HVAC optimization using real-time data control

Abstract

This disclosure describes a solution for monitoring, controlling, and sharing HVAC operation status information and its analysis based on a distributed computing system involving a local Building Automation Server (BAS), a network-based (cloud-based) system, and client terminals. On the network-based system, a client-level virtual machine launches a container process for the client, which includes background and foreground child processes. The background child process collects and analyzes HVAC data without client interaction. The foreground child process is set up when the container process starts but is not fully activated until appropriate client interaction is detected. The foreground child process pushes a more comprehensive HVAC operation dataset through the BAS server and analyzes the data through the client terminal at a higher data update rate than the background child process, presenting the data and analysis results to the client in near real-time.

Description

Background Technology

[0001] This disclosure generally relates to the optimization of heating, ventilation, and air conditioning (HVAC). More specifically, but not exclusively, this disclosure relates to the collection and presentation of data on the status of HVAC operations, and the control of HVAC operations based on that data. Technical Field

[0002] Related technical descriptions

[0003] The installation and operation of systems for heating, ventilating, and cooling buildings are costly. In many cases, heating, ventilation, and air conditioning (HVAC) systems can be intentionally operated to improve efficiency. In these cases, the control device takes input from environmental sensors, occupancy sensors, and people, and then, based on that input, the control device can guide the operation of the HVAC system. Efficient operation of an HVAC system can provide sustained cost savings when less energy is used to provide a sufficient level of HVAC comfort. Efficient operation of an HVAC system can also provide additional savings by extending the lifespan of one or more components of the HVAC system when components are used less frequently or underutilized. Various patent publications teach aspects of techniques and related technologies that may be useful for understanding this invention.

[0004] Hartman's U.S. Patent No. 5,535,814 B2 (i.e., the '814 Patent) is entitled "Self-Balancing Variable Air Volume Heating and Cooling System." The '814 Patent teaches a variable air volume heating and cooling system that provides automatic airflow balancing across the system. To balance the system of the '814 Patent, the maximum airflow setting of each terminal box is automatically and continuously adjusted in response to the load of the central supply fan and local area conditions. The system taught in the '814 Patent has the advantages of automating the initial air balancing of the terminal units upon installation and automatically rebalancing in response to changing conditions without human technician intervention.

[0005] Hartman's U.S. Patent No. 6,185,946 B2 (i.e., the '946 Patent) is entitled "SYSTEM FORSEQUENCING CHILLERS IN A LOOP COOLING PLANT AND OTHER SYSTEMS THAT EMPLOY ALLVARIABLE-SPEED UNITS." The '946 Patent builds upon some concepts taught in the '814 Patent. In addition to providing intentional control over individual HVAC systems, it should be recognized that additional efficiency gains can be obtained by intentionally controlling parallel units within an HVAC system. For example, the '946 Patent teaches an improved method for sequencing parallel centrifugal pumps in a variable flow liquid circulation system, parallel fans in a variable airflow system, and centrifugal coolers in an HVAC system having multiple variable-speed driven centrifugal coolers arranged in parallel. In at least some of the methods of the '946 patent, the operating point of the online unit can be determined, the current operating point of the online unit can be compared with the natural curve of maximum efficiency, and some of these units can be added or released to move to the optimal efficiency operating curve that is closest to the whole system.

[0006] Further improvements in HVAC operating efficiency have been made by using real-time data collection, real-time efficiency prediction, and adaptation to future operations based on data collection and efficiency prediction to allow individual HVAC components to operate more efficiently. U.S. Patent No. 8,219,250 B2 ('250 patent) by Dempster et al. is entitled *SYSTEMS ANDMETHODS TO CONTROL ENERGY CONSUMPTION EFFICIENCY*. In the '250 patent, a controller is configured to exchange information with a building automation system (BAS). The controller includes various executable programs for determining real-time operating efficiency, simulated predicted or theoretical operating efficiency, and adjusting HVAC system operating parameters. In one method taught in the '250 patent, the BAS is used to control the operating efficiency of the HVAC system. The method includes the following actions: (1) exchanging information synchronously and in a timely manner between the controller and the building automation system; (2) determining the operating efficiency of the HVAC system based on the current operating status of the equipment; (3) determining the predicted operating efficiency of the HVAC system calculated according to the installation specifications accompanying the HVAC equipment; (4) comparing whether the operating efficiency is lower than a desired threshold relative to the predicted operating efficiency; (5) adjusting one or more HVAC system operating parameters; (6) transmitting one or more adjustments to the BAS; and (7) triggering the controller's self-learning feature to automatically invoke the adjustment at a later time when the operating efficiency is again lower than the desired threshold.

[0007] Figure 1 shows a conventional energy-optimized HVAC system 10. A building automation system (BAS) 12 is arranged to control multiple HVAC components 34. For example, the BAS 12 in Figure 1 is arranged to direct the operation of variable frequency drives (VFDs) 14, tower fans 16, coolers 18, air handling units (AHUs) 20, boilers 22, variable air volume (VAV) and constant air volume (CAV) air handling units 24, pumps and valves 26, and other possible HVAC components not shown.

[0008] As indicated by the double-headed pointer, BAS 12 and the HVAC components in the plurality of HVAC components 34 can establish and maintain one or more of the following: one-way communication, two-way communication, wired communication, wireless communication, electromechanical communication, mechanical communication, or some combination thereof. Through the means of communication, BAS 12 can provide control signals, status signals, parameters, or other such data to the HVAC components 34, and in some cases, one or more of the HVAC components 34 can provide BAS 12 with control signals, status signals, error signals, stored parameters, generated data, or other information.

[0009] In the conventional energy-optimized HVAC system 10, an energy optimization control engine (EOCE) 50 is communicatively coupled to the BAS 12. The EOCE 50 can provide control information to guide the energy-efficient operation of the BAS 12 in accordance with '814 patent, '946 patent, '250 patent, or certain other protocols.

[0010] The implementation of a conventional energy-optimized HVAC system 10 is a process requiring several people. These people may include the building site owner / manager 28a, an energy optimization provider representative 28b, an energy optimization engineer 28c, and any one or more other persons associated with a particular building or building site, such as control engineers, integration engineers, maintenance engineers, service engineers, etc., referred to herein as building engineers 28d. Each person associated with the conventional energy-optimized HVAC system 10 has access to the user computing device 32. The persons associated with the conventional energy-optimized HVAC system 10 can communicate with each other and with others via a wide area network (WAN) 30, such as the Internet, and the associated user computing device 32. In some cases, some of those associated with the conventional energy-optimized HVAC system 10 use the user computing device 32 to communicate with one or more of the EOCE 50, BAS 12, and various HVAC components 34.

