy consumption of such infrastructure. Thus, optimizing usage of various built environment infrastructure and ensuring energy efficiency thereof. Moreover, the aforementioned built environment management system is configured to adjust a duration of operation of such infrastructure based on a historical trend of occupancy within the built environment thereby minimizing overall energy consumption. Furthermore, the aforementioned built environment management system is configured to incorporate comfort of occupants within the built environment while determining the set of optimal operational values for operating the built environment infrastructure. Furthermore, the aforementioned built environment management system is configured to integrate and utilize Machine Learning (ML) model to predict occupancy, comfort of occupants, energy consumption and so on. The ML model may be further implemented to periodically revaluate and upgrade performance of the built environment management system, thereby ensuring that the built environment infrastructure operate efficiently and have a longer service life. Thus, minimizing environmental impact and allowing the built environment to achieve sustainable development goals. Additionally, the aforementioned built environment management system is configured to maintain thermal inertia of the built environment by monitoring and adjusting thermal environment within the built environment. Thus, the aforementioned built environment management system aids in maintaining a constant indoor temperature despite changes in an outdoor environment to maximise user comfort. Furthermore, the aforementioned built environment management system is configured to establish a connection to an Application Programming Interface (API) and / or smart grid to receive real-time price of electricity based on grid data to optimize power consumption of the built environment to minimised electricity bill (as price of electricity varies during different time of a day) or CO2e (which also varies during different time of the day). Furthermore, the built environment management system is configured to implement multiobjective optimisation for energy consumption and CO2e for consequently enhancing energy efficiency as well as economic efficiency of the built environment. For example, an equal amount of power saved at certain time let us say 1 PM means a different amount of economic (cost) saving and emission savings than if the same amount of power would be saved at let us say 5 PM due to difference in the price of electricity and the aforementioned built environment management system may optimize the energy consumption at 1 PM and at 5 PM in a manner to provide best possible built environment management with best possible economic solution.

[0023] In a second aspect, the present disclosure provides a method for monitoring, controlling and optimizing a built environment, the method comprising: monitoring, using an environment monitoring unit, an indoor environment; monitoring, using an energy monitoring unit, energy consumption of a built environment infrastructure coupled to the energy monitoring unit, wherein the built environment infrastructure comprises at least one of: a lighting arrangement, an amenity-appliance arrangement, a heating- ventilation-air conditioning (HVAC) arrangement; receiving data from at least one data source; determining a set of optimal operational values corresponding to the built environment infrastructure, based on the data received; and adjusting one or more operational settings of the built environment infrastructure, based on the set of optimal operational values determined, thereby optimizing the built environment; wherein the method comprises providing, in real-time, at least one of: a carbon dioxide equivalent (CChe) data, an energy consumption data of the built environment infrastructure, an operational costing data of the built environment infrastructure, based on the data received.

[0024] The aforementioned method allows optimized operation of built environment infrastructure. Moreover, the method enables optimization of energy consumption by adjusting the one or more operational settings of the built environment infrastructure. Furthermore, the method provides real-time CO2e data, the energy consumption data of the built environment and the operational costing data for assessing quality and performance of the built environment infrastructure.

[0025] Throughout the disclosure, the term "built environment" refers to manmade or modified structures that provide occupants therewithin, facilities for living, working, and recreational activities. For example, built environment may refer to an office, a commercial establishment, a residential complex, a public infrastructure (bus station, railway station, metro station), a healthcare facility, a recreational facility, a sports complex, and so on. The term "occupant" as used herein refers to a person who is inclined to spend their time within the built environment, and an animal as well as plants reside within the built environment.

[0026] The term "carbon dioxide equivalent (CC^e)" refers to a unit of measurement where a different greenhouse gases (GHGs) emitted is converted to an equivalence of carbon dioxide (CO2) emitted. For example, 1 kg of methane emitted can be expressed as 29.8 kg of CO2e, and 1 kg of nitrous oxide (N2O) is equal to 298 kg of CO2e. It may be appreciated that the CO2e data is an essential parameter in estimating sustainability of a built environment.

[0027] Throughout the disclosure, the term "built environment management system" refers to a system configured to monitor, assess, control, and optimize, operation as well as performance of various facilities, namely the built environment infrastructure, within the built environment. The built environment management system may be configured to work as a standalone system, or to work in integration with an existing management system within the built environment. It may be appreciated that the built environment management system is configured to optimize a quality of the built environment by enhancing comfort of occupants therewithin while optimizing relevant energy consumption. The built environment management system is also configured to provide the CO2e data for the built environment in real-time to evaluate sustainability of the built environment and use the CO2e data to optimize selfperformance. The built environment management system is also configured to provide the energy consumption data and the operational costing data of the built environment infrastructure to evaluate performance of the built environment infrastructure for optimally managing of economical as well as operational aspects of the built environment, while ensuring utmost user comfort.

[0028] Throughout the disclosure, the term "at least one user" refers to the occupant as well as a person or an operator having authorized access to adjust and modify the one or more operational parameters of the built environment infrastructure utilizing the aforementioned built environment management system. For example, at least one user may be a houseowner who is away from home and is utilizing the aforementioned built environment management system to regulate temperature of the house remotely or turn on a ventilation unit to circulate stale indoor air while coming from a vacation before reaching house and so on. In this regard, the aforementioned built environment management system may also be configured to provide access to at least one user to control one or more operational settings of the built infrastructure, manually and remotely, using a remote-control feature such as internet of things (loT).

[0029] Throughout the disclosure, the term "built environment infrastructure" refers to facilities provided for improvement and comfort of occupants within the built environment. In this regard, for example, the built environment infrastructure refers to comprises at least one of: a lighting arrangement, an amenity-appliance arrangement, a heating- ventilationair conditioning (HVAC) arrangement. It may be appreciated that the built environment infrastructure is coupled to external electrical power supply facilities (such as electrical grid, solar panels, diesel generators, inverters, and so on). The built environment infrastructure is designed to enhance the built environment. In this regard, it may be appreciated that the built environment infrastructure may also refer to standalone HVAC units, central HVAC units, heat pumps and so on. It may be appreciated that the built environment management system may also be configured to work to manage the built environment infrastructure which may be standalone HVAC units or central HVAC units.

[0030] The term "one or more operational settings" as used herein refers to settings at which the built environment infrastructure is configured to operate. For example, one or more operational settings may refer to at least one of: a temperature setting of an air conditioning unit, a mode setting of the HVAC unit from cooling, to heating, to ventilation, to automatic setting, a speed setting of a ventilation unity, a humidity setting for a humidifier unit, a brightness (lux) setting for light arrangements (for example, set light brightness to a certain percentage), a run-time setting for amenity-appliance arrangement (for example, a duration setting of an odour remover machine for spraying perfume, or a triggering an arrangement for auto cleaning of bathroom after a specific time interval) and so on.

