DESC:EARLIEST PRIORITY DATE:
This Application claims priority from a provisional patent application filed in India having Patent Application No. 202321079749, filed on November 23, 2023, and titled “A CLOUD-BASED BUILDING MANAGEMENT SYSTEM”.
FIELD OF INVENTION
[0001] Embodiments of the present disclosure relate to the field of building management system, and more particularly, a cloud-native system for remote control of building management and a method thereof.
BACKGROUND
[0002] Traditionally, a building management system is essentially a solution that includes both a hardware and software platform. Now, with respect to the hardware, all devices in a building are controlled centrally from a single place, and all the devices are wired to a controller, the controller is programmed and functions as a switch to specify when the devices should be turned ON, turned OFF and controls data from the controller itself. As, the controller is connected to a desktop application, the data from the controller is routed to the desktop application where a user can only view the data i.e. in read-only format.
[0003] Currently, wireless communication is not necessarily equivalent to an internet-based solution. Wireless connectivity often includes LoRa (Long Range) or Zigbee, which are wireless communication technologies that do not require internet access. These wireless devices connect with one another in a local network, and the data is routed to a gateway. This gateway, which has an Ethernet connection, then connects to the internet, routing the data to the cloud. As a result, the system does not rely solely on an internet-based communication, but rather on local wireless networks, allowing the data to be viewed remotely once the data has been uploaded to the cloud.
[0004] Further, the devices or equipment’s (electrical and electronic) in the building are programmed and as users occupy, the users manually adjust parameters of the devices within a specific range.
[0005] Hence, there is a need for an improved system for system for building management which addresses the aforementioned issue(s).
OBJECTIVE OF THE INVENTION
[0006] An objective of the present invention is to integrate a wireless fidelity chip inside a controller, thereby enabling the controller to connect the controller directly to a cloud, thereby creating a wireless architecture.
[0007] Another objective of the present invention is to allow a user to monitor, control, manage, and configure parameters of the devices remotely from any location, thereby the user need not be within a specific distance.
[0008] Yet, another objective of the present invention is to integrate a machine learning model and an artificial intelligence model in the cloud that houses intelligence, analytics, and techniques for continuous commissioning, predictive maintenance, and real-time analytics of the devices thereby adjusting the parameters in real-time.
BRIEF DESCRIPTION
[0009] In accordance with an embodiment of the present disclosure, a cloud-native system for remote control of building management is provided. The system includes a wireless controller module adapted to connect to a cloud-native platform to establish a direct connection between a plurality of controllers and the cloud-native platform, wherein the wireless controller module is connected to the plurality of controllers. The system also includes a processing subsystem hosted on a server wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a data collection module configured to collect data from a one or more devices positioned in a building via the plurality of controllers wherein the plurality of controllers constantly captures a plurality of heterogenous parameters wherein the plurality of heterogenous parameters includes temperature, humidity, lighting level, and an operational mode of the one or more devices. The processing subsystem also includes a communication module operatively coupled to the data collection module, wherein the communication module is configured to transmit the data to the cloud-native platform via a network switch in real-time within a predetermined time, wherein the predetermined time is configurable by a user. The processing subsystem also includes a computation module operatively coupled to the communication module wherein the computation module is configured to adjust the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model and simultaneously generates a notification by a notification module, wherein the plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions. Furthermore, the processing subsystem includes a user interface module operatively coupled to the computation module wherein the user interface module is configured to enable the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform.
[0010] In accordance with another embodiment of the present disclosure, a method for remotely controlling building management is provided. The method includes establishing, by a wireless controller module, a direct connection between a plurality of controllers and the cloud-native platform, wherein the wireless controller module is connected to the plurality of controllers. The method also includes capturing, by a data collection module, a plurality of heterogenous parameters, wherein the plurality of heterogenous parameters comprises temperature, humidity, lighting level and an operational mode of the one or more devices. Further, the method includes transmitting, by a communication module, the data to the cloud-native platform via a network switch in real-time within a predetermined time, wherein the predetermined time is configurable by a user. Furthermore, the method includes adjusting, by a computation module, the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model and simultaneously generates a notification by a notification module, wherein the plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions. Moreover, the method includes enabling, by a user interface module, the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform.