[0011] An operational use of a conventional energy-optimized HVAC system 10 is now described. In this scenario, a BAS 12 and multiple HVAC components 34 are installed in a building complex that does not have an EOCE 50. The building site owner / manager 28a recognizes that the building complex has very high energy and maintenance costs, and in an effort to reduce these costs, the building site owner / manager 28a contacts an energy optimization provider representative 28b.

[0012] Energy optimization provider representative 28b seeks assistance from site owner / manager 28a, energy optimization engineer 28c, and building engineer 28d. Using BAS 12, building engineer 28d collects data from BAS 12 and any number of multiple HVAC components 34. Information that may include “on” and “off” times, alarms, temperature data, humidity data, airflow data, and other such information is transmitted to energy optimization provider representative 28b. The collected information may be collected instantaneously as a “snapshot,” or it may be collected over time, such as hours, days, weeks, or months.

[0013] Using the building complex information collected by the building engineer 28d, the energy optimization engineer 28c creates a specific configuration for the EOCE 50, tailored to the building complex and the already installed BAS 12 and HVAC components 34. In some cases, this specific configuration may include hardware, software, or a combination of both. Once so customized, the EOCE 50 is delivered to the building complex and installed. This installation can be performed by the building engineer 28d, the energy optimization engineer 28c, others, or some combination thereof. It is presumed that once installed, the EOCE 50 will operate well and improve the energy use of the building complex.

[0014] In some cases, EOCE 50 can communicate via WAN 30 to provide information to the energy optimization provider representative 28b. This information can be provided automatically, manually, or through some other process. By using the transmitted information, the energy optimization provider representative 28b, the energy optimization engineer 28c, or others can evaluate the energy optimization performance of EOCE 50. Based on faults (if any), and further based on additional optimization findings or for other reasons, it can be determined that improvements can be made to EOCE 50.

[0015] If improvements to EOCE 50 are determined, additional building data can be collected, and Energy Optimization Engineer 28c can generate a new configuration for EOCE 50. This new configuration may include new hardware, new software, or both. Once generated, the new configuration is delivered to the building complex and installed by Building Engineer 28d, Energy Optimization Engineer 28c, other personnel, or some combination thereof.

[0016] Whenever improvements or other changes are determined to be made to EOCE 50, the same time-consuming and expensive manual process is followed to collect data, generate a new configuration for EOCE 50, and install the new configuration.

[0017] All topics discussed in the Background section are not necessarily prior art and should not be assumed to be prior art solely because of their discussion in the Background section. In this way, unless explicitly stated otherwise, any knowledge of a problem in the prior art discussed in the Background section or associated with that topic should not be considered prior art. Rather, the discussion of any topic in the Background section should be considered as part of the inventor's method for addressing a particular problem, and may be inventive within that section and on its own. Summary of the Invention

[0018] Because heating, ventilation, and air conditioning (HVAC) equipment provides significant benefits to people and property, and because losses during equipment operation cannot be tolerated, the installation and activation of HVAC energy optimization control systems are typically expensive and time-consuming. The standard process requires extensive manual on-site data collection, followed by substantial off-site software programming and configuration. Subsequently, the energy optimization control system, custom-developed for the specific site, is manually deployed at the building site where the HVAC equipment operates, as part of the standard procedure.

[0019] This disclosure describes a solution for monitoring, controlling, and sharing HVAC operation status information and its analysis based on a distributed computing system involving a local building automation server (BAS), a network-based (cloud-based) system, and client terminals. On the network-based system, client registration is established for real-time HVAC monitoring and control services, and client-level virtual machines are generated and assigned to the registered clients. The client-level virtual machines include one or more container processes, each comprising background and foreground child processes. The background child processes are started immediately upon service startup via the client-level virtual machines and operate without interaction with the clients. The background child processes collect smaller datasets of HVAC unit operations from one or more associated building automation system (BAS) servers and analyze the data for routine control functions to maintain the routine operations of the HVAC units monitored by the registered clients when registering with the cloud system.

[0020] The foreground subprocess is also set up when the container process starts, but it may not be fully activated until a suitable client interaction is detected. Upon detecting a suitable client interaction (e.g., the client activates a webpage for the foreground subprocess), the foreground subprocess can push a more comprehensive HVAC operation dataset through the BAS server and analyze the data via a client endpoint (e.g., a client application installed on the client's computing device), presenting the data and analysis results to the client in near real-time. The foreground subprocess presents the latest data and analysis from the point when client interaction is detected, and historical data and analysis, such as from the background subprocess, can be combined with the latest data and analysis. In this embodiment, foreground data is collected and presented to the client at a higher update rate than that of the background subprocess.

[0021] By utilizing data and analytics presented through foreground subprocesses, users can detect operational malfunctions in HVAC units of interest and correct these malfunctions using the foreground subprocesses and relevant BAS (Battery Automation System). Background subprocesses can also correct malfunctions during routine HVAC unit operations and analyze these malfunctions to generate a historical record of HVAC operations.

[0022] This disclosure describes several tools and methods for advancing the field of HVAC energy optimization technology. The innovations described herein are novel and useful, and are not well-known, routine, or conventional in the energy optimization industry. The innovations described herein utilize known building blocks combined in novel and useful ways, along with other structures and constraints, to produce more than is conventionally known to date. These embodiments improve HVAC operating computing systems that, when unprogrammed or differently programmed, cannot perform or provide the specific HVAC energy optimization development and deployment features claimed herein.

[0023] The embodiments described in this disclosure improve upon known HVAC energy optimization processes and techniques. In this way, the embodiments described herein improve upon specific computing devices that implement the HVAC energy optimization processes and techniques described herein. For example, scaling update rates based on background and foreground processes, presentation focus, and for other reasons can save additional energy in computing systems implementing the features described herein, as well as in network infrastructure that transmits communication between the various components described herein. In addition to energy savings, the systems and methods disclosed herein further provide more efficient and faster computing, a real and noticeable speed increase when presenting information via a presentation device, and other such improvements.

[0024] The computerized actions described in the embodiments herein are not purely conventional and are not well understood. Rather, these actions are novel to the industry. Furthermore, combinations of the actions described in conjunction with these embodiments provide new information, motivations, and business or other enterprise outcomes that do not yet exist when these actions are considered individually.

[0025] There is no universally accepted definition of what constitutes an abstract concept. Where the concepts discussed in this disclosure may be considered abstract, these claims provide tangible, practical, and concrete applications of the allegedly abstract concepts, which are substantially more numerous than previously known applications.

[0026] The embodiments described herein use computerized techniques to improve HVAC energy optimization techniques; however, other techniques and tools are still available for deploying HVAC optimization programming. Therefore, the claimed subject matter does not exclude the entire or even a considerable portion of the HVAC optimization programming field.