[0031] Throughout the disclosure, the term "environment monitoring unit" refers to an arrangement of various monitoring elements, namely at least one sensor, to assess the indoor environment and provide relevant measurements of at least one parameter corresponding to the indoor environment. Throughout the disclosure, the term "indoor environment" refers to microenvironment within the built environment. The phrase "at least one parameter corresponding to the indoor environment" as used herein, refers to indoor occupancy, indoor temperature, indoor humidity, indoor carbon dioxide (CO2) level, indoor carbon monoxide (CO) level, particulate matter concentration, volatile organic compounds (VOC) concentration, indoor location tracking, indoor air quality, indoor light and sound comfort levels, gas leak, indoor air pressure, indoor air velocity and so on.

[0032] It may be appreciated that the indoor occupancy may also be defined on basis of demographics in the built environment, for example, a ratio, a percentage, a numeral data on male and female occupants within the built environment.

[0033] Throughout the disclosure, the term "energy monitoring unit" refers to an arrangement of various elements working in a cohesive manner, and which are communicably coupled to the built environment infrastructure, in order to monitor the energy consumption thereof.

[0034] Throughout the disclosure, the term "control unit" refers to a component of the built environment management system which is configured to perform activities such as: receiving data (pertaining to the built environment, energy consumption of the built environment infrastructure, and outdoor environment), analyzing the data received, determining set of optimal operational values parameters, and adjusting one or more operational settings of the built environment infrastructure. The control unit advantageously optimizes the built environment by adjusting one or more operational settings of the built environment infrastructure, based on the set of optimal operational values parameters, thereby improving comfort to at least on user therewithin. It may be appreciated that the control unit is coupled to the at least one data source, the energy monitoring unit, the environment monitoring unit and the built environment infrastructure, to receive the data and adjust the one or more operational settings of the built environment infrastructure. Preferably, the control unit is configured to receive data from the at least one data source. Optionally, the control unit may be a microprocessor, a microcontroller, a on chip control unit, a central processing unit, or any such suitable arrangement. Optionally, the control unit may utilize at least one adjustment arrangement to adjust the one or more operational settings of the built environment infrastructure, wherein the at least one adjustment arrangement may be, for an example, an actuator, a thermostat and so on. Optionally, the control unit may be communicably coupled to the existing management system, for example, a lighting adjustment system such as digital addressable lighting interface (DALI®).

[0035] Optionally, the at least one data source is implemented as at least one of: a cloud data source, the environment monitoring unit and the energy monitoring unit, and wherein the data from the at least one data source pertains to at least one of: a comfort metric, at least one parameter corresponding to the indoor environment and at least one parameter related to an outdoor environment. In this regard, the term "at least one data source" refers to an input source coupled to the control unit. Optionally, the at least one data source may be a local data source namely, the environment monitoring unit and the energy monitoring unit or a cloud data source such as a cloud storage connected to at least one of: a remote server, a third-party service provider server and so on. Optionally, the environment monitoring unit and the energy monitoring unit, both are configured to be communicably coupled to the at least one data source and relay the data pertaining to the at least one parameter corresponding to the indoor environment as well as energy consumption thereto. Optionally, alternatively, the control unit may directly receive such data from the environment monitoring unit and the energy monitoring unit. Optionally, the cloud data source is configured to collect data from an associated application programming interface (API) via a suitable form of information exchange. For example, the suitable form of information exchange may refer to using java script notion (JSON) or any such suitable script as commands, request and so on. The technical advantages of receiving data from the at least one data source include enabling remote control, providing real-time updates, enhancing data security, and reducing hardware requirements, which in turn minimizes energy consumption and operational costs. The term "operational cost" as used herein refers to an economic parameter associated with the operation of the built environment infrastructure such as the HVAC system, the lighting arrangement and the amenity-appliances arrangement. The operational cost may include electricity consumption cost (electricity bill), wear-and-tear cost (maintenance) and so on.

[0036] It may be appreciated that the term "comfort metric" as used herein refers to a value associated with comfort of at least one user within the built environment. Optionally, the comfort metrics is expressed in terms of a numeral, a colour code, a percentage, or any such suitable indicators based on comfort parameters such as a thermal comfort, breathability of indoor air (corresponds to air quality) and so on. For example, hot or cold feeling may be expressed on a scale of 0 to 10, may be expressed in terms of red colour for feeing hot, yellow for feeling fine or blue for feeling cold, or may be expressed in a percentage. For another example, the indoor air may be dry or humid and this affects comfort of the occupant, and the corresponding comfort parameter may be expressed in a numeral scale or percentage.

[0037] It may be appreciated that the phrase "at least one parameter corresponding to an outdoor environment" as used herein refers to values corresponding to various environmental factors associated with an outdoor environment. The at least one parameter corresponding to the outdoor environment may refer to at least one of: outdoor temperature, outdoor humidity, outdoor air quality, outdoor air pressure, outdoor light, wind profile, weather condition and so on. Optionally, the at least one data source is adapted to receive information associated with the at least one parameter corresponding to the outdoor environment, via the API which may provide various aspects of outdoor environment, such as current and historical data pertaining to weather, outdoor temperature, and photoperiod of a particular geographical location.

[0038] Preferably, the control unit utilizes data received from the at least one data source to determine the set of optimal operational values corresponding to the built environment infrastructure. The term "optimal operational values" as used herein refers to optimum values for operating the built infrastructure. The set of optimal operation values are determined in order to adjust operation of the built environment infrastructure to regulate at least one of: an indoor temperature, indoor humidity, indoor ventilation and so on within the built environment to consequently enhance comfort of the at least one user therewithin, while minimizing energy consumption to provide such comfort. Optionally, by adjusting the one or more operational settings of the built environment infrastructure, operation of the built environment infrastructure can be adjusted.

[0039] It may be appreciated that the based on the set of optimal operational values determined, the one or more operational settings of the built infrastructure are adjusted. In this regard, the control unit is configured to perform such adjustment to regulates operation of various units of the built environment infrastructure such as, lighting arrangement, the amenity-appliance arrangement, and the heating- ventilation-air conditioning (HVAC) arrangement. Optionally, the various units of built environment infrastructure are independently controlled as it may be optimal to adjust a specific unit in a specific manner as per specific operational settings as required. In this regard, each of the various units will be controlled in a specific manner or may also be controlled as per a zone where they are operational. The term "zone" as used herein refers a section of defined boundary within the built environment, for example, a living room in an apartment, a meeting hall in an office, and so on. It may be appreciated that the set of optimal operational values may be redefined after a predefined time period which is set automatically by the control unit or manually by the at least one user within the built environment.

[0040] Optionally, the environment monitoring unit comprises an interface configured to receive the comfort metric from at least one user within the indoor environment. The term "interface" refers to an arrangement capable of performing as a medium of communication between at least one user and component of the built environment management system, namely, the environment monitoring unit. In this regard, the interface may refer to a keypad, a button pad, a button press, a QR. code scan, a digital interface, a monitor, a liquid crystal display (LCD), a light emitting diode (LED), a touch screen, any such display having a selectable option displayed thereon, a web-form, and so on. It may be appreciated that at least one user may input their comfort (based on comfort parameters) via the interface. The technical advantage is integration of user-specific information pertaining to comfort into determination of the set of optimal values, thereby optimizing operation of the built environment infrastructure.