[0011] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0013] FIG. 1 is a block diagram representation of a cloud-native system for remote control of building management in accordance with an embodiment of the present disclosure;
[0014] FIG. 2 is a block diagram of an exemplary embodiment of a cloud-native system for remote control of building management of FIG. 1 in accordance with an embodiment of the present disclosure;
[0015] FIG. 3 is a block diagram of an exemplary embodiment of a cloud-native system for remote control of building management in a real-time scenario in accordance with an embodiment of the present disclosure;
[0016] FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure; and
[0017] FIG. 5 illustrates a flow chart representing the steps involved in a method method for remotely controlling building management in accordance with an embodiment of the present disclosure.
[0018] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
[0019] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.
[0020] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or subsystems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
[0022] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
[0023] Embodiments of the present disclosure relates to cloud-native system for remote control of building management is provided. The system includes a wireless controller module adapted to connect to a cloud-native platform to establish a direct connection between a plurality of controllers and the cloud-native platform, wherein the wireless controller module is connected to the plurality of controllers The system also includes a processing subsystem hosted on a server wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a data collection module configured to collect data from the one or more devices positioned in a building via the plurality of controllers, wherein the plurality of controllers constantly captures a plurality of heterogenous parameters, wherein the plurality of heterogenous parameters includes temperature, humidity, lighting level and an operational mode of the one or more devices. The processing subsystem also includes a communication module operatively coupled to the data collection module, wherein the communication module is configured to transmit the data to the cloud-native platform via a network switch in real-time within a predetermined time, wherein the predetermined time is configurable by a user. The processing subsystem also includes a computation module operatively coupled to the communication module wherein the computation module is configured to adjust the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model, wherein the plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions. Furthermore, the processing subsystem includes a user interface module operatively coupled to the computation module wherein the user interface module is configured to enable the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform.
[0024] FIG. 1 is a block diagram representation of a cloud-native system for remote control of building management in accordance with an embodiment of the present disclosure. The system (100) includes a processing subsystem (140) hosted on a server (150). In one embodiment, the server (150) may include a cloud-based server. In another embodiment, parts of the server (150) may be a local server coupled to a first user device. The processing subsystem (140) is configured to execute on a network (160) to control bidirectional communications among a plurality of modules. In one example, the network (160) may be a private or public local area network (LAN) or Wide Area Network (WAN), such as the Internet. In another embodiment, the network (160) may include both wired and wireless communications according to one or more standards and/or via one or more transport mediums. In one example, the network (160) may include wireless communications according to one of the 802.11 or Bluetooth specification sets, or another standard or proprietary wireless communication protocol. In yet another embodiment, the network (160) may also include communications over a terrestrial cellular network, including, a global system for mobile communications (GSM), code division multiple access (CDMA), and/or enhanced data for global evolution (EDGE) network.
[0025] The cloud-native system (100) includes a wireless controller module (110). The cloud-native system (100) is a computing environment designed to utilize cloud technologies to create, deploy and manage applications. The wireless controller module (110) is adapted to connect to a cloud-native platform to establish a direct connection between a plurality of controllers and the cloud-native platform. Typically, each of the plurality of controllers is directly connected to a cloud. The wireless controller module (110) is integrated with a wireless-fidelity chip. The wireless controller module (110) is connected to the plurality of controllers. In one embodiment, the plurality of controllers is either connected to the plurality of sensors via an interface to collect data from the one or more devices or collect the data directly from the one or more devices within the building. As used herein, the interface is a communication interface primarily based on wireless connectivity, which utilizes internet-based communication for data exchanges. The wireless connectivity operates effectively within a range of 50 meters in a line-of sight configuration, ensuring reliable communication between the plurality of sensors and the wireless controller module (110) when with distance of a wireless router. Further, with respect to ethernet connectivity, physical distance between the plurality of sensors and the wireless controller module (110) is not constrained by typical limitation of the wireless connectivity.
[0026] It must be noted that, the plurality of controllers within the building is integrated into the wireless controller module (110). Typically, the wireless controller module (110) functions as a central controller that routes the data to the cloud-native platform (100).