[0027] These features, which have other purposes and advantages that will subsequently become apparent, are contained in the details of the construction and operation claimed in a more full description below, with reference to the accompanying drawings that form part of them.

[0028] This synopsis is provided to present, in a simplified form, certain concepts that will be further described in the detailed embodiments. Unless otherwise expressly stated, the synopsis does not identify key or essential features of the claimed subject matter, nor is it intended to limit the scope of the claimed subject matter. Attached Figure Description

[0029] Non-limiting and non-exhaustive embodiments are described with reference to the following figures, in which, unless otherwise specified, similar reference numerals denote similar parts throughout the views. The dimensions and relative positions of elements in the figures are not necessarily drawn to scale. For example, the shapes of various elements are selected, enlarged, and positioned to improve the readability of the figures. Specific shapes of the drawn elements have been selected for ease of identification in the figures. Hereinafter, one or more embodiments are described with reference to the figures, in which:

[0030] Figure 1 shows a conventional energy-optimized HVAC system;

[0031] Figure 2 It is an energy-optimized HVAC system designed to monitor, analyze, and control HVAC installations;

[0032] Figure 3 This is an example of a cloud-based system;

[0033] Figure 4 This is an example of a client virtual machine;

[0034] Figure 5 This is an example of a building automation server; and

[0035] Figure 6 This is an example process for operating an energy-optimized HVAC system. Detailed Implementation

[0036] Embodiments of the present invention aim to improve the operational efficiency of computing architectures in collecting and presenting data on the operation of HVAC devices and in controlling the operation of HVAC devices based on the effectively collected and presented information. In embodiments, this efficiency is achieved by efficiently establishing and managing virtual machines and one or more container processes operated via virtual machines for each client, such that, for example, computing resources can be efficiently distributed among multiple building automation system (BAS) servers and / or central servers acting as host servers for the virtual machines, and hardware resources can be effectively allocated among multiple virtual machines based on the interaction actions of users or their client computing devices.

[0037] In the example embodiment described here, one or more energy optimization control devices are installed in a building location. After installation, the energy optimization control device is powered on and "online" via a network connection through an embedded or external communication hub (e.g., a connection device). Once online, the energy optimization control device is activated and configured based on the HVAC equipment within the building controlled by the energy optimization device. For example, energy-optimized programming logic is remotely generated for a specific building and deployed to the energy optimization control device. Certain setup files and configuration software files are installed on the energy optimization control device, and then the energy optimization control device is initialized using the remotely generated HVAC optimization programming.

[0038] The configuration of energy optimization devices can be based on information associated with the building, information associated with the HVAC equipment installed in the building, and utility and environmental information from third-party sources. For example, a remote computing system managed by an energy optimization service provider verifies the deployability of an energy optimization control unit, and the energy optimization control unit is instantiated and allowed to operate. Subsequently, the energy optimization control unit can continue to provide HVAC operation data to the remote computing system, and when sufficient improvements can be achieved, the remote computing system generates, automatically downloads, and deploys improved energy-optimized programming logic.

[0039] This disclosure can be more readily understood through detailed implementation of the embodiments. The terminology used herein is for the purpose of describing particular embodiments only and is not restrictive to the claims unless determined to be restrictive by a court or a recognized authority with legitimate jurisdiction. Unless specifically defined herein, the terminology used herein should have its conventional meaning as known in the relevant art.

[0040] Before going into further details, it is helpful to first explain some of the terms used below that may help in understanding this disclosure.

[0041] HVAC system. As used herein, an HVAC system or apparatus is broadly understood as a system or apparatus that performs any one or more of heating, ventilation, and air conditioning in or otherwise associated with a structure such as a building. An HVAC system may be standalone, or multiple HVAC systems may cooperate with each other in any advantageous combination. One or more HVAC systems may be deployed in a single building structure. Alternatively, one or more HVAC systems may be deployed in multiple building structures, and in these cases, these building structures may be arranged in a single campus, or these structures may be arranged in multiple campuses geographically apart. An HVAC system may, exemplary and non-exhaustively, include any one or more of a building automation system (BAS), energy optimization controller, variable frequency drive (VFD), tower fan, cooler, air handling unit (AHU), boiler, variable air volume (VAV) and constant air volume (CAV) air handling units, pump, valve, humidifier, dehumidifier, and any other components that may provide supporting functionality for the HVAC system. Regarding data collection and HVAC control, the BAS can be considered separate from other components and / or devices in the HVAC system, which are referred to individually or collectively as "HVAC units" herein. Therefore, as used herein, an HVAC system comprises at least one BAS and any number of HVAC units.

[0042] Optimization. Throughout this specification and claims, the term "optimization," when used in the context of "energy optimization," does not imply "optimal" in a general sense. Energy optimization refers to the individual, collective, or individual and collective control or guidance of one or more HVAC components to achieve an improvement in an HVAC system. This improvement can be any one or more of the following: increasing heating, ventilation, or air conditioning as desired; decreasing heating, ventilation, or air conditioning as desired; reducing energy use while maintaining acceptable HVAC performance levels; reducing the cost of operating a particular HVAC system while maintaining acceptable HVAC performance levels; reducing maintenance of one or more components of a particular HVAC system; increasing the lifespan of one or more components of a particular HVAC system; or other similar improvements. Energy optimization can be performed in stages over time. A single HVAC system may undergo one, two, or multiple energy optimizations. Energy optimization can be achieved by any number of factors, independently or collectively considered in guiding the operation of a particular HVAC system. These factors, exemplarily and non-exhaustibly, include the measured, calculated, or measured and calculated operating efficiency of one or more HVAC components, the predicted operating efficiency of one or more HVAC components, the time of day, geographic location, current weather, predicted weather, energy source, energy cost, and current data from any number of input sensors (e.g., light sensors, temperature sensors, occupancy sensors, inlet / outlet sensors, etc.).

[0043] In the following description, certain specific details are set forth in order to provide a thorough understanding of the various embodiments disclosed. However, those skilled in the art will recognize that the embodiments may be practiced without one or more of these specific details or by utilizing other methods, components, materials, etc. In other instances, well-known structures associated with computing systems, including client and server computing systems and networks, have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0044] Figure 2 The HVAC energy optimization system 200 was showcased. (Reference) Figure 2System 200 may include a local subsystem 202, a cloud subsystem 204, and a remote client 206. In the local subsystem 202, each of the multiple building structures 210 includes multiple HVAC units 220 and one or more HVAC energy optimization units (“control units”) 230. Control units 230 may be embedded in one or more HVAC units 220, or may be stand-alone units. One or more HVAC units 220 or control units 230 associated with each building 210 may be communicatively coupled to a building automation system / server (BAS) 240 associated with the building 210. Control units 230 and BAS 240 may work together as a local system (control unit 230) and a remote system (BAS 240) to control the multiple HVAC units 220, respectively. For example, each building 210 may include a control system 230 that controls the HVAC units 220 installed in the building 210, and a single BAS 240 may be associated with the control systems 230 of multiple buildings 210. In another embodiment, BAS 240 may be dedicated to a single building 210, wherein the functions of control device 230 and BAS 240 are integrated into a single physical system, referred to as BAS 240 for simplicity. Of course, other embodiments with different arrangements of these systems and subsystems are conceivable.

