BUILDING MANAGEMENT SYSTEM WITH INFECTION MODES OPERATING USING COMPLIANCE STANDARDS
Methods, systems, and machine-readable storage media for building standard compliance. One system includes a controller including one or more processors configured to receive an activation signal corresponding to an infection control mode (ICM). The one or more processors are further configured to initiate the ICM including activating one or more interventions, wherein the one or more interventions include operating HVAC equipment of the building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards. The one or more processors are further configured to determine an infection risk score based on a performance of the HVAC equipment of the building based on the one or more infection control standards, wherein the infection risk score corresponds to an analysis of an environmental condition of the building and a target environmental condition based on the one or more infection control standards.
This application claims the benefit of, and priority to: (1) U.S. Provisional Application No. 63/567,189, filed Mar. 19, 2024, and (2) U.S. Provisional Application No. 63/522,969, filed Jun. 23, 2023, each of which are incorporated by reference herein in their entireties and for all purposes.
BACKGROUNDThe present disclosure relates generally to control systems. The present disclosure relates more particularly to modes for buildings. Building environmental conditions and occupancy levels can affect the health and safety of building occupants. It may be difficult to address potential issues affecting infection control without monitoring and analyzing the conditions in various spaces, under various circumstances in a building, and against various standards.
SUMMARYSome embodiments relate to an HVAC system of a building including a controller including one or more computer-readable storage media and one or more processors. The controller can be configured to receive an activation signal corresponding to an infection control mode (ICM). The controller can be configured to initiate the ICM including activating one or more interventions. The one or more interventions include operating HVAC equipment of the building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards. The controller can be configured to determine an infection risk score based on a performance of the HVAC equipment of the building based on the one or more infection control standards. The infection risk score corresponds to an analysis of an environmental condition of the building and a target environmental condition based on the one or more infection control standards. The controller can be configured to provide the infection risk score.
In some embodiments, the environmental condition corresponds to one or more measured values of air quality parameters within the building, and wherein the one or more measured values is at least one of an air change rate per hour (ACH), a level of specific airborne contaminant, or a particulate matter (PM) concentration. In some embodiments, the target environmental condition corresponds to a predetermined value of the air quality parameters defined by the one or more infection control standards. The one or more infection control standards are at least one of a ASHRAE standard or a government health standard.
In some embodiments, the controller can be configured to determine a minimum energy solution that is compliant with the one or more infection control standards, wherein determining the minimum energy solution includes calculating one or more HVAC system parameters to balance between HVAC capacity and energy usage that satisfies the one or more infection control standards. Determining the minimum energy solution can include modifying the one or more HVAC system parameters based on conditions of the building in response to data collected from temporary sensors or permanent sensors installed within the building and monitoring and updating the minimum energy solution as the conditions of the building change.
In some embodiments, the controller can be configured to determine at least one of a minimum operating cost that is compliant with the one or more infection control standards, a minimum energy and maintenance cost that is compliant with the one or more infection control standards, or a minimum sustainability cost that is compliant with the one or more infection control standards. In some embodiments, the controller can be configured to generate a graphical representation providing compliance levels of a plurality of spaces within the building. The graphical representation includes an indication of the infection risk score and an indication whether the plurality of spaces meeting the one or more infection control standards. In some embodiments, the controller can be configured to operate the HVAC equipment based on changes in occupancy levels, wherein operating includes adjusting HVAC system parameters.
In some embodiments, the controller can be configured to in response to the environmental condition after a period of time being below or outside the one or more infection control standards, initiate additional infection control measures including at least one of activating in-room ultraviolet (UV) light units, increasing airflow of the HVAC system, adjusting an operation of an in-room air cleaning device, adjusting occupancy levels of the building, or adjusting filtration capabilities of the HVAC equipment. In some embodiments, the controller can be configured to determine one or more spaces within the building as validated environments. In some embodiments, the controller can be configured to in response to determining the one or more spaces, monitor ICM data of the one or more spaces to assess a current state of the building. In some embodiments, the controller can be configured to provide the current state of the building.