[0027] The processing subsystem (140) includes a data collection module (170), a communication module (180), a computation module (190), and a user interface module (200).
[0028] The data collection module (170) is configured to collect the data from one or more devices positioned in a building via the plurality of controllers. The plurality of controllers constantly captures a plurality of heterogenous parameters from the one or more devices within the building. Typically, the one or more devices includes, but is not limited to lighting systems, heating, ventilation and air conditioning systems, water management system, energy management system, utility management system, lift management system and fire alarm system. The plurality of heterogenous parameters includes, but is not limited to temperature, humidity, lighting level, chilled water, static pressure, inlet temperature and an operational mode of the one or more devices.
[0029] The communication module (180) is operatively coupled to the data collection module (170). The communication module (180) is configured to transmit the data to the cloud-native platform via a network switch in real-time within a predetermined time. Typically, frequency at which the data is transmitted from the wireless controller module (110) to the cloud-native platform is configurable, allowing the user to adjust transmission interval based on their specific needs and use cases. Further, the data transmission can be set to intervals of 5 seconds to 10 minutes, depending on the user's discretion. This flexibility enables the user to optimize performance and data usage according to requirements of building management application, ensuring that real-time monitoring and control are balanced with the operational efficiency.
[0030] Further, data processing and security in the cloud-native platform includes following:
• Data logging
• Data Identification and input output (IO) logging
• Data processing for operation rules
• Processed data flows to server to archive
• Over the air on the Go licensees and database updates instantly using agile development methodology
• Secure socket layer (SSL) securities and 256-bit encryption
• Cloud data optimization
• Rule based logic
• Secured end-to-end encrypted data transceiver process
[0031] The computation module (190) is operatively coupled to the communication module (180). The computation module (190) is configured to adjust the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model and simultaneously generates a notification by a notification module (210, FIG. 2). Typically, the artificial intelligence model and the machine learning model is configured to analyze the data received from the wireless controller module (110). For example, the artificial intelligence model and the machine learning model utilizes the plurality of factors to adjust the plurality of heterogenous parameters. The plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions. Further, the machine learning model and the artificial intelligence model is configured to learn from historical and current data patterns to improve accuracy and relevance of adjustments over time. Further, the machine learning model continuously refines its predictions based on feedback, learning what adjustments work best in different situations. For example, it may recognize patterns in usage of the water management system and adjustments by the user, enabling it to predict and proactively adjust settings to optimize energy efficiency or comfort levels. Further, the artificial intelligence model and the machine learning model are trained based on the adjustments made by the user in a predetermined time to auto-adjust the plurality of heterogeneous parameters in the real-time.
[0032] Further, the computation module (190) is also configured to house intelligence (artificial intelligence model and machine learning model), analytics (process the data received from the plurality of controllers to provide insights on the one or more devices), and techniques for continuous commissioning (continuous monitoring and adjusting the plurality of heterogenous parameters in real-time), predictive maintenance, and real-time analytics of the one or more devices.
[0033] The user interface module (200) is operatively coupled to the computation module (190). The user interface module (200) is configured to enable the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform. Typically, the user is allowed to operate the plurality of heterogeneous parameters of the one or more devices from any location.
[0034] Typically, the user interface module (200) or a web interface connects to the cloud-native platform that hosts the data and control functions of the one or more devices. From the user interface module (200), the user is allowed to view operational status, usage or alerts when adjustments are made by the artificial intelligence and the machine learning model of the one or more devices.
[0035] It must be noted that the user is allowed to adjust the plurality of heterogenous parameters of the one or more devices though the user interface module (200) by directly adjusting the plurality of heterogenous parameters. The plurality of heterogenous parameters includes, but is not limited to turning lights on/off, adjusting HVAC temperature, locking/unlocking doors, security and access control, ventilation and air flow management, occupancy based lighting, occupancy based temperature control, grant or revoke permissions to specific rooms in the building, elevator controls, activate sprinklers for fire suppression in the building.
[0036] It must be noted that the cloud-native platform provides a comprehensive, real-time interface for monitoring status of the wireless controller module (110), the plurality of controllers, and the one or more devices.
[0037] The user interface module (200) also provides critical information about the operational status of the wireless controller module (110), including whether it is online or offline. It also provides details about the operational mode of the one or more devices connected to the wireless controller module (110), such as whether they are set to automatic or manual mode.