[0041] Optionally, the environment monitoring unit comprising at least one sensor configured to measure and provide, in real-time or at a predefined interval, a thermal inertial data of the built environment, at least one parameter corresponding to the indoor environment selected from at least one of: indoor temperature, indoor humidity, indoor CO2 levels, indoor occupancy, indoor carbon monoxide (CO) level, particulate matter concentration, volatile organic compounds (VOC) concentration, indoor location tracking, indoor air quality, indoor light and sound comfort levels, gas leak, indoor air pressure, indoor air velocity; and the cloud data source configured to provide at least one parameter corresponding to an outdoor environment selected from at least one of: outdoor temperature, outdoor humidity, outdoor air quality, outdoor air pressure, outdoor light, wind profile, weather condition. In this regard, the at least one sensor may be at least one of: a temperature sensor, a humidity sensor, a hygrometer, a motion sensor, vibration sensor such as an accelerometer, an occupancy sensor, an infrared sensor, a chromatic confocal sensor, a light sensor, an optical sensor, an CO2 concentration measurement sensor, a CO concentration measurement sensor, a non-dispersive infrared (NDIR.) sensors, a multigas detection sensor, dosimeters, airflow meters, acoustic sensors and so on. The term "thermal inertia" as used herein refers to thermal state of the built environment. It may be appreciated that thermal inertial may be defined in terms of a comparison between indoor temperature and outdoor temperature. The thermal inertia may be affected by at least one parameter corresponding to indoor environment. By utilizing thermal inertia data of the built environment, the aforementioned built environment management system achieves the technical advantage of maximized user comfort with optimized energy efficiency, CO2e and operational cost.

[0042] Optionally, it may be appreciated that the at least one sensor monitors and measure the at least one parameter corresponding to the indoor environment, which are essential as they specify an ambient environment of the built environment at a specific time which affect the comfort parameters of the occupant. For example, increased humidity within the indoor environment may let the occupant feel hotter and more sweltered, therefore negatively affecting their thermal comfort. For another example, increased CO2 concentration in indoor air may affect wellbeing of the occupant making them breathless. In such cases the dehumidification may be required, or ventilation may be required to enhance comfort of the occupant. However, when the humidity is lowered, or the ventilation has led to decrease in CO2 concentration, then prolonging operation of a dehumidifier or ventilator will only result in unnecessary energy consumption and may degrade service life of such utilities. Thus, updated data on the at least one parameter corresponding to the indoor environment is required to re-evaluate the set of optimal operational values to adjust the one or more operational settings of the built environment infrastructure.

[0043] Optionally, the at least one sensor is configured to transmit data measured (pertaining to at least one parameter corresponding to the indoor environment) to the control unit of the built environment monitoring system directly via wireless connection or via wired connection. For example, the at least one sensor may transmit data wirelessly via wireless fidelity (WiFi) or EnOcean using a suitable transmission protocol such as message queuing telemetry transport (MQTT) protocol

[0044] Moreover, optionally, the environment monitoring unit is configured to measure, in real-time or at the predefined interval, at least one parameter corresponding to the indoor environment, by utilizing the at least one sensor. The term "real-time'' as used herein refers to a time interval in a range of 0 to 10 second, within which measurement of the at least one parameter corresponding to the indoor environment is performed and the data measured is relayed to the built environment management system (specifically the control unit) for further processing in the unit itself or for transfer of the data to the cloud. In this regard, the real-time may refer to the data measured being relayed within time interval ranging from 0, 0.01, 0.02, 0.03, 0.04, 0.06, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 3, 4, 5, 6, 7, 8 or 9 seconds up to 0.01, 0.02, 0.03, 0.04, 0.06, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 seconds. The predefined interval refers to a time interval of 10 to 30 minutes. In this regard, the predefined interval may refer to data being measured and relayed repetitively after an time interval ranging from 10, 11, 12, 13, 14, 15, 16,17,18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, or 29 minutes up to 11, 12, 13, 14, 15, 16,17,18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 or 30 minutes. The technical advantage is redefining one or more operational settings of the built environment infrastructure based on real-time and accurate data thereby providing multi-objective optimization such as optimizing energy consumption, CO2e, and operational cost while maximizing user comfort.

[0045] Optionally, it may be appreciated that the environment monitoring unit may also utilize at least one sensor implemented as an image sensing device, and wherein the image sensing device is configured to monitor demographics-based occupancy of the indoor environment, and the environment monitoring unit may relay the data corresponding to demographics-based occupancy to the at least one data source.

[0046] Moreover, the cloud data source is configured to acquire values corresponding to the at least one parameter corresponding related to the outdoor environment via the API and provide the same to the control unit for further processing. The technical advantage is improving accuracy of determination of the set of optimal operational values thereby optimizing operation of built environment infrastructure.

[0047] Optionally, built environment management system further comprises an outdoor environment monitoring unit, communicably coupled to the at least one data source, configured to monitor the at least one parameter corresponding to the outdoor environment. In this context, the outdoor environment monitoring unit refers to an arrangement of various measuring and monitoring elements working cohesively to monitor and measure the at least one parameter corresponding to the outdoor environment. Optionally, the outdoor environment monitoring unit may be arranged on a site near the built environment. Optionally, the outdoor environment monitoring unit may be arranged within a distance range of 0 to 10 meters from the built environment. It may be appreciated that the outdoor environment monitoring unit may also be arranged within a premises of the built environment. The technical advantage is lowering chances of data loss due to malfunctioning or downtime of a server associated with the API.

[0048] Optionally, the energy monitoring unit is further configured to measure, in real-time or at a predefined interval, at least one of: one or more original operational settings, operational duration, performance data of the built environment infrastructure. In this regard, the phrase "one or more original operational settings" refers to a current value at which the built infrastructure are operating. The term current value corresponds to a specific time when the built environment management system initiates a step of determining the set of optimal operational values. For example, at a specific time of 10 am, a temperature setting of a heating unit is set at 30 degrees Celsius, a temperature setting of an air conditioning unit is set at 25 degrees Celsius, a humidifier unit is at on state, a fan speed setting of a ventilation unit is set at highest speed and so on. Such operational settings are defined as the one or more original operational settings, when the built environment management system starts working and determining the set of optimal operational values based on comfort metrics, indoor conditions (corresponding to at least one parameter related to indoor environment) and outdoor conditions (corresponding to at least one parameter related to outdoor environment). The built environment management system then modifies the one or more original operational settings to one or more operational settings based on the set of optimal operational values to enhance user-comfort within the built environment. Optionally, the term "operational duration" refers to a time duration for which the built environment infrastructure operates. For example, a lighting arrangement in an office may remain operational for 12 hours, an appliance arrangement and / or and a HVAC arrangement in the same office may remain functional for 8 hours. The term "performance data of the built environment infrastructure" refers to operational efficiency the built environment infrastructure, such as data on a frequency of unintended shut down, cooling or heating efficacy, speed of fan in ventilation unit, and so on. For example, an efficiency of air conditioning unit in the built environment. The technical advantage is, information on one or more original operational settings, the operational duration, and the performance data of the built environment infrastructure enable the built environment management system to improve accuracy of determining an optimal operational settings to optimize both energy consumption and user-comfort. Moreover, such information allows determining health of the built environment infrastructure.