Some embodiments relate to an HVAC system of a building including a controller including one or more computer-readable storage media and one or more processors. The controller can be configured to receive an environmental dataset including indoor air quality (IAQ) data and one or more operational parameters or sensor readings of HVAC equipment of the building. The controller can be configured to generate a clean air delivery metric for a target area of the building based on one or more parameters to satisfy one or more infection control standards including at least one of a room occupancy, a room volume, or a performance specification of the HVAC equipment. The controller can be configured to initiate a mode to assess compliance with the one or more infection control standards based on the clean air delivery metric.
In some embodiments, the controller can be further configured to in response to determining the clean air delivery metric is below a threshold, generate a notification including one or more recommendations to increase the clean air delivery metric. In some embodiments, the controller can be further configured to generate and provide a recommendation for a maximum occupancy capacity of the target area based on the clean air delivery metric corresponding to an infection control mode (ICM) of the building. In some embodiments, the controller can be further configured to in response to the room occupancy exceeding the maximum occupancy capacity, provide one or more user devices an indication corresponding to the maximum occupancy capacity being exceeded.
In some embodiments, the controller can be further configured to calculate a target clean air delivery rate for the target area based on occupancy data and the one or more infection control standards. In some embodiments, the controller can be further configured to validate a current state of the building including current infection control measures. In some embodiments, the controller can be further configured to generate and provide adjustments for compliance with the one or more infection control standards. In some embodiments, initiating the mode includes initiating a building inspection mode (BIM) to operate the HVAC equipment of the building to assess readiness of the HVAC system to transition into ICM.
In some embodiments, the controller can be further configured to determine an environmental condition of the building and a target environmental condition based on an analysis of the clean air delivery metric against the one or more infection control standards. In some embodiments, the controller can be further configured to generate and provide a graphical representation displaying compliance levels of at least the target area of the building. The graphical representation includes an indication of the clean air delivery metric and an indication whether the target area meets the one or more infection control standards.
Some embodiments relate to a method, including receiving, by one or more processing circuits, an activation signal corresponding to an infection control mode (ICM). The method can include initiating, by the one or more processing circuits, the ICM including activating one or more interventions. The one or more interventions include operating HVAC equipment of a building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards. The method can include determining, by the one or more processing circuits, an infection risk score based on a performance of the HVAC equipment of the building based on the one or more infection control standards. The infection risk score corresponds to an analysis of an environmental condition of the building and a target environmental condition based on the one or more infection control standards. The method can include providing, by the one or more processing circuits, the infection risk score.
In some embodiments, the environmental condition corresponds to one or more measured values of air quality parameters within the building, and wherein the one or more measured values is at least one of an air change rate per hour (ACH), a level of specific airborne contaminant, or a particulate matter (PM) concentration. In some embodiments, the target environmental condition corresponds to a predetermined value of the air quality parameters defined by the one or more infection control standards. The one or more infection control standards are at least one of a ASHRAE standard or a government health standard.
In some embodiments, the method further includes determining, by the one or more processing circuits, a minimum energy solution that is compliant with the one or more infection control standards. Determining the minimum energy solution can include calculating one or more HVAC system parameters to balance between HVAC capacity and energy usage that satisfies the one or more infection control standards, modifying the one or more HVAC system parameters based on conditions of the building in response to data collected from temporary sensors or permanent sensors installed within the building, and monitoring and updating the minimum energy solution as the conditions of the building change. In some embodiments, the method further includes determining, by the one or more processing circuits, a minimum operating cost that is compliant with the one or more infection control standards. In some embodiments, the method further includes determining, by the one or more processing circuits, a minimum energy and maintenance cost that is compliant with the one or more infection control standards. In some embodiments, the method further includes determining, by the one or more processing circuits, a minimum sustainability cost that is compliant with the one or more infection control standards.
Various objects, aspects, features, and advantages of the disclosure will become more apparent and better understood by referring to the detailed description taken in conjunction with the accompanying drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements.
It will be recognized that some or all of the figures are schematic representations for purposes of illustration. The figures are provided for the purpose of illustrating one or more embodiments with the explicit understanding that they will not be used to limit the scope or the meaning of the claims.