[0038] Further, the user interface module (200) offers visibility into the plurality of heterogenous parameters that the wireless controller module (110) is managing across a diverse set of heterogeneous equipment, including Heating, Ventilation, and Air Conditioning (HVAC), lighting, and security systems. The plurality of heterogenous parameters includes settings such as temperature, humidity, lighting levels, and other system-specific data.
[0039] In one embodiment, the user interface module (200) allows the user to view the plurality of heterogenous parameters in a graphical representation. The graphical representation includes, but is not limited to chart, pie, bar, doughnut, and scattered categories.
[0040] FIG. 2 is a block diagram of an exemplary embodiment of a cloud-native system for remote control of building management of FIG. 1 in accordance with an embodiment of the present disclosure. The processing subsystem (140) also includes a notification module (210) and an analytics module (220).
[0041] The notification module (210) is configured to generate a notification in response to adjustments of the plurality of heterogenous parameters performed by the computation module (190). Typically, the user is allowed to view the notification. For example, the artificial intelligence model and the machine learning module detects a change in temperature in a room. The artificial intelligence model and the machine learning model auto adjusts the temperature based on occupancy of a user’s in the room and environmental conditions, and then it adjust the temperature and sends an alert to a building manager via the user interface or a mobile app, saying, "Temperature in the Room is adjusted to 24°C for optimal comfort."
[0042] The analytics module (220) is operatively coupled to the user interface module (200). The analytics module (220) is configured to generate insights and analytics based on the data received from the plurality of sensors. The analytics module (220) is also configured to provide health status of the one or more devices based on the plurality of heterogenous parameters. For example, the analytics module (220) detects unusual energy consumption, temperature fluctuations, or reduced airflow, flagging potential HVAC system issues like clogged filters or failing compressors. A notification is sent to the building manager, recommending maintenance.
[0043] FIG. 3 is a block diagram of an exemplary embodiment of a cloud-native system for remote control of building management in a real-time scenario in accordance with an embodiment of the present disclosure.
[0044] In an example, consider a scenario, where user X is in a building. Typically, the building is equipped with a one or more devices (300). For example, the one or more devices (300) includes, but is not limited to Heating, Ventilation and air conditioning system, Water Management system, Lift Management system, Energy Management system, Utility Management system and a fire alarm system. The building is equipped with a plurality of controllers. The data collection module (170) captures data from the plurality of controllers connected to the one or more devices, wherein the data includes a plurality of heterogenous parameters. Typically, the plurality of heterogenous parameters includes, but is not limited to temperature, humidity, lighting level, occupancy of users, operational status of the one or more devices. Each of the plurality of controllers (wireless controller module (110)) is directly connected to the cloud-based platform to route the data received from the wireless controller module (110) or the plurality of controllers via a network switch (320). Now, the data is transmitted from the wireless controller module (110) to the cloud-native platform and the data from each of the plurality of controllers is routed to the cloud-native platform directly. For example, the data collection module (170) constantly collects temperature readings from different zones in the building and transmits to the cloud-native platform. Now, the computation moule (190) at the cloud-native platform analyzes the data and adjust the plurality of heterogenous parameters of the one or more devices. For example, the computation module (190) sets the temperature to 20°C for optimal comfort. The artificial intelligence model and the machine learning model at the cloud-native platform learns input from the user X over time, current weather condition and the data received from the plurality of controllers. It can predict future adjustments based on the analysis. For example, if the User X regularly adjusts the temperature in afternoon via the user interface module (200) to cool settings when occupancy decreases, the artificial intelligence model and the machine learning model automatically adjust the temperature in the future without User X needing to intervene. As there is change in adjustment, a notification module (210) generation notification to the user X. Further, the user X is allowed to monitor and control the plurality of heterogenous parameters from any location.
[0045] In one embodiment, the computation module (190) learns the data received from the plurality of controllers, adjustments by the user X, and current weather conditions and transmits a command to the wireless controller module (110) to operate the one or more devices (300) at certain parameters.
[0046] FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. The server (150) includes processor(s) (430), and memory (410) operatively coupled to the bus (420). The processor(s) (430), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.
[0047] The memory (410) includes several subsystems stored in the form of executable program which instructs the processor (430) to perform the method steps illustrated in FIG. 1. The memory (410) includes a processing subsystem (140) of FIG.1. The processing subsystem (140) includes a plurality of modules. The plurality of modules includes a data collection module (170), a communication module (180), a computation module (190) and a user interface module (200).