[0049] Optionally, the built environment management system further comprising a server communicably coupled to the control unit, the environment monitoring unit, the energy monitoring unit a smart grid, and a data repository. In this regard, the server is configured to receive data from the control unit, the environment monitoring unit, and the energy monitoring unit, in real-time and / or at the predefined interval. The server is also configured to communicate with the smart grid to track electricity costs, in real-time and / or at the predefined interval thereby enabling the built environment management system to optimize of energy consumption, CO2e savings, operational cost of the built environment infrastructures accordingly, based on varying price of electricity during different time of the day. The data repository may be a local data repository or cloud-based data repository which may be configured to serve as an active or a backup data storage facility. For example, cloud-based data repository may be, but not limited to, AWS S3 Buckets, AWS Timestream Databases and any such suitable cloud-based data repository. The technical advantage of coupling the built environment management system to the server is integration with smart grid to promote sustainable development, while optimizing energy consumption of the built environment. Another technical advantage is eliminating risk of data loss as the data from the control unit, the environment monitoring unit, the energy monitoring unit and the smart grid can be stored in the data repository for future retrieval when required.

[0050] Optionally, the data repository is configured to receive, in real-time or at a predefined interval, and store therein at least one of: the data received from the environment monitoring unit, the energy monitoring unit and the smart grid. In this regard, the server, which is communicably coupled with the control unit, the environment monitoring unit, the energy monitoring unit and the smart grid, is configured to store data received therefrom. Optionally, alternatively, the control unit may directly store such data on the data repository, as the data received from the environment monitoring unit, the energy monitoring unit and the smart grid are utilized by the control unit while determining the set of optimal operational values. The technical advantage is eliminating risk of data loss. Another technical advantage is ensuring privacy and security of data to cater to requirement of the at least one user.

[0051] Optionally, the server is configured to operate the control unit to adjust the one or more operational settings of the built environment infrastructure, based on the data stored in the data repository and smart grid data. In this regard, the server may be utilized by the at least one user to remotely control operation of the built environment management system. It may be appreciated that the server operates the control unit of the built environment management system to adjust, modify one or more operational settings of the built environment infrastructure. For example, the built environment management system is integrated in residential premises of the at least one user. While returning from office, the at least one user may want to turn on an air conditioning unit at the residential premises, with a temperature setting of 20 degrees Celsius. In such case, the at least one user may utilize the server to operate the control unit of the built environment management system to turn the air conditioning unit on and set the temperature setting to required temperature of 20 degrees Celsius. The technical advantage is implementation of remote control for enhanced user experience of the at least one user.

[0052] Optionally, the server is configured to generate at least one digital twin corresponding to comfort metrics and the built environment infrastructure, based on the data stored in the data repository. In this regard, the term the "digital twin" as used herein refers to an algorithm such as a supervised machined learning model trained on historic or simulated data pertaining to the built environment and user preferences of the at least one user residing in the built environment. In other words, the at least one digital twin may refer to a virtual model of the built environment and built environment infrastructure (such as HVAC, lighting, and amenity-appliance arrangement) or a system within the built environment, a process such as management of built environment infrastructure and so on. In this regard, the at least one digital twin is configured to be connected to its real-world counterpart (i.e., the built environment, the built environment infrastructure, the system within the built environment, the process) by a 2-way flow of real-time data, replicating or mimicking aspects such as power consumption of HVAC system at particular temperature setpoints, solar radiation, outside temperature and / or relative humidity, type of ventilation unit, heating system of a heat pump, temperature settings, humidity settings, operation duration. The at least one digital twin may run locally in the data repository on an edge computing device, or remotely in the cloud such as in AWS Sagemaker or AWS Lambda. Optionally, the at least one digital twin corresponding to comfort metrics and the built environment infrastructure, is configured to mimic the comfort parameters of the at least one user based on the data stored in the data repository. Similarly, the at least one digital twin is configured to virtually create a digital replica of the built environment infrastructure, based on the data stored in the data repository. The technical advantage is enabling the server to directly adjust the one or more operational settings by operating the control unit, which may be performed in case of any fault in receiving the data from environment monitoring unit or any other component of the built environment management system. In this regard, it may be appreciated that the technical advantage of the at least one digital twin is that the at least one digital twin aids in virtually simulating test decisions pertaining to management of the built environment infrastructure based on the comfort metric, one or more operational parameters of the built environment infrastructure before actual adjustment to understand how different test decisions might affect real- world counterpart.

[0053] It may be appreciated that the at least one digital twin may also incorporate data pertaining to difference in outdoor temperature and indoor temperature, a cyclical encoding of hour, humidity, CO2levels, and a binary encoding of occupancy during weekend and weekdays are used as input features. Optionally, the at least one digital twin may also incorporate binary encoding during working hours and outside working hours, and binary encoding pertaining to the particular use of a room or zone within the built environment, namely, a shared facility or a meeting room and so on. The at least one digital twin is configured to utilize various methodology such as log transformation and scaling, to make such input ingestible. Optionally, the at least one digital twin comprises a first digital twin corresponding to the comfort metrics. The first digital twin leverages the ability of neural networks to uncover complex relationships between features to replicate an overall sentiment of the at least one user corresponding to at least one parameter corresponding to the indoor environment. For example, the first digital twin may mimic the comfort metrics of the at least one user based on indoor temperature, indoor humidity, and CO2levels. Optionally, the first digital twin may also mimic the comfort metrics by corelating a comfort of user corresponding to at least one parameter corresponding to the outdoor environment, for example, outdoor temperature. Optionally, the at least one digital twin comprises a second digital twin incorporating a neural network to replicate the built environment infrastructure to estimate energy consumption thereof. The second digital twin is configured to estimate the energy consumption in real time or in the predefined time period. For example, the second digital twin estimates the energy consumption of the built environment infrastructure in a time interval of 15 minute. Moreover, optionally, the second digital twin may also implement an algorithm trained on historic data or simulated data of the built environment infrastructures (such as data on HVAC system) in combination with the thermal inertia of the built environment to predict the energy consumption for given a set of environmental parameters (at least one parameters corresponding to both indoor and outdoor environment) and a given temperature setpoint I operational mode of the built environment infrastructures.