DETAILED DESCRIPTION OverviewReferring generally to the FIGS., various example systems and methods are shown and described relating to an infection control mode (ICM). That is, the systems and methods can perform various planning and real-time actions associated with implementation of the ICM that satisfies one or more standards. Planning can include regular testing and strategizing to ensure standard compliance, which can include exploring options like adding end-zone disinfection units or making trade-offs to achieve compliance. Additionally, real-time actions include assessments and modifications based on the received signals of the building's operational parameters or sensor readings to update interventions and maintain the ICM. Moreover, the systems and methods can generate recommendations for the continuous operation of a building under ICM. The ICM can optimize equivalent outdoor air parameters by coordinating ventilation, filtration, and air cleaning measures, enhancing room air distribution to reduce infection risk, and characterizing the effectiveness and safety of filters and air cleaners. In some embodiments, the systems and methods can analyze the development and execution of a building readiness plan, manage system operation during periods of high risk, outline and enforce the frequency of maintenance tasks, and adapt these functionalities across different building types, such as residential homes and healthcare facilities.
In some embodiments, upon receiving an activation signal, the system activates one or more interventions under one or more standards for infectious risk mitigation. These interventions can include adjustments in the HVAC system, engaging supplementary infection control devices, and/pr controlling building occupancy levels. Furthermore, the various system and methods can receive signals of operating parameters of the building and uses these signals to assess whether the ICM is in compliance with one or more designated standards. For example, both proactive planning measures, such as considering the implementation of end-zone disinfection units or evaluating trade-offs for compliance, and real-time adaptive responses, such as dynamic adjustments to rapidly changing environmental or occupancy conditions.
Building HVAC Systems and Building Management SystemsReferring now to
Referring particularly to
The BMS that serves building 10 includes a HVAC system 100. HVAC system 100 can include a plurality of HVAC devices (e.g., heaters, chillers, air handling units, pumps, fans, thermal energy storage, etc.) configured to provide heating, cooling, ventilation, or other services for building 10. For example, HVAC system 100 is shown to include a waterside system 120 and an airside system 130. Waterside system 120 may provide a heated or chilled fluid to an air handling unit of airside system 130. Airside system 130 may use the heated or chilled fluid to heat or cool an airflow provided to building 10. An exemplary waterside system and airside system which can be used in HVAC system 100 are described in greater detail with reference to
HVAC system 100 is shown to include a chiller 102, a boiler 104, and a rooftop air handling unit (AHU) 106. Waterside system 120 may use boiler 104 and chiller 102 to heat or cool a working fluid (e.g., water, glycol, etc.) and may circulate the working fluid to AHU 106. In various embodiments, the HVAC devices of waterside system 120 can be located in or around building 10 (as shown in
AHU 106 may place the working fluid in a heat exchange relationship with an airflow passing through AHU 106 (e.g., via one or more stages of cooling coils and/or heating coils). The airflow can be, for example, outside air, return air from within building 10, or a combination of both. AHU 106 may transfer heat between the airflow and the working fluid to provide heating or cooling for the airflow. For example, AHU 106 can include one or more fans or blowers configured to pass the airflow over or through a heat exchanger containing the working fluid. The working fluid may then return to chiller 102 or boiler 104 via piping 110.
Airside system 130 may deliver the airflow supplied by AHU 106 (i.e., the supply airflow) to building 10 via air supply ducts 112 and may provide return air from building 10 to AHU 106 via air return ducts 114. In some embodiments, airside system 130 includes multiple variable air volume (VAV) units 116. For example, airside system 130 is shown to include a separate VAV unit 116 on each floor or zone of building 10. VAV units 116 can include dampers or other flow control elements that can be operated to control an amount of the supply airflow provided to individual zones of building 10. In other embodiments, airside system 130 delivers the supply airflow into one or more zones of building 10 (e.g., via supply ducts 112) without using intermediate VAV units 116 or other flow control elements. AHU 106 can include various sensors (e.g., temperature sensors, pressure sensors, etc.) configured to measure attributes of the supply airflow. AHU 106 may receive input from sensors located within AHU 106 and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow through AHU 106 to achieve setpoint conditions for the building zone.
Waterside SystemReferring now to
In
Hot water loop 214 and cold water loop 216 may deliver the heated and/or chilled water to air handlers located on the rooftop of building 10 (e.g., AHU 106) or to individual floors or zones of building 10 (e.g., VAV units 116). The air handlers push air past heat exchangers (e.g., heating coils or cooling coils) through which the water flows to provide heating or cooling for the air. The heated or cooled air can be delivered to individual zones of building 10 to serve thermal energy loads of building 10. The water then returns to subplants 202-212 to receive further heating or cooling. Although subplants 202-212 are shown and described as heating and cooling water for circulation to a building, it is understood that any other type of working fluid (e.g., glycol, CO2, etc.) can be used in place of or in addition to water to serve thermal energy loads. In other embodiments, subplants 202-212 may provide heating and/or cooling directly to the building or campus without requiring an intermediate heat transfer fluid. These and other variations to waterside system 200 are within the teachings of the present disclosure.