[0045] HVAC unit 220 can be any indoor climate or environmental control device and its peripheral equipment, including but not limited to variable frequency drives (VFDs), tower fans, coolers, air handling units (AHUs), boilers, variable air volume (VAV) and constant air volume (CAV) air handling units, pumps and valves, and other possible devices / components suitable for regulating indoor environments (e.g., temperature, humidity, air quality, noise cancellation, air circulation, lighting, etc.).

[0046] Building 210 can be any single building structure or a complex consisting of two or more buildings. Building 210 can be a commercial structure, such as an office building, warehouse, publicly accessible building (e.g., a school or other public building, a hospital, an entertainment venue such as a stadium or theater, a bank, a retail establishment, a restaurant, a hotel or other accommodation building, etc.), an industrial building, etc. Building 210 can also be a large residential structure, such as a cooperative apartment structure that includes many HVAC units 220 within each individual cooperative unit and in common / shared areas.

[0047] In some cases, the control device 230 or the BAS 240 associated with it performs certain functions in the manner of BAS 12 in Figure 1. However, as discussed in this disclosure, Figure 2BAS 240 is structurally different from BAS 12 in Figure 1, and BAS 240 performs additional / different functions or performs functions different from the corresponding functions performed by BAS 12.

[0048] Figure 2 The HVAC component 220 can be configured as shown in Figure 1 as the HVAC component 34. In at least some embodiments, Figure 2 One or more of the HVAC components 220 are identical to the corresponding HVAC component 34 in FIG1. ​​In other embodiments, Figure 2 One or more of the HVAC components 34 have features that implement, supplement, or otherwise support the functionality of BAS 240 and / or control unit 230. For example, in an embodiment, control unit 230 is embedded in HVAC unit 220 such that HVAC unit 220 is a smart / connected HVAC 220.

[0049] In the following description, the function of control unit 230 will be described in conjunction with BAS 240 or HVAC 220, and the structure and / or function of control unit 230 will not be described separately. However, it should be understood that a separate control unit 230 is possible and included in this disclosure, which may implement some of the functions of BAS 240 and / or HVAC 220.

[0050] Figure 2 The dual-headed pointer indication of BAS 240 can establish and maintain communication links of one or more of the following: one-way communication, two-way communication, wired communication, wireless communication, electromechanical communication, mechanical communication, or some combination thereof. Through the use of communication, BAS 240 is arranged to provide HVAC components 220 with any one or more of the following: control signals, status signals, parameters, and other such data. In some cases, one or more of the HVAC components 220 provide BAS 240 with control signals, status signals, error signals, stored parameters, generated data, or other information. For example, information identifying multiple HVAC components 220 coupled to BAS 240, operating control parameters for each of the multiple HVAC components 220, and measured operating status data associated with each of the multiple HVAC components 220 can be exchanged via communication links 242 and 244.

[0051] The cloud-based subsystem 204 can be implemented using virtual machines. In embodiments, host servers 250 may be computing devices separate from BAS 240, or they may be implemented using one or more BAS 240s. Host servers 250 may work together in a distributed computing scheme to support a virtualization tier 260, which includes multiple system-level virtual machines (VMs) 262, each of which includes multiple client-level VMs 264. The virtualization tier 260 can be any level of virtualization, i.e., total virtualization, OS-level virtualization, application-level virtualization, or some other level of partial virtualization. In some examples, the virtualization tier 260 includes multiple virtual machine tiers. For example, the virtualization tier 260 may include a shared virtual database 266 and a shared virtual OS 267 for all the individual virtual machines 262.

[0052] System VM 262 can be generated individually for one or more specific categories of HVAC monitoring, analysis, and control functions / services that can be accessed through cloud system 200.

[0053] Each individual client-level VM 264 can be configured to implement one or more applications, i.e., container processes 268, included in the system-level VM 262. Container processes 268 can be personalized for each individual client VM 264 and can be configured based on the client requirements of each client VM 264. In an embodiment, a client VM 262 can be configured for a client 270 (shown as a client computing device). For example, a client VM 264 can be generated or assigned to a client 270 based on the client 270's requirements for data monitoring, data analysis, and HVAC control of a particular HVAC unit 220. For example, different clients 270 may focus on the data monitoring, analysis, and climate control needs of different buildings 210 and / or different HVAC units 220.

[0054] In this embodiment, the client VM 264 may include any number of foreground subprocesses (applications) and background subprocesses (applications). Foreground subprocesses collect and analyze information and actively display information and analysis results via the client computing device 270 when the client interacts. Background subprocesses collect data and perform data analysis without client interaction. In this embodiment, foreground subprocesses have higher priority than background subprocesses in resource allocation (e.g., computing resources, communication resources, and / or storage resources). Furthermore, for the foreground subprocesses, the client VM 264 may include one or more client-side applications and cloud-side applications. The cloud-side applications may be installed and supported via the host server 250, and the client-side applications (“client terminals”) may be installed on the client computing device 270.

[0055] Client computing device 270, virtual machine 262 / 264, host server 250 and / or BAS 240 can communicate with each other via network 280 (e.g., Internet).

[0056] refer to Figure 3 The diagram illustrates details of an example system VM 262 (one is shown for simplicity) within virtualization layer 260. One or more host servers 250 may support virtualization layer 260 above hypervisor layer 310 of host server 250. Within virtualization layer 260, higher-level virtual instances 262 (referred to herein as "system VM 262") may abstract the hardware resources of host server 250's CPU, memory, and communication capabilities and allocate these resources to lower-level virtual machines 264 (referred herein as "client VM" 264). System VM 262 may include or share a virtual OS 267, a virtual database 266, and a virtual communication interface 326 configured to exchange data with or otherwise transfer data to BAS 240.

[0057] The system VM 262 may also include a system application 330, which includes a client registration unit 332, a client VM management unit 334, a background data collection unit 336, and a data key management unit 338.

[0058] System VM 262 may include multiple client VMs 264, each client VM being used for a registered client 270, shared among multiple clients 270, or having multiple client VMs 264 assigned to a single client 270. Client VMs 264 include container processes 268 specifically created based on the registration of the corresponding client 270. That is, container processes 268 are generated in response to a request from a client 270 when registering with a specific system-level VM 262 (i.e., for HVAC monitoring, analysis, and control services).