[0054] Optionally, the built environment management system further comprising a digital dashboard, corresponding to the at least one digital twin, configured to display to the at least one user, in real-time, one or more operational settings of the built environment infrastructure. In this regard, the digital dashboard may refer to a platform, a display board, and so on configured to display data pertaining to the comfort metrics and one or more operational settings of the built environment infrastructure thereon. The digital dashboard may display the data as at least one of: texts, numbers, graphics (such as bar charts, line graphs, pie charts, and other visual elements) and any combination thereof. The digital dashboard provides the at least one user with a quick and comprehensive overview of relevant information on the built environment infrastructure. Moreover, the digital dashboard provides an intuitive interface, enabling the at least one user to override automated settings and manually control the built environment infrastructure remotely should they wish to do so. Thereby ensuring complete digital integration of the built environment infrastructure (namely, the lighting arrangement, the amenity-appliance arrangement, the heating- ventilation-air conditioning (HVAC) arrangement) and allowing at least one user to observe and manage one or more operational settings of the built environment infrastructure in real-time via the server, utilizing a suitable internet connection. The technical advantage is digital dashboard enables the at least one user to monitor, analyze, and manage data in real-time, aiding in decision-making and tracking performance of built environment infrastructures.

[0055] Optionally, the built environment management system further comprising at least one Machine Learning (ML) model for optimizing performance of the built environment management system, wherein the at least one ML model is trained based on historical data stored in the data repository. In this regard, the at least one ML model may be utilized as a multi objective optimisation model trained based on the data corresponding to at least one digital twin. The at least one ML model may also be utilized as reinforcement learning model which is configured to determine the optimal operational setting for the built environment infrastructure by trying different setpoints for the built environment infrastructure utilizing at least one suitable algorithm. Specifically, the at least one ML model is configured to recompute outcome (such as energy consumption, comfort metrics) for each of the different set points to determine the optimal operational setting for the built environment infrastructure in order to maximise comfort and minimise energy consumption. The at least one algorithm may be a genetic evolutionary algorithm to identify a set of non-dominated reference points, where improving one objective (i.e., user-comfort) would not necessarily worsen another (i.e., energy consumption). In this regard, the at least one algorithm generates a plurality of new solutions on the basis of a favourable solution in current time frame and one or more original operational settings of the built environment infrastructure, by introducing possible modification (mutations) and combinations (crossovers). The at least one ML model is configured to opt for a best possible solution amongst the plurality of new solutions until a predefined stopping criterion is reached. The predefined stopping criteria refers to an optimized solution for both usercomfort and the energy consumption. After obtaining the optimal solution, the at least one ML model is configured to implement multicriteria decision-making methodology to select a single, balanced solution. For example, having determined an optimal solution corresponding to the built environment, such as a suitable value of humidity and temperature therewithin by utilizing the at least one ML model, the built environment management system may properly adjust the HVAC arrangement settings to maximize the user-comfort with optimized energy consumption. The technical advantage is obtaining an accurate and optimized operation of the built environment infrastructure.

[0056] Moreover, the at least one ML model is also configured to utilize variables (such as time frame of a day, a week, a month, a season, a geolocation, a weather forecast and so on) into account to optimise the operation of built environment infrastructure for optimal user-comfort and energy consumption in anticipation of occupancy and / or electricity price and / or grid emission factor changes. In this context the at least one ML model is communicably coupled to the control unit and is configured to operate the control unit to adjust the one or more operational settings of the built environment infrastructure. For example, the at least one ML model is also configured to operate the control unit to pre-heat or pre-cool buildings before expected occupancy i.e., arrival of the at least one user, or basis of a density of occupancy (i.e., number of users within the buildings), to manage energy consumption and the user-comfort. For another example, the at least one ML model may pre-heat the buildings before the at least one user occupies the building, at a time when electricity fare rate is forecasted to be cheaper. Furthermore, the at least one ML model may be re-trained periodically to delivery optimal performance for a specific built environment based on the data stored in the data repository. Furthermore, the built environment management system may incorporate a first ML model trained on historical data configured to mimic a comfort metric corresponding to user-comfort corresponding to the at least one parameter related to indoor environment, a second ML model trained on historical data configured to mimic the built environment infrastructure (such as the lighting arrangement, the amenity-appliance arrangement, the HVAC arrangement), and third ML model configured to perform multi objective optimisation by taking the outcome of the first and the second ML model as input to provide a best possible solution for optimization of the built environment. The technical advantage of using the at least one ML model is optimization of performance of the built environment management system.

[0057] Optionally, the built environment management system is configured to utilize the at least one ML model to: predict the comfort metrics and occupancy based on at least one of: a historical data corresponding to the at least one parameter corresponding to the indoor environment, a demographics within the built environment; predict energy consumption of the built environment infrastructure by analyzing the data received from the energy monitoring unit; and operate the control unit to adjust the one or more operational settings of the built environment infrastructure.

[0058] In this regard, the at least one ML model is configured to analyze the historical data corresponding to the at least one parameter corresponding to the indoor environment measured by the environment monitoring unit to identify a trend in comfort metrics and occupancy within the built environment based on various factors such as the time frame of day, the season, the time frame of week (for example, which day of the week, Sunday or Monday and so on), the month (for example, December or March) and so on. The at least one ML model is also configured to predict the comfort metrics and occupancy based on the demographics within the built environment, for example, ratio of male and female occupants. Optionally, the at least one ML model may obtain data on demographics from the at least one data source or the data repository. Based on the data the at least one ML model may predict when the built environment may be densely occupied, sparsely occupied or unoccupied. Moreover, the at least one ML model is configured to analyse the data received from the energy monitoring unit and identify a trend of energy consumption, thereby predicting energy consumption of the built environment infrastructure for a specific time, day, week, month and so on. Based on predictions on occupancy and energy consumption, the at least one ML model is configured to operate the control unit in order to adjust the one or more operational settings of the built environment infrastructure. For example, the at least one ML model may recognize trend that on Sundays the built environment (if an office premises) is unoccupied, therefore there would not be any need to turn on air conditioning unit in lounge, workspace. However, based on pattern of energy consumption the at least one ML may predict that a server room is consuming more energy. So, it may determine that even on Sundays the server room will remain operational. Based on both these predictions the at least one ML model may determine that on Sundays, only server room air conditioning unit has to be turned on, thereby optimizing energy consumption. The technical advantage is based on such prediction, the built environment infrastructure may be operated in a suitable manner to optimize the energy consumption, CO2e, and operational cost.

[0059] It may be appreciated that the ML model is pre-trained and is configured to implement evolutionary learning methodology to provide prediction on optimal comfort metrics and occupancy pattern or trend for a specific built environment, over time. The ML model predicts whether there is occupancy in the zone of the built environment in binary encoding at a specific time. The ML model may turn on the built environment management system if a likelihood of occupancy is predicted to be high at a certain time of a day of a week. In this regard, the ML model predicts the time it takes for the zone to reach a certain target temperature based on the thermal inertia by analysing historical data. The technical advantage is automatically turning on the built environment management system in advance of predicted occupancy thereby ensuring maximized user comfort.