Each of subplants 202-212 can include a variety of equipment configured to facilitate the functions of the subplant. For example, heater subplant 202 is shown to include a plurality of heating elements 220 (e.g., boilers, electric heaters, etc.) configured to add heat to the hot water in hot water loop 214. Heater subplant 202 is also shown to include several pumps 222 and 224 configured to circulate the hot water in hot water loop 214 and to control the flow rate of the hot water through individual heating elements 220. Chiller subplant 206 is shown to include a plurality of chillers 232 configured to remove heat from the cold water in cold water loop 216. Chiller subplant 206 is also shown to include several pumps 234 and 236 configured to circulate the cold water in cold water loop 216 and to control the flow rate of the cold water through individual chillers 232.
Heat recovery chiller subplant 204 is shown to include a plurality of heat recovery heat exchangers 226 (e.g., refrigeration circuits) configured to transfer heat from cold water loop 216 to hot water loop 214. Heat recovery chiller subplant 204 is also shown to include several pumps 228 and 230 configured to circulate the hot water and/or cold water through heat recovery heat exchangers 226 and to control the flow rate of the water through individual heat recovery heat exchangers 226. Cooling tower subplant 208 is shown to include a plurality of cooling towers 238 configured to remove heat from the condenser water in condenser water loop 218. Cooling tower subplant 208 is also shown to include several pumps 240 configured to circulate the condenser water in condenser water loop 218 and to control the flow rate of the condenser water through individual cooling towers 238.
Hot TES subplant 210 is shown to include a hot TES tank 242 configured to store the hot water for later use. Hot TES subplant 210 may also include one or more pumps or valves configured to control the flow rate of the hot water into or out of hot TES tank 242. Cold TES subplant 212 is shown to include cold TES tanks 244 configured to store the cold water for later use. Cold TES subplant 212 may also include one or more pumps or valves configured to control the flow rate of the cold water into or out of cold TES tanks 244.
In some embodiments, one or more of the pumps in waterside system 200 (e.g., pumps 222, 224, 228, 230, 234, 236, and/or 240) or pipelines in waterside system 200 include an isolation valve associated therewith. Isolation valves can be integrated with the pumps or positioned upstream or downstream of the pumps to control the fluid flows in waterside system 200. In various embodiments, waterside system 200 can include more, fewer, or different types of devices and/or subplants based on the particular configuration of waterside system 200 and the types of loads served by waterside system 200.
Airside SystemReferring now to
In
Each of dampers 316-320 can be operated by an actuator. For example, exhaust air damper 316 can be operated by actuator 324, mixing damper 318 can be operated by actuator 326, and outside air damper 320 can be operated by actuator 328. Actuators 324-328 may communicate with an AHU controller 330 via a communications link 332. Actuators 324-328 may receive control signals from AHU controller 330 and may provide feedback signals to AHU controller 330. Feedback signals can include, for example, an indication of a current actuator or damper position, an amount of torque or force exerted by the actuator, diagnostic information (e.g., results of diagnostic tests performed by actuators 324-328), status information, commissioning information, configuration settings, calibration data, and/or other types of information or data that can be collected, stored, or used by actuators 324-328. AHU controller 330 can be an economizer controller configured to use one or more control algorithms (e.g., state-based algorithms, extremum seeking control (ESC) algorithms, proportional-integral (PI) control algorithms, proportional-integral-derivative (PID) control algorithms, model predictive control (MPC) algorithms, feedback control algorithms, etc.) to control actuators 324-328.
Still referring to
Cooling coil 334 may receive a chilled fluid from waterside system 200 (e.g., from cold water loop 216) via piping 342 and may return the chilled fluid to waterside system 200 via piping 344. Valve 346 can be positioned along piping 342 or piping 344 to control a flow rate of the chilled fluid through cooling coil 334. In some embodiments, cooling coil 334 includes multiple stages of cooling coils that can be independently activated and deactivated (e.g., by AHU controller 330, by BMS controller 366, etc.) to modulate an amount of cooling applied to supply air 310.