[0059] Container process 268 may include foreground and background subprocesses. The foreground and background subprocesses may be related to each other in that they focus on the same set of target HVAC devices 220 requested by the registered client 270. The foreground and background subprocesses may differ from each other in the datasets involved, the data update rate, and the way the data is used. The foreground and background subprocesses may also involve different sets of related HVAC devices 220 in terms of data collection and control, because the different categories of data collected and controlled under these two subprocesses may involve different related HVAC devices 220 under data dependencies and control dependencies between the HVAC devices 220.

[0060] In a background subprocess, a first dataset (typically a smaller set of data categories about the operational status and / or other relevant information of an HVAC unit) can be received and analyzed as a backend process, i.e., without interacting with or being presented to client 270. For example, operational status data of a target HVAC unit 220 can be received and analyzed to automatically control the operation of the HVAC unit 220 based on control parameters established under a specific client VM 264 registered with the client. The background data can also be used as a historical performance record of the target HVAC unit 220 for machine learning and artificial intelligence purposes. For example, the background subprocess can generate any number of key performance indicators (“KPI”) values ​​for each HVAC unit 220 of interest. While the results of the background subprocess are not presented to client 270 in real time, they can be used in subsequent foreground subprocesses within the same container process 268. For example, historical KPI values ​​or information representing any such KPI values ​​can be presented to client 270 along with real-time HVAC data from the foreground subprocess. In this embodiment, the background subprocess receives data at a slower update rate than the foreground subprocesses of the same container process 268. In this embodiment, the background child process data reception is automatically started when the client VM 264 is created or the container process 268 is started, and will continue periodically until or unless the client VM 264 is terminated or modified to remove the corresponding container process 268.

[0061] In the foreground subprocess, a second dataset (typically including additional data categories regarding the operational status and / or other relevant information of the HVAC unit 220) can be collected, analyzed, and presented to the client 270 via the client terminal 270 (e.g., through its multimedia display). In the foreground subprocess, the collected data or analytical products based on the collected data are presented to the client 270 in a substantially real-time and forward-looking manner, i.e., only the most up-to-date data or data products are presented. Historical data can be used at least partially to generate the latest data. For example, the latest KPI trend data may include historical KPI values.

[0062] Specifically, in operation, the client registration unit 332 is configured to receive requests from client 270 regarding the monitoring, analysis, and / or control of the total energy efficiency / optimization of one or more target HVAC units 220 or building 210. This request may specify the particular HVAC unit 220 of interest to the client "target HVAC unit 220," the energy efficiency requirements of client 270, the desired balance between energy saving and HVAC performance, etc. In embodiments, client registration may be implemented via a dedicated internet webpage accessible through network 280, via a dynamically generated webpage, or via some other interface.

[0063] Based on the received client request, and during registration, the client VM management unit 334 can assign the client VM 264 to the client 270. The client VM 264 includes one or more container processes 268 that are specifically configured or otherwise arranged based on the client's request. For example, datasets, data analysis schemes, and HVAC control schemes for foreground and background child processes can be customized based on the client's request.

[0064] The client VM management unit 334 can also cause client-side applications (referred to as "client terminals") to be installed on the client computing device 270.

[0065] In another embodiment, the client terminal 270 is additionally or alternatively implemented by using a website that provides a Uniform Resource Locator (URL) to a customized webpage under the client VM 264.

[0066] When client VM 264 is created, one or more corresponding container processes 268 may be ready to be started. In this embodiment, the corresponding background child process starts automatically without interaction with client 270, while the foreground child process is started in an inactive state and subsequently activated when client 270 interacts. For example, the foreground child process may be activated when client 270 activates a webpage on client VM 264 and clicks a tab for a specific container process 268.

[0067] The background data collection unit 336 can be configured to collect data related to indoor climate control and total energy optimization of interest from target HVAC units 220 and / or other HVAC units 220 (“related HVAC units”) in building 210. In embodiments, the reception of background subprocess data can be implemented at the system VM 320 level, as shown and described herein, because the data from the background subprocess can be shared among multiple different client VMs 264 and can be received from the BAS 240 along the same path and / or update rate. However, it should be understood that, for example, the reception of background subprocess data (“background data”) can also be implemented at the client VM 264 level, where client VM 264 / container process 268 differs from other client VMs 264 in terms of background subprocess data requirements.

[0068] Background data can be stored in virtual database 266 and then retrieved or extracted (e.g., pushed) to client VM 264. In an embodiment, background data receiving unit 336 can receive background data from BAS 240 and / or building 210 at a first update rate. Such received background data can be extracted to or retrieved by client VM 264 or its container process 268 at a second data update rate, which may or may not be equal to the first update rate.

[0069] In some cases, the data key management unit 338 is configured to generate and assign authentication keys for data exchange associated with each client VM 264. The authentication keys may be shared with the BAS 240. In an embodiment, the BAS 240 uses the authentication keys to authenticate data reception / collection requests for the client VM 264 and embeds the authentication keys into any data provided by the client VM 264, including data for background child processes. Similarly, the client VM 264 or its container process 268 may only accept data including the embedded authentication key assigned to the client VM 264 or container process 268.

[0070] In some embodiments, the authentication key may be dynamically and / or randomly generated, and may be encrypted and decrypted under a private / public key scheme, all of which are included in this disclosure.

[0071] Figure 4 An exemplary container process 268 is shown for client VM 264. (Reference) Figure 4 Container process 268 may include a foreground subprocess 410 and a background subprocess 430. The foreground subprocess 410 and the background subprocess 430 are created as a pair and are related to each other in various respects. For example, the dataset used in the foreground subprocess (“foreground data”) may overlap with, or specifically include, the dataset used in the background subprocess (“background data”), even though the foreground data includes more data categories and is updated more frequently, i.e., it is collected at a higher update rate. Furthermore, the data analysis results of the background subprocess 430 can also be used for data analysis and data presentation in the foreground subprocess 410.

[0072] Specifically, the foreground subprocess 410 may include a client interaction unit 412, a data collection unit 414, a foreground data analysis unit 416, a data presentation unit 418, and a foreground control unit 420. The background subprocess 430 may include a background analysis unit 432 and a background control unit 434.