[0060] Optionally, the ML model may be a multi-model arrangement comprising a first model which is a supervised time-series ML model, and a second model which is a reinforcement ML model. By implementing such multimodel arrangement, the accuracy in prediction is improved thereby optimizing built environment management.

[0061] It may be appreciated that the at least one digital twin, and the at least one ML model may be pre-trained before deployment, based on a sitespecific data for a specific built environment or aggregated data. They are also configured to be re-trained periodically to delivery optimal performance for the specific space.

[0062] Optionally, the built environment management system further comprising a feedback unit, communicably coupled to the control unit, for receiving, in real-time, a user feedback, for optimizing the built environment. In this regard, the feedback unit may refer to an interactive platform to enable the at least one user to provide their feedback pertaining to comfort, operational efficiency, and so on. The feedback unit may also be configured to enable the at least one user to set one or more operational settings of the built environment infrastructure ahead of time. For example, the at least one user may provide their feedback on how cold or hot they may be feeling. For another example, the at least one user may set a time when the air conditioning unit should be turned on. The technical advantage is integration of inputs from at least one user to optimize automation of built environment infrastructure.

[0063] In an embodiment, the built environment management system comprises a cloud-based management unit communicably coupled to the environment monitoring unit, the energy monitoring unit and at least one data source, and the control unit. Optionally, the cloud-based management unit is configured to collect data pertaining to at least one parameter corresponding to the indoor environment, at least one parameter related to an outdoor environment and energy consumption of the built environment infrastructure from the environment monitoring unit, at least one data source and the energy monitoring unit respectively. Optionally, the cloud-based management unit is also configured to determine a set of optimal operational values corresponding to the built environment infrastructure, based on the data received and to transmit commands to the control unit to adjust one or more operational settings of the built environment infrastructure, based on the set of optimal operational values determined, thereby optimizing the built environment. Moreover, the cloud-based management unit is adapted to utilize the at least one ML model to determine a set of optimal operational values corresponding to the built environment infrastructure and to transmit commands to the control unit 206 to adjust one or more operational settings of the built environment infrastructure based on the set of optimal operational values determined.

[0064] In an embodiment, the built environment management system is configured to control the built environment infrastructure, relay the data to the at least one data source and store the data in the data repository by utilizing a cloud service, for example, AWS Lambda. The technical advantage is access to a holistic view of built environment, built environment infrastructure status and performance while providing seamless operational control of built environment infrastructure. Moreover, the cloud service may be utilized to connect with other servers or cloud services without any complexity. Furthermore, such approach may be economically beneficial while managing and optimizing built environment remotely.

[0065] In an embodiment, the built environment management system is configured to integrate with a conventional built environment infrastructure, namely legacy infrastructure, by utilizing communication protocols. For example, communication protocols may be building automation and control networks (BACnet), Modbus, KNX, local operating network (LonWork), Controller Area Network (CAN), open platform communications unified architecture (OPCUA), meter-bus, highway addressable remote transducer (HART), ethernet for control automation technology (EtherCAT), Zigbee, EnOcean, digital addressable lighting interface (DALI) and so on. The communication protocols enable direct digital communication between the built environment management system and the legacy infrastructure to transmit data packets that correspond to various commands for controlling the legacy infrastructure, such as adjusting temperature of an air conditioning or heating unit, fan speed, or mode settings. For example, the disclosed built environment management system using BACnet protocol to communicate with the legacy infrastructure. The built environment management system is configured to send control signals formatted as BACnet objects, which are compatible with the legacy infrastructure. Each BACnet object corresponds to a specific function, allowing for granular control over one or more operational settings of the legacy infrastructure system's operations. For instance, temperature adjustments may be communicated as analog value objects, while mode changes might be communicated as binary value objects. The technical advantage is integration with such communication protocol allows real-time operational status monitoring of the legacy infrastructure.

[0066] In an embodiment, the built environment management system is configured to utilize the at least one ML model to control such the legacy infrastructure while collecting data pertaining to operation of the legacy infrastructure. The data collected is utilized by the at least one ML model to refine built environment management system performance and provide optimized solution to enhance energy efficiency of the built environment where the legacy infrastructure is used. The technical advantage is automation may be implemented in the legacy infrastructure without prior automation facility.

[0067] Optionally, the disclosed built environment management system is configured to incorporate carbon intensity of a grid as a function of time, the grid is an electrical grid to which the built environment is connected to, for deriving required energy. The technical advantage is inclusion of dynamic nature of energy availability, fare, and carbon intensity to optimize energy costs and footprint of the built environment.

[0068] Optionally, the aforementioned built environment management system is configured to analyse post and pre-adjustment performance of the built environment infrastructure to estimate a saving in operational cost.

[0069] Optionally, the present disclosure leverages advanced monitoring of built environment infrastructure energy consumption and built environmental conditions to evaluate the return on investment (R.OI) for retrofitting. By analyzing historic and real-time data from the data repository, the present system is configured to determine when it is economically and environmentally beneficial to replace current built environment infrastructure with more efficient infrastructures. This assessment includes tracking energy usage patterns and calculating potential savings in power consumption, costs and CO2e emissions. Optionally, the present system is configured to monitor heat loss in three dimensions across different rooms, providing detailed insights into built environment. This information is crucial for selecting the optimal replacement for built environment infrastructure (such as HVAC or heat pump system), ensuring maximum efficiency and comfort for the occupants. Through this data-driven approach unnecessary economic expenses are avoided. The technical advantages are optimization of built environment management and improvement of performance of the built environment infrastructure.

[0070] The present disclosure also relates to the method as described above. Various embodiments and variants disclosed above, with respect to the aforementioned built environment management system, apply mutatis mutandis to the method.

[0071] Optionally, the method further comprising adjusting the one or more operational settings of the built environment infrastructure, based on data stored in a data repository and smart grid data, wherein the data repository and a smart grid are communicably coupled to a server, and wherein the data repository is configured to receive, in real-time or at a predefined interval, and store therein at least one of: the data received from the environment monitoring unit, the energy monitoring unit and the smart grid.

[0072] Optionally, the method further comprising generating at least one digital twin corresponding to comfort metrics and the built environment infrastructure, based on the data stored in the data repository.

[0073] Optionally, the method further comprising generating a digital dashboard, corresponding to the at least one digital twin, configured to display to the at least one user, in real-time, one or more operational settings of the built environment infrastructure.

[0074] Optionally, the method further comprising optimizing performance of a built environment management system using at least one Machine Learning ( ML) model, wherein the at least one ML model is trained based on historical data stored in the data repository.

[0075] Optionally, the method further comprising : predicting a comfort metrics and occupancy based on at least one of: a historical data corresponding to corresponding to at least one parameter corresponding to the indoor environment, a demographics within the built environment; predicting energy consumption of the built environment infrastructure by analyzing the data received from the energy monitoring unit; and adjusting the one or more operational settings of the built environment infrastructure.