Heating coil 336 may receive a heated fluid from waterside system 200 (e.g., from hot water loop 214) via piping 348 and may return the heated fluid to waterside system 200 via piping 350. Valve 352 can be positioned along piping 348 or piping 350 to control a flow rate of the heated fluid through heating coil 336. In some embodiments, heating coil 336 includes multiple stages of heating coils that can be independently activated and deactivated (e.g., by AHU controller 330, by BMS controller 366, etc.) to modulate an amount of heating applied to supply air 310.
Each of valves 346 and 352 can be controlled by an actuator. For example, valve 346 can be controlled by actuator 354 and valve 352 can be controlled by actuator 356. Actuators 354-356 may communicate with AHU controller 330 via communications links 358-360. Actuators 354-356 may receive control signals from AHU controller 330 and may provide feedback signals to controller 330. In some embodiments, AHU controller 330 receives a measurement of the supply air temperature from a temperature sensor 362 positioned in supply air duct 312 (e.g., downstream of cooling coil 334 and/or heating coil 336). AHU controller 330 may also receive a measurement of the temperature of building zone 306 from a temperature sensor 364 located in building zone 306.
In some embodiments, AHU controller 330 operates valves 346 and 352 via actuators 354-356 to modulate an amount of heating or cooling provided to supply air 310 (e.g., to achieve a setpoint temperature for supply air 310 or to maintain the temperature of supply air 310 within a setpoint temperature range). The positions of valves 346 and 352 affect the amount of heating or cooling provided to supply air 310 by cooling coil 334 or heating coil 336 and may correlate with the amount of energy consumed to achieve a desired supply air temperature. AHU 330 may control the temperature of supply air 310 and/or building zone 306 by activating or deactivating coils 334-336, adjusting a speed of fan 338, or a combination of both.
Still referring to
In some embodiments, AHU controller 330 receives information from BMS controller 366 (e.g., commands, setpoints, operating boundaries, etc.) and provides information to BMS controller 366 (e.g., temperature measurements, valve or actuator positions, operating statuses, diagnostics, etc.). For example, AHU controller 330 may provide BMS controller 366 with temperature measurements from temperature sensors 362-364, equipment on/off states, equipment operating capacities, and/or any other information that can be used by BMS controller 366 to monitor or control a variable state or condition within building zone 306.
Client device 368 can include one or more human-machine interfaces or client interfaces (e.g., graphical user interfaces, reporting interfaces, text-based computer interfaces, client-facing web services, web servers that provide pages to web clients, etc.) for controlling, viewing, or otherwise interacting with HVAC system 100, its subsystems, and/or devices. Client device 368 can be a computer workstation, a client terminal, a remote or local interface, or any other type of user interface device. Client device 368 can be a stationary terminal or a mobile device. For example, client device 368 can be a desktop computer, a computer server with a user interface, a laptop computer, a tablet, a smartphone, a PDA, or any other type of mobile or non-mobile device. Client device 368 may communicate with BMS controller 366 and/or AHU controller 330 via communications link 372.
Building Management Systems (BMS)Referring now to
Each of building subsystems 428 can include any number of devices, controllers, and connections for completing its individual functions and control activities. HVAC subsystem 440 can include many of the same components as HVAC system 100, as described with reference to
Still referring to
Interfaces 407, 409 can be or include wired or wireless communications interfaces (e.g., jacks, antennas, transmitters, receivers, transceivers, wire terminals, etc.) for conducting data communications with building subsystems 428 or other external systems or devices. In various embodiments, communications via interfaces 407, 409 can be direct (e.g., local wired or wireless communications) or via a communications network 446 (e.g., a WAN, the Internet, a cellular network, etc.). For example, interfaces 407, 409 can include an Ethernet card and port for sending and receiving data via an Ethernet-based communications link or network. In another example, interfaces 407, 409 can include a Wi-Fi transceiver for communicating via a wireless communications network. In another example, one or both of interfaces 407, 409 can include cellular or mobile phone communications transceivers. In one embodiment, communications interface 407 is a power line communications interface and BMS interface 409 is an Ethernet interface. In other embodiments, both communications interface 407 and BMS interface 409 are Ethernet interfaces or are the same Ethernet interface.