[0073] The client interaction unit 412 can be configured to detect client interaction events to activate the foreground subprocess 410. Note that in at least some embodiments, the foreground subprocess 410 starts when the container process 268 starts, but is not fully activated until a client interaction event is detected. Client interaction events may include client activation of a relevant webpage for data monitoring, clicking a tab of a specific data monitoring program under the foreground subprocess, predefined gestures, voice commands, or any other client interaction defined / categorized as indicating that the client 270 expects to monitor, focus on, or otherwise capture or present specific details of HVAC 220 operations in building 210 in real time. The client interaction unit 412 can also be configured to manage the termination of the foreground subprocess 410. For example, the client interaction unit 412 can continuously monitor interaction activity on the client 270 side and a threshold interval for the foreground subprocess to remain active. If no client interaction activity is detected within the threshold interval, the client interaction unit 412 can terminate or pause the foreground subprocess 410.

[0074] Data collection unit 414 is configured to push data collection requests to one or more BAS 240s to obtain a (second) dataset from the foreground subprocess 410. In embodiments, a mailbox process is established between data collection unit 414 and the associated BAS 240 for foreground data collection. The second dataset is typically more comprehensive in terms of data categories than the first dataset from the background subprocess 430, but this is optional. In many embodiments, the update rate required for collecting and transmitting the second dataset is higher than that for the background data, but there may be cases where the update rate for collecting and transmitting the second dataset is the same as or lower than that for the background data. Considering the case where the update rate for collecting and transmitting the second dataset is higher than that for the background data, the collection of the second dataset (i.e., foreground data) is not under the normal data receiving routine as for the background data, and data collection unit 414 specifically requests BAS 240 to collect the data from the foreground subprocess 410 at a higher update rate.

[0075] In this embodiment, front-end data collected from BAS 240 is also extracted into virtual database 266. This second dataset can be identified and given higher priority in database operations, for example, prioritizing it over back-end data in data read and / or write queues. Furthermore, virtual database 266 may include multiple partitions dedicated to front-end data and multiple partitions dedicated to back-end data.

[0076] In this embodiment, the virtual communication interface 326 can give higher priority to sending and receiving data to the second dataset of the foreground subprocess than to background data.

[0077] The front-end data analysis unit 416 is configured to analyze a second dataset, i.e., front-end data, upon request from a client. For example, the analysis can determine whether the target HVAC unit 220 is operating in a manner that achieves overall energy optimization or a balance between energy efficiency and indoor climate control performance.

[0078] Data presentation unit 418 is configured to present HVAC data and / or data analysis results to a user via client computing device 270. Data presentation can be achieved via a dedicated client terminal (i.e., a client-side application installed on client computing device 270) or via a webpage linked to client VM 264. In some cases, information may alternatively be "presented" to a data collection repository, such as a database for presentations that are time-shifted. In this embodiment, data presentation to client computing device 270 is performed substantially in real-time and includes only the most recent data, including HVAC data collected from BAS 240 and / or data analysis results from front-end data analysis unit 416.

[0079] The front-end control unit 420 is configured to control the operation of the HVAC unit 220 via commands or control parameters to the BAS 240 based on data analysis results from the front-end data analysis unit 416 and / or user input. For example, when a user identifies a fault condition on one or more target HVAC units 220 through the presented front-end data and / or data analysis results, the user can input HVAC correction data through the front-end control unit 420 to control the operation of the target HVAC unit 220.

[0080] The background data analysis unit 432 is configured to analyze the first dataset received in the background subprocess. In this embodiment, the analysis is for maintaining the normal / routine operation of the target HVAC unit 220 under preset operating parameters and / or preset optimization parameters. For background analysis, client interaction may not be required. That is, the analysis results can be stored for historical analysis purposes and later presented to the user / client 270 as part of the foreground subprocess 410, but the analysis results may not be presented to the client 270 in real time.

[0081] The background control unit 434 is configured to control the operation of the target HVAC unit 220 based on background analysis results without user / client 270 input. The background control unit 434 can determine at least one of climate control performance parameters and energy-saving parameters. For example, some operating parameters of the HVAC unit 220 (individually or as a group for total energy optimization control) can be set through front-end control or system settings, and the background control unit 434 can monitor and maintain compliance with these operating parameters. For example, front-end control can set the energy consumption of a specific group of HVAC units 220 within a certain range. If background data and / or background analysis results indicate that the energy consumption of the target HVAC units 220 in that group exceeds a preset range, the background control unit 434 can determine this through the relevant BAS 240 and selectively control it to adjust the energy consumption status of certain HVAC units 220 in the group.

[0082] Figure 5 A sample BAS 240 is shown. BAS 240 includes a heartbeat data collection unit 520, a mailbox data collection unit 530, an HVAC control implementation unit 540, and a data coordination unit 550.

[0083] Heartbeat data collection unit 520 is configured to collect a first operational status dataset for background child processes 430 of container process 268 from HVAC unit 220. In an embodiment, multiple container processes 268 or multiple client VMs 264 may share background data collected from the same HVAC unit 220. Therefore, heartbeat data collection unit 520 can collect operational status data from HVAC unit 220 in a manner independent of specific client VMs 264 and / or container processes 268. For example, heartbeat data collection unit 520 may collect operational status data from HVAC unit 220 at a frequency faster than the update rate of background child processes 430 of container process 268. In an embodiment, the data collection frequency of heartbeat data collection unit 520 may even be faster than the data update rate of foreground child process 410. The operational status data collected by heartbeat data collection unit 520 can also be used for foreground child process 410.

[0084] In this embodiment, the data collected by the heartbeat data collection unit 520 is extracted to the background data collection unit 336 directly or through the virtual database 266.

[0085] Mailbox data collection unit 530 is configured to collect operational data under a mailbox process established by data collection unit 414 of foreground subprocess 410. Data collection under a mailbox process is a customized process compared to routine background data collection. For example, the category / type of operational data, the target HVAC device 220, and the update rate for data collection can be customized for the mailbox process. Since the mailbox process is not standard, mailbox data collection unit 530 can determine a set of HVAC devices 220 associated with the target HVAC device 220 for data collection. The associated HVAC devices 220 can be determined based on overall optimization requirements or based on data dependencies between HVAC devices 220. Furthermore, mailbox data collection unit 530 can also determine the data communication hub through which the target and associated HVAC operational data are routed. In an embodiment, this associated HVAC 220 information and data communication hub information can be initially determined by client VM registration unit 332 when client 270 registers, and can be updated / reconfirmed by mailbox data collection unit 530 when the mailbox process is started.

[0086] The HVAC control implementation unit 540 is configured to control the HVAC unit 220 based on instructions from the background control unit 434 and / or the front-end control unit 420. The HVAC control implementation unit 540 can also control the HVAC unit 220 automatically based on preset control parameters. For example, in emergency maintenance situations, the HVAC control implementation unit 540 can implement emergency control of the HVAC unit 220.