[0076] Optionally, the method further comprising receiving, in real-time, a user feedback, for optimizing the built environment.

[0077] For attaining the goals of sustainable development, the present disclosure provides the aforementioned built environment management system and method thereof, with optimized energy consumption, minimized costs, and minimized CO2e. The present disclosure provides smart control of built environment while monitoring and assessing performance of built environment infrastructures such as a lighting arrangement, an amenityappliance arrangement, a heating- ventilation-air conditioning (HVAC) arrangement. Thus, undue operational failure and frequent disposal of the built environment infrastructures is avoided. Thus, the disclosed built environment management system and method thereof, provide green building management with minimal environmental impact. Moreover, the disclosed built environment management system is geared towards ensuring comfort of occupant while monitoring indoor environment for potential risk, such as CO2 concentration, thereby ensuring that the occupants have access to healthy indoor environment while optimizing energy consumption for enhancing user comfort. Thus, promoting environmentally sustainable practices in the field of built environment management. EXPERIMENTAL PART

[0078] The disclosed built environment management system was utilized to monitor, control, and optimize a built environment implemented as a building. The disclosed built environment management system was observed to have reduced the buildings' operational costs while cutting and quantifying a HVAC scope to greenhouse emissions for the building. The disclosed built environment management system also was observed to have quantitatively enhanced occupants' comfort while maintaining a healthy indoor environment in the building. In this regard, dynamic adjustments were made by utilizing at least one ML model which to select a best possible solution considering dynamic nature of buildings facilities, the electricity grid, and occupant's comfort. Moreover, by using the disclosed built environment management system, power and emissions savings were estimated to be more than 15% of previous saving using any conventional loT solution.

[0079] DETAILED DESCRIPTION OF THE DRAWINGS

[0080] Referring to FIG. 1A, illustrated is a block diagram of a built environment management system 100 for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure. As shown in FIG. 1, the built environment management system 100 comprises an environment monitoring unit 102 configured to monitor an indoor environment ; an energy monitoring unit 104 communicably coupled to a built environment infrastructure for monitoring energy consumption thereof, wherein the built environment infrastructure comprises at least one of: a lighting arrangement, an amenity-appliance arrangement, a heating- ventilation-air conditioning (HVAC) arrangement; and a control unit 106 communicably coupled to at least one data source 108, environment monitoring unit 102 and the energy monitoring unit 104. The control unit 106 is configured to: receive data from at least one data source 108, the environment monitoring unit 102 and the energy monitoring unit 104; determine a set of optimal operational values corresponding to the built environment infrastructure, based on the data received; and adjust one or more operational settings of the built environment infrastructure, based on the set of optimal operational values determined, thereby optimizing the built environment. The built environment management system 100 is configured to provide, in real-time, a carbon dioxide equivalent (CO2e) data, an energy consumption data of the built environment infrastructure, an operational costing data of the built environment infrastructure based on the data received.

[0081] It may be appreciated that FIG. 1A is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

[0082] Referring to FIG. IB, illustrated is a block diagram of a built environment management system 100 for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure. As shown in FIG. IB, the built environment management system 100 comprises an environment monitoring unit 102; an energy monitoring unit 104; a cloud-based management unit 103 communicably coupled to the environment monitoring unit 102, the energy monitoring unit 104 and at least one data source 108; and a control unit 106 communicably coupled to the cloud-based management unit 103. The cloud-based management unit 103 is configured to collect data pertaining to at least one parameter corresponding to the indoor environment, at least one parameter related to an outdoor environment and energy consumption from the environment monitoring unit 102, at least one data source 108 and the energy monitoring unit 104. The cloud-based management unit 103 is also configured to determine a set of optimal operational values corresponding to the built environment infrastructure, based on the data received and transmit commands to the control unit 206 to adjust one or more operational settings of the built environment infrastructure, based on the set of optimal operational values determined, thereby optimizing the built environment.

[0083] It may be appreciated that FIG. IB is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

[0084] Referring to FIG. 2, illustrated is a schematic illustration of workflow of a built environment management system 200 for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure. As shown in the FIG. 2, the built environment management system 200 is configured to trigger operation of a first digital twin 202 and the second digital twin 204, wherein the first digital twin 202 is configured to mimic a built environment infrastructure 218 and the second digital twin 204 is configured to mimic a comfort metrics. The built environment management system 200 is communicably coupled to a data repository 206, for receiving data pertaining to built environment infrastructure 218, at least one parameter corresponding to indoor environment, at least one parameter corresponding to outdoor environment, and comfort of at least one user within the built environment as comfort metrics. The first digital twin 202 receive data pertaining to built environment infrastructure from the data repository 206, and the second digital twin 204 receives the data from data pertaining to comfort of at least one user, as comfort metrics from the data repository 206. As shown, the data repository 206 is communicably coupled to an environment monitoring unit 208A to received data on a thermal inertial data of the built environment and at least one parameter corresponding to the indoor environment. Moreover, the data repository 206 is communicably coupled to an energy monitoring unit 208B to received data on an energy consumption data of the built environment infrastructure. Additionally, the data repository 206 is communicably coupled to at least one data source 212 to receive data on at least one parameter related to outdoor environment from at least one data source 212. The first digital twin 202 and second digital twin 204 both are coupled to at least one ML model 210. The at least one ML model 210 is coupled to at least one data source 212 to receive data on at least one parameter related to outdoor environment via an associated application programming interface B. The at least one ML model 210 is configured to provide set of optimal operational values to a cloud service 214 and / or a control unit 216 to adjust one or more operational settings of the built environment infrastructure 218. The cloud service 214 is configured to relay updates on the built environment infrastructure 218 to the data repository 206 (connection A) .Additionally, the cloud service 214 is configured to calculate energy savings, CO2e, operation cost based on the energy consumption data.

[0085] It may be appreciated that FIG. 2 is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

[0086] Referring to FIG. 3, illustrated is a flowchart 300 depicting steps of a method for monitoring, controlling and optimizing a built environment, in accordance with an embodiment of the present disclosure. At step 302, using an environment monitoring unit, an indoor environment is monitored. At step 304, using an energy monitoring unit, energy consumption of a built environment infrastructure coupled to the energy monitoring unit is monitored. At step 306, data from at least one data source is received. At step 308, a set of optimal operational values corresponding to the built environment infrastructure is determined, based on the data received. At step 310, one or more operational settings of the built environment infrastructure are adjusted, based on the set of optimal operational values determined, thereby optimizing the built environment. At step 312, a carbon dioxide equivalent (CChe) data based on the data received is provided in real-time.