Still referring to
Memory 408 (e.g., memory, memory unit, storage device, etc.) can include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage, etc.) for storing data and/or computer code for completing or facilitating the various processes, layers and modules described in the present application. Memory 408 can be or include volatile memory or non-volatile memory. Memory 408 can include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present application. According to some embodiments, memory 408 is communicably connected to processor 406 via processing circuit 404 and includes computer code for executing (e.g., by processing circuit 404 and/or processor 406) one or more processes described herein.
In some embodiments, BMS controller 366 is implemented within a single computer (e.g., one server, one housing, etc.). In various other embodiments BMS controller 366 can be distributed across multiple servers or computers (e.g., that can exist in distributed locations). Further, while
Still referring to
Enterprise integration layer 410 can be configured to serve clients or local applications with information and services to support a variety of enterprise-level applications. For example, enterprise control applications 426 can be configured to provide subsystem-spanning control to a graphical user interface (GUI) or to any number of enterprise-level business applications (e.g., accounting systems, user identification systems, etc.). Enterprise control applications 426 may also or alternatively be configured to provide configuration GUIs for configuring BMS controller 366. In yet other embodiments, enterprise control applications 426 can work with layers 410-420 to optimize building performance (e.g., efficiency, energy use, comfort, or safety) based on inputs received at interface 407 and/or BMS interface 409.
Building subsystem integration layer 420 can be configured to manage communications between BMS controller 366 and building subsystems 428. For example, building subsystem integration layer 420 may receive sensor data and input signals from building subsystems 428 and provide output data and control signals to building subsystems 428. Building subsystem integration layer 420 may also be configured to manage communications between building subsystems 428. Building subsystem integration layer 420 translate communications (e.g., sensor data, input signals, output signals, etc.) across a plurality of multi-vendor/multi-protocol systems.
Demand response layer 414 can be configured to optimize resource usage (e.g., electricity use, natural gas use, water use, etc.) and/or the monetary cost of such resource usage in response to satisfy the demand of building 10. The optimization can be based on time-of-use prices, curtailment signals, energy availability, or other data received from utility providers, distributed energy generation systems 424, from energy storage 427 (e.g., hot TES 242, cold TES 244, etc.), or from other sources. Demand response layer 414 may receive inputs from other layers of BMS controller 366 (e.g., building subsystem integration layer 420, integrated control layer 418, etc.). The inputs received from other layers can include environmental or sensor inputs such as temperature, carbon dioxide levels, relative humidity levels, air quality sensor outputs, occupancy sensor outputs, room schedules, and the like. The inputs may also include inputs such as electrical use (e.g., expressed in kWh), thermal load measurements, pricing information, projected pricing, smoothed pricing, curtailment signals from utilities, and the like.
According to some embodiments, demand response layer 414 includes control logic for responding to the data and signals it receives. These responses can include communicating with the control algorithms in integrated control layer 418, changing control strategies, changing setpoints, or activating/deactivating building equipment or subsystems in a controlled manner. Demand response layer 414 may also include control logic configured to determine when to utilize stored energy. For example, demand response layer 414 may determine to begin using energy from energy storage 427 just prior to the beginning of a peak use hour.
In some embodiments, demand response layer 414 includes a control module configured to actively initiate control actions (e.g., automatically changing setpoints) which minimize energy costs based on one or more inputs representative of or based on demand (e.g., price, a curtailment signal, a demand level, etc.). In some embodiments, demand response layer 414 uses equipment models to determine an optimal set of control actions. The equipment models can include, for example, thermodynamic models describing the inputs, outputs, and/or functions performed by various sets of building equipment. Equipment models may represent collections of building equipment (e.g., subplants, chiller arrays, etc.) or individual devices (e.g., individual chillers, heaters, pumps, etc.).
Demand response layer 414 may further include or draw upon one or more demand response policy definitions (e.g., databases, XML files, etc.). The policy definitions can be edited or adjusted by a user (e.g., via a graphical user interface) so that the control actions initiated in response to demand inputs can be tailored for the user's application, desired comfort level, particular building equipment, or based on other concerns. For example, the demand response policy definitions can specify which equipment can be turned on or off in response to particular demand inputs, how long a system or piece of equipment should be turned off, what setpoints can be changed, what the allowable set point adjustment range is, how long to hold a high demand setpoint before returning to a normally scheduled setpoint, how close to approach capacity limits, which equipment modes to utilize, the energy transfer rates (e.g., the maximum rate, an alarm rate, other rate boundary information, etc.) into and out of energy storage devices (e.g., thermal storage tanks, battery banks, etc.), and when to dispatch on-site generation of energy (e.g., via fuel cells, a motor generator set, etc.).