[0087] Data coordination unit 550 is configured to process background and foreground data to generate data packets for subprocess 410 and / or foreground subprocess 430, respectively. This processing may include merging HVAC data together using the same time scale and / or unit of measurement. The merging may also include removing inappropriate data and replacing missing data using appropriate data insertion methods. Data coordination unit 550 also adds the authentication key of the relevant client VM 264 to the generated data packets. As discussed herein, client VM 264 uses the assigned authentication key to receive data from BAS 240 and / or from virtual database 266.

[0088] Figure 6 This demonstrates a sample process 600 from system 200. (Reference) Figure 6 In example operation 610, the client registration unit 332 of the client VM manager 330 receives a client request from the client terminal 270 regarding registering a service for real-time monitoring and control of certain HVAC devices 220 under the overall optimization plan.

[0089] In example operation 620, the client VM management unit 334 creates client VM 264 and assigns client VM 264 to the requesting client terminal 270.

[0090] In example operation 630, client VM 264 starts one or more container processes 268 of client VM 264 based on a client request. This startup can immediately begin background child processes 430. This startup can set foreground child processes 410 to be ready to run and partially run, but foreground child processes 410 may also require full activation through client interaction.

[0091] In example operation 640, BAS 240 (e.g., mailbox data collection unit 530) identifies multiple controllable HVAC devices 220 based on the initiated container process 268. The multiple HVAC devices 220 may include a target HVAC device 220 of interest to client 270, as well as related HVAC devices 220 associated with the target HVAC device 220 based on operational dependencies, data dependencies, and / or data communication dependencies. Mailbox data collection unit 530 may also identify one or more data communication hubs for collecting data from the multiple HVAC devices 220.

[0092] In example operation 650, one or both of the heartbeat data collection unit 520 and the mailbox data collection unit 530 receive operational status data associated with each of the identified plurality of controllable HVAC devices 220.

[0093] In example operation 660, data coordination unit 550 groups HVAC operation status data received from different controllable HVAC devices among multiple controllable HVAC devices 220 based on data merging requests from container process 268. Data merging requests may include various data update rates.

[0094] In example operation 670, BAS 240 transmits the grouped HVAC operation status data to the client VM 264 in essentially real time.

[0095] In example operation 680, data presentation unit 418 sends a portion of the grouped operation status data to client terminal 270 under foreground subprocess 410. In the example, upon detecting active client interaction on foreground subprocess 410, data presentation unit 418 sends data packets to client 270 under foreground subprocess. Data packets generated for background subprocess 430 may not be presented to client 270 in real time and may be provided to client 270 upon client request. In some cases, data presentation unit 418 transmits data to client terminal 270 via BAS 240 (e.g., using the mailbox process described herein). In other cases, data communication to client device 270 occurs outside of BAS 240, for example via a direct secure data communication path (e.g., Secure Hypertext Transfer Protocol, HTTPS). In this regard, the communication path between exemplary operations 680 and 685 crosses the dashed portion of BAS 240.

[0096] In the example, data presentation unit 418 can display foreground data groups on a monitor associated with client terminal 270. The latest data regarding the HVAC operation status and / or related data analysis under foreground subprocess 410 is displayed. Historical data (e.g., HVAC operation status data and related analysis under background subprocess 430) can be combined with the latest data groups and presented to client 270 as an optional practice when selected by the client.

[0097] When the client terminal 270 receives the grouped operation status data and related data analysis results, the user of the client terminal can monitor the operation of the HVAC unit 220 and determine the fault condition. When a fault condition is detected, the user can transmit HVAC correction data to the corresponding BAS server 240 via the foreground subprocess 410 in optional client interaction 685. Specifically, in example operation 690, the foreground control unit 420 can cause the corresponding BAS 240 to adjust the operation of the relevant HVAC unit 220 based on the HVAC correction data.

[0098] In example operation 690, the foreground control unit 420 controls HVAC operations based on client interaction. Furthermore, the background analysis unit 432 and the background control unit 434 can analyze the processed grouped operation status data and control the operation of one or more of the multiple HVAC devices under the background subprocess 430. In this example, background data analysis and control are performed through background operations of the client VM 264 without user interaction.

[0099] As used in this disclosure, the term “unit” means an application-specific integrated circuit (ASIC), electronic circuitry, a processor and memory operable to execute one or more software or firmware programs, a combinational logic circuit system, or other suitable component (hardware, software, or hardware and software) that provides the functionality described with respect to the module.

[0100] The terms “real-time” or “realtime” as used herein and in the appended claims are not intended to imply instantaneous processing, transmission, reception, or other methods as appropriate. Rather, the terms “real-time” and “real time” imply that activity occurs within an acceptable short period of time (e.g., a period of seconds or minutes) and that the activity can be continuous (receiving data randomly, periodically, scheduledly, streaming, or otherwise; data associated with one or more HVAC 220s; data received from BAS 240 at VM layer 260). Examples of non-real-time activity are activities that occur over extended periods of time (e.g., weeks or months).

[0101] When the terms “basic” or “approximately” in any grammatical form are used as modifiers in this disclosure and any appended claims (e.g., to modify structure, size, measurement, or some other characteristic), they should be understood to mean that the characteristic can vary by up to 30%. For example, a large amount of off-site software programming and configuration can be described as software programming performed by one or more software practitioners over several days or weeks.

[0102] In the foregoing description, certain specific details have been set forth to provide a full understanding of the various disclosed embodiments. However, those skilled in the art will recognize that the embodiments may be practiced without one or more of these specific details, or by utilizing other methods, components, materials, etc. In other instances, well-known structures associated with electronic and computing systems, including client and server computing systems and networks, have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0103] Unless the context otherwise requires, throughout the specification and the appended claims, the word “comprise” and its variations, such as “comprises”, “comprising”, “includes” and “including”, shall be interpreted in an open-ended, inclusive sense.

[0104] Throughout this specification, references to "one embodiment" or "an embodiment" and variations thereof mean that at least one embodiment includes the specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment" or "in one embodiment" appearing throughout this specification do not necessarily all refer to the same embodiment. Furthermore, specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0105] As used in this specification and the appended claims, unless expressly indicated otherwise in the text and context, the singular forms “a,” “an,” and “the” include the plural objects. It should also be noted that unless inclusion or exclusivity is expressly indicated in the text and context as appropriate, the conjunctions “and” and “or” generally include “and / or” in the broadest sense. Furthermore, the use of “and” and “or” as referred to herein as “and / or” is intended to cover embodiments including all associated items or ideas as well as one or more other alternative embodiments including fewer than all associated items or ideas.

[0106] The subheadings and summaries provided herein are for convenience only and are not intended to limit or interpret the scope or meaning of the embodiments.