[0087] It may be appreciated that FIG. 3 is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

Claims

CLAIMS1. A built environment management system (100, 200) for monitoring, controlling, and optimizing a built environment, the built environment management system comprising: an environment monitoring unit (102, 208A) configured to monitor an indoor environment; an energy monitoring unit (104, 208B) communicably coupled to a built environment infrastructure (218) for monitoring energy consumption thereof, wherein the built environment infrastructure comprises at least one of: a lighting arrangement, an amenity-appliance arrangement, a heating- ventilation-air conditioning (HVAC) arrangement; and a control unit (106, 216) communicably coupled to at least one data source (108, 212), environment monitoring unit and the energy monitoring unit, the control unit configured to: receive data from the at least one data source; determine a set of optimal operational values corresponding to the built environment infrastructure, based on the data received; and adjust one or more operational settings of the built environment infrastructure, based on the set of optimal operational values determined, thereby optimizing the built environment, wherein the built environment management system is configured to provide, in real-time, at least one of: a carbon dioxide equivalent (CChe) data, an energy consumption data of the built environment infrastructure, operational costing data of the built environment infrastructure, based on the data received.

2. A built environment management system (100, 200) according to claim 1, wherein the at least one data source (108, 212) is implemented as at least one of: a cloud data source, the environment monitoring unit (102) and the energy monitoring unit (104, 208B), and wherein the data from the at least one data source pertains to at least one of: a comfort metric, at least one parameter corresponding to the indoor environment and at least one parameter related to an outdoor environment.

3. A built environment management system (100, 200) according to claim 2, wherein the environment monitoring unit (102, 208A) comprises an interface configured to receive the comfort metric from at least one user within the indoor environment.

4. A built environment management system (100, 200) according to claims 2 and 3, wherein the environment monitoring unit (102, 208A) comprising at least one sensor configured to measure and provide, in real-time or at a predefined interval a thermal inertial data of the built environment, at least one parameter corresponding to the indoor environment selected from at least one of: indoor temperature, indoor humidity, indoor CO2 levels, indoor occupancy, indoor carbon monoxide (CO) level, particulate matter concentration, volatile organic compounds (VOC) concentration, indoor location tracking, indoor air quality, indoor light and sound comfort levels, gas leak, indoor air pressure, indoor air velocity; and the cloud data source configured to provide at least one parameter related to an outdoor environment selected from at least one of: outdoor temperature, outdoor humidity, outdoor air quality, outdoor air pressure, outdoor light, wind profile, weather condition.

5. A built environment management system (100, 200) according to claim 4, further comprises an outdoor environment monitoring unit, communicably coupled to the at least one data source, configured to monitor the at least one parameter corresponding to the outdoor environment.

6. A built environment management system (100, 200) according to any of the preceding claims, wherein the energy monitoring unit (104, 208B) is further configured to measure, in real-time or at a predefined interval, at least one of: one or more original operational settings, operational duration, performance data of the built environment infrastructure (218).

7. A built environment management system (100, 200) according to any of the preceding claims, further comprising a server communicably coupled to the control unit (106, 216), the environment monitoring unit (102, 208A), the energy monitoring unit (104, 208B), a smart grid, and a data repository (206).

8. A built environment management system (100, 200) according to claim 7, wherein the data repository (206) is configured to receive, in real-time or at a predefined interval, and store therein at least one of: the data received from the environment monitoring unit (102), the energy monitoring unit (104) and the smart grid.

9. A built environment management system (100, 200) according to claims 7-8, wherein the server is configured to operate the control unit (106, 216) to adjust the one or more operational settings of the built environment infrastructure (218), based on the data stored in the data repository (206) and smart grid data.

10. A built environment management system (100, 200) according to claims 7-9, wherein the server is configured to generate at least onedigital twin (202, 204) corresponding to comfort metrics and the built environment infrastructure (218), based on the data stored in the data repository (206).

11. A built environment management system (100, 200) according to claim 10, further comprising a digital dashboard, corresponding to the at least one digital twin (202, 204), configured to display to the at least one user, in real-time, one or more operational settings of the built environment infrastructure (218).

12. A built environment management system (100, 200) according to claims 7-11, further comprising at least one Machine Learning ( ML) model (210) for optimizing performance of the built environment management system, wherein the at least one ML model is trained based on historical data stored in the data repository (206).

13. A built environment management system (100, 200) according to claim 12, wherein the built environment management system is configured to utilize the at least one ML model (210) to: predict the comfort metrics and occupancy based on at least one of: a historical data corresponding to the at least one parameter corresponding to the indoor environment, a demographics within the built environment; predict energy consumption of the built environment infrastructure by analyzing the data received from the energy monitoring unit (104, 208B); and operate the control unit (106, 216) to adjust one or more operational settings of the built environment infrastructure (218).

14. A built environment management system (100, 200) according to any of the preceding claims, further comprising a feedback unit,communicably coupled to the control unit, for receiving, in real-time, a user feedback, for optimizing the built environment.

15. A method for monitoring, controlling, and optimizing a built environment, the method comprising: monitoring, using an environment monitoring unit (102, 208A), an indoor environment; simultaneously, monitoring, using an energy monitoring unit (104, 208B), energy consumption of a built environment infrastructure (218) coupled to the energy monitoring unit, wherein the built environment infrastructure comprises at least one of: a lighting arrangement, an amenity-appliance arrangement, a heating- ventilation-air conditioning (HVAC) arrangement; receiving data from at least one data source (108, 212); determining a set of optimal operational values corresponding to the built environment infrastructure (218), based on the data received; and adjusting one or more operational settings of the built environment infrastructure, based on the set of optimal operational values determined, thereby optimizing the built environment, wherein the method comprises providing, in real-time, at least one of: a carbon dioxide equivalent (CChe) data, an energy consumption data of the built environment infrastructure, an operational costing data of the built environment infrastructure, based on the data received.

16. A method according to claim 15, further comprising: adjusting the one or more operational settings of the built environment infrastructure, based on data stored in a data repository (206) and smart grid data, wherein the data repository and a smart grid are communicably coupledto a server, and wherein the data repository is configured to receive, in real-time or at a predefined interval, and store therein at least one of: the data received from the environment monitoring unit (102), the energy monitoring unit (104) and the smart grid.

17. A method according to claim 16, further comprising generating at least one digital twin (202, 204) corresponding to comfort metrics and the built environment infrastructure (218), based on the data stored in the data repository (206).

18. A method according to claim 17, further comprising generating a digital dashboard, corresponding to the at least one digital twin (202, 204), configured to display to the at least one user, in real-time, one or more operational settings of the built environment infrastructure (218).

19. A method according to claims 15-18, further comprising optimizing performance of a built environment management system (100, 200) using at least one Machine Learning ( ML) model (210), wherein the at least one ML model is trained based on historical data stored in the data repository.

20. A method according to claim 19, further comprising: predicting a comfort metrics and occupancy based on at least one of: a historical data corresponding to corresponding to at least one parameter corresponding to the indoor environment, a demographics within the built environment; predicting energy consumption of the built environment infrastructure (218) by analyzing the data received from the energy monitoring unit (104, 208B); and adjusting the one or more operational settings of the built environment infrastructure (218).5 21. A method according to claims 15-20, further comprising receiving, in real-time, a user feedback, for optimizing the built environment.

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