[0048] The data collection module (170) is configured to collect data from a one or more devices positioned in a building via the plurality of controllers wherein the plurality of controllers constantly captures a plurality of heterogenous parameters wherein the plurality of heterogenous parameters includes temperature, humidity, lighting level, and an operational mode of the one or more devices. The processing subsystem (140) also includes a communication module (180) operatively coupled to the data collection module (170), wherein the communication module (180) is configured to transmit the data to the cloud-native platform via a network switch in real-time within a predetermined time, wherein the predetermined time is configurable by a user. The processing subsystem (140) also includes a computation module (190) operatively coupled to the communication module (180) wherein the computation module (190) is configured to adjust the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model and simultaneously generates a notification by a notification module, wherein the plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions. Furthermore, the processing subsystem (140) includes a user interface module (200) operatively coupled to the computation module (190) wherein the user interface module (200) is configured to enable the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform.
[0049] The bus (420) as used herein refers to be internal memory channels or computer network that is used to connect computer components and transfer data between them. The bus (420) includes a serial bus or a parallel bus, wherein the serial bus transmits data in bit-serial format and the parallel bus transmits data across multiple wires. The bus (420) as used herein, may include but not limited to, a system bus, an internal bus, an external bus, an expansion bus, a frontside bus, a backside bus and the like.
[0050] FIG. 5 illustrates a flow chart representing the steps involved in a method for remotely controlling building management in accordance with an embodiment of the present disclosure.
[0051] The method (400) includes establishing, by a wireless controller module, a direct connection between a plurality of controllers and the cloud-native platform, wherein the wireless controller module is connected to the plurality of controllers in step 510. Typically, the wireless controller module is integrated with a wireless-fidelity chip.
[0052] The method (500) also capturing, by a data collection module, a plurality of heterogenous parameters, wherein the plurality of heterogenous parameters comprises temperature, humidity, lighting level, and an operational mode of the one or more devices in step 520.
[0053] Further, the method (500) transmitting, by a communication module, the data to the cloud-native platform via a network switch in real-time within a predetermined time, wherein the predetermined time is configurable by a user in step 530. Typically, the network switch is a device used to connect the one or more devices (such as computers, servers, or other networked devices).
[0054] Furthermore, the method (500) includes adjusting, by a computation module, the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model and simultaneously generates a notification by a notification module, wherein the plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions in step 550. Typically, the artificial intelligence model and the machine learning model are trained based on the adjustments made by the user in a predetermined time to auto-adjust the plurality of heterogenous parameters in the real-time.
[0055] In another embodiment, the computation module is configured to house intelligence, analytics, and techniques for continuous commissioning, predictive maintenance, and real-time analytics of the one or more devices.
[0056] Moreover, the method (500) includes enabling, by a user interface module, the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform in step 550. Typically, the user is allowed to operate the plurality of heterogenous parameters of the one or more devices from any location.
[0057] Various embodiments of the cloud-native system for remote control of building management above provides various benefits by revolutionize building management by providing the cloud-native platform that offers real-time remote control and analytics, coupled with AI and ML for continuous commissioning. Further, the cloud-native platform utilizes a wireless controller module (110) with direct cloud connectivity to interface with building-level equipment like HVAC, lighting, and security systems. The wireless controller module (110) communicates with the cloud-native platform that houses the intelligence and analytics layer, which uses AI and ML modules for enhanced functionality.
[0058] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the described techniques may be implemented within one or more processors, including one or more microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The term “processor” or “processing subsystem” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry. A electronic control unit including hardware may also perform one or more of the techniques of this disclosure.
[0059] Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various techniques described in this disclosure. In addition, any of the described units, modules, or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware, firmware, or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware, firmware, or software components, or integrated within common or separate hardware, firmware, or software components.
[0060] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
[0061] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
[0062] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.
,CLAIMS:1. A cloud-native system (100) for remote control of building management comprising:

characterized in that,

a wireless controller module (110) adapted to connect to a cloud-native platform to establish a direct connection between a plurality of controllers and the cloud-native platform,
wherein the wireless controller module (110) is connected to the plurality of controllers;

a processing subsystem (140) hosted on a server (150) wherein the processing subsystem (140) is configured to execute on a network (160) to control bidirectional communications among a plurality of modules comprising:

a data collection module (170) configured to collect data from a one or more devices positioned in a building via the plurality of controllers wherein the plurality of controllers constantly captures a plurality of heterogenous parameters, wherein the plurality of heterogenous parameters comprises temperature, humidity, lighting level, and an operational mode of the one or more devices;
a communication module (180) operatively coupled to the data collection module (170), wherein the communication module (180) is configured to transmit the data to the cloud-native platform via a network switch in real-time within a predetermined time, wherein the predetermined time is configurable by a user;
a computation module (190) operatively coupled to the communication module (180) wherein the computation module (190) is configured to adjust the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model and simultaneously generates a notification by a notification module (210),
wherein the plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions; and
a user interface module (200) operatively coupled to the computation module (190) wherein the user interface module (200) is configured to enable the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform.

2. The cloud-native system (100) as claimed in claim 1, wherein the wireless controller module (110) is integrated with a wireless-fidelity chip.

3. The cloud-native system (100) as claimed in claim 1, wherein the notification module (210) is configured to generate the notification in response to the adjustments of the plurality of heterogenous parameters performed by the computation module (190).

4. The cloud-native system (100) as claimed in claim 1, comprises an analytics module (220) operatively coupled to the user interface module (200) wherein the analytics module (220) is configured to generate insights and analytics based on the data received from the plurality of sensors.

5. The cloud-native system (100) as claimed in claim 4, wherein the analytics module (220) is configured to provide health status and prediction of operation of the one or more devices based on the plurality of heterogenous parameters.

6. The cloud-native system (100) as claimed in claim 1, wherein the user is allowed to operate the plurality of heterogenous parameters of the one or more devices from any location.

7. The cloud-native system (100) as claimed in claim 1, wherein the computation module (190) is configured to house intelligence, analytics, and techniques for continuous commissioning, predictive maintenance, and real-time analytics of the one or more devices.

8. The cloud-native system (100) as claimed in claim 1, wherein the artificial intelligence model and the machine learning model is trained based on the adjustments made by the user in a predetermined time to auto-adjust the plurality of heterogenous parameters in the real-time.

9. The cloud-native system (100) as claimed in claim 1, wherein the computation module (190) is configured to transmit a command to the wireless controller module (110) upon analyzing the plurality of heterogenous parameters to operate the one or more devices.

10. A method (500) for remotely controlling building management comprising:

characterized in that,
establishing, by a wireless controller module, a direct connection between a plurality of controllers and the cloud-native platform, wherein the wireless controller module is connected to the plurality of controllers; (510)

capturing, by a data collection module, a plurality of heterogenous parameters, wherein the plurality of heterogenous parameters comprises temperature, humidity, lighting level, and an operational mode of the one or more devices; (520)

transmitting, by a communication module, the data to the cloud-native platform via a network switch in real-time within a predetermined time, wherein the predetermined time is configurable by a user; (530)

adjusting, by a computation module, the plurality of heterogenous parameters of the one or more devices based on a plurality of factors in the real-time by an artificial intelligence model and a machine learning model and simultaneously generates a notification by a notification module, wherein the plurality of factors is based on the data received from the plurality of controllers, adjustments made by the user and a change in environmental conditions; (540) and

enabling, by a user interface module, the user to monitor and control the data of the one or more devices in the real-time through the cloud-native platform. (550)
Dated this 21st day of November 2024
Signature

Prakriti Bhattacharya
Patent Agent (IN/PA-5178)
Agent for the Applicant