[0107] In this disclosure, the list of conjunctions uses commas, which may be referred to as Oxford commas, Harvard commas, serial commas, or another similar term. Such lists are intended to connect words, clauses, or sentences such that the content following the comma is also included in the list.

[0108] The embodiments described above can be combined to provide further embodiments. If necessary, aspects of the embodiments can be modified to utilize concepts from various patents, applications, and publications to provide even more advanced embodiments.

[0109] In view of the detailed description above, these and other modifications can be made to the embodiments. In summary, the terminology used in the claims should not be construed as limiting the claims to the specific embodiments disclosed in this specification and the claims, but should be interpreted to include all possible embodiments and the entire scope of equivalents entitled to be obtained by these claims. Accordingly, the claims are not limited by this disclosure.

Claims

1. A method for improving a heating, ventilation, and air conditioning system, the method comprising: Utilize distributed computing systems accessible via wide area networks: Receive requests from the client computing device; Assign the virtual machine to the client computing device; Based on the request, a container process comprising a foreground subprocess and a background subprocess is launched via the virtual machine, wherein launching the background subprocess includes automatically launching the background subprocess without interaction with the client computing device; and The background control unit, which executes background subprocesses, automatically controls the target controllable heating, ventilation, and air conditioning unit among multiple controllable heating, ventilation, and air conditioning units. On the building automation system server: The container process is used to identify the plurality of controllable heating, ventilation, and air conditioning devices. Receive operational status data associated with each of the plurality of controllable heating, ventilation, and air conditioning devices; The operational status data received from different controllable heating, ventilation, and air conditioning devices among the plurality of controllable heating, ventilation, and air conditioning devices are grouped based on the data merging requirements of the container process. The grouped operation status data is transmitted to the virtual machine in real time; as well as On the client computing device: Receive at least some of the grouped operational state data transmitted to the virtual machine; Determine the fault condition; as well as The container process transmits heating, ventilation, and air conditioning calibration data to the building automation system server. The container process further analyzes the grouped operational status data to control the operation of one or more of the multiple heating, ventilation, and air conditioning devices.

2. The method of claim 1, further comprising: On the client computing device, a request is initiated for a real-time data stream associated with a selected heating, ventilation, and air conditioning unit among the plurality of heating, ventilation, and air conditioning units.

3. The method of claim 2, further comprising: On the building automation system server: Receive the request for the real-time data stream associated with the selected heating, ventilation, and air conditioning unit among the plurality of heating, ventilation, and air conditioning units; and Data associated with the selected heating, ventilation, and air conditioning unit is periodically transmitted to the client computing device.

4. The method of claim 1, wherein, The container process analyzes the processed data, including: Determine at least one of the climate control performance parameters and energy saving parameters.

5. The method of claim 4, wherein, Determining at least one of the climate control performance parameters and the energy-saving parameters includes: The trade-off range between the climate control performance parameters and the energy-saving parameters is determined based on the request from the client computing device.

6. The method of claim 1, wherein, Identifying the plurality of controllable heating, ventilation, and air conditioning devices includes: Identify the first group of controllable heating, ventilation, and air conditioning devices based on the request from the client computing device; and Automatically identify a second group of controllable heating, ventilation, and air conditioning devices to obtain at least one data point, wherein at least one of the first group of controllable heating, ventilation, and air conditioning devices depends on each of the second group of controllable heating, ventilation, and air conditioning devices.

7. The method of claim 1, further comprising: On the building automation system server, a set of communication hubs associated with the plurality of heating, ventilation, and air conditioning units are identified.

8. The method of claim 1, further comprising: On the distributed computing system accessible via the wide area network, an authentication key is created for the container process.

9. The method of claim 8, further comprising: On the building automation system server, the grouped operational status data is transmitted to the virtual machine using the authentication key.

10. The method of claim 1, further comprising: The client computing device displays a first selected portion consisting of grouped operation status data and a second selected portion consisting of analyzed grouped operation status data.

11. The method of claim 1, further comprising: On the client computing device, a timestamp is associated with each piece of data received.

12. The method according to claim 1, wherein, The foreground subprocess involves a first set of data related to the multiple heating, ventilation, and air conditioning devices, while the background subprocess involves a second set of data related to the multiple heating, ventilation, and air conditioning devices, the second set of data being different from the first set of data; The first set of data and the second set of data have different data update rates; The first set of data is updated in real time, while the second set of data is updated at a lower rate than the first set. The second set of data is analyzed as a backend process in the background subprocess, without any interaction with the client computing device.

13. The method according to claim 12, wherein, The background subprocess generates multiple key performance index values ​​for each of the multiple heating, ventilation, and air conditioning devices as the second set of data.

14. The method of claim 1, wherein starting the foreground subprocess comprises starting the foreground subprocess as inactive and activating the foreground subprocess when interacting with the client computing device.

15. A system comprising: A building automation system server, communicatively coupled to multiple controllable heating, ventilation, and air conditioning devices located within the corresponding building, and A distributed computing system communicatively coupled to the building automation system server; and wherein, during operation: The building automation system server: Receive operational status data from one or more of the plurality of heating, ventilation, and air conditioning devices; The received operational data is grouped based on data merging requirements; and The grouped operational data is transmitted to the distributed computing system in essentially real-time; and The distributed computing system: Receive requests for heating, ventilation, and air conditioning monitoring, analysis, and control services from the client computing device; The virtual machine is assigned to the client computing device for the service. Based on the client's request, a container process containing foreground and background subprocesses is launched via the virtual machine. Launching the background subprocess includes automatically launching it without interaction with the client computing device. A background control unit executing the background subprocess automatically controls a target controllable heating, ventilation, and air conditioning device among multiple controllable heating, ventilation, and air conditioning devices. The container process analyzes grouped operational data to control the operation of one or more of the multiple heating, ventilation, and air conditioning devices based on the client's request. This results in the display of one or more of the grouped operational data and analysis results via the client computing device.

16. The system of claim 15, wherein, The distributed computing system includes a virtualization layer, which includes higher-level system virtual machines that generate virtual machines assigned to the client computing devices.

17. The system of claim 15, wherein, The container process analyzes the grouped operational data, including determining the balance between climate control performance parameters and energy-saving parameters.

18. The system of claim 15, wherein, The building automation system server identifies the multiple controllable heating, ventilation, and air conditioning devices, including: Identify the first group of controllable heating, ventilation, and air conditioning devices based on the request from the client computing device; and Automatically identify a second group of controllable heating, ventilation, and air conditioning devices to obtain at least one data point, wherein at least one of the first group of controllable heating, ventilation, and air conditioning devices depends on each of the second group of controllable heating, ventilation, and air conditioning devices.

19. The system of claim 15, wherein, The distributed computing system further assigns a data authentication key to the virtual machine assigned to the client computing device.

Images