Integrated control layer 418 can be configured to use the data input or output of building subsystem integration layer 420 and/or demand response later 414 to make control decisions. Due to the subsystem integration provided by building subsystem integration layer 420, integrated control layer 418 can integrate control activities of the subsystems 428 such that the subsystems 428 behave as a single integrated supersystem. In some embodiments, integrated control layer 418 includes control logic that uses inputs and outputs from a plurality of building subsystems to provide greater comfort and energy savings relative to the comfort and energy savings that separate subsystems can provide alone. For example, integrated control layer 418 can be configured to use an input from a first subsystem to make an energy-saving control decision for a second subsystem. Results of these decisions can be communicated back to building subsystem integration layer 420.
Integrated control layer 418 is shown to be logically below demand response layer 414. Integrated control layer 418 can be configured to enhance the effectiveness of demand response layer 414 by enabling building subsystems 428 and their respective control loops to be controlled in coordination with demand response layer 414. This configuration may advantageously reduce disruptive demand response behavior relative to conventional systems. For example, integrated control layer 418 can be configured to assure that a demand response-driven upward adjustment to the setpoint for chilled water temperature (or another component that directly or indirectly affects temperature) does not result in an increase in fan energy (or other energy used to cool a space) that would result in greater total building energy use than was saved at the chiller.
Integrated control layer 418 can be configured to provide feedback to demand response layer 414 so that demand response layer 414 checks that constraints (e.g., temperature, lighting levels, etc.) are properly maintained even while demanded load shedding is in progress. The constraints may also include setpoint or sensed boundaries relating to safety, equipment operating limits and performance, comfort, fire codes, electrical codes, energy codes, and the like. Integrated control layer 418 is also logically below fault detection and diagnostics layer 416 and automated measurement and validation layer 412. Integrated control layer 418 can be configured to provide calculated inputs (e.g., aggregations) to these higher levels based on outputs from more than one building subsystem.
Automated measurement and validation (AM&V) layer 412 can be configured to verify that control strategies commanded by integrated control layer 418 or demand response layer 414 are working properly (e.g., using data aggregated by AM&V layer 412, integrated control layer 418, building subsystem integration layer 420, FDD layer 416, or otherwise). The calculations made by AM&V layer 412 can be based on building system energy models and/or equipment models for individual BMS devices or subsystems. For example, AM&V layer 412 may compare a model-predicted output with an actual output from building subsystems 428 to determine an accuracy of the model.
Fault detection and diagnostics (FDD) layer 416 can be configured to provide on-going fault detection for building subsystems 428, building subsystem devices (i.e., building equipment), and control algorithms used by demand response layer 414 and integrated control layer 418. FDD layer 416 may receive data inputs from integrated control layer 418, directly from one or more building subsystems or devices, or from another data source. FDD layer 416 may automatically diagnose and respond to detected faults. The responses to detected or diagnosed faults can include providing an alert message to a user, a maintenance scheduling system, or a control algorithm configured to attempt to repair the fault or to work-around the fault.
FDD layer 416 can be configured to output a specific identification of the faulty component or cause of the fault (e.g., loose damper linkage) using detailed subsystem inputs available at building subsystem integration layer 420. In other exemplary embodiments, FDD layer 416 is configured to provide “fault” events to integrated control layer 418 which executes control strategies and policies in response to the received fault events. According to some embodiments, FDD layer 416 (or a policy executed by an integrated control engine or business rules engine) may shut-down systems or direct control activities around faulty devices or systems to reduce energy waste, extend equipment life, or assure proper control response.
FDD layer 416 can be configured to store or access a variety of different system data stores (or data points for live data). FDD layer 416 may use some content of the data stores to identify faults at the equipment level (e.g., specific chiller, specific AHU, specific terminal unit, etc.) and other content to identify faults at component or subsystem levels. For example, building subsystems 428 may generate temporal (i.e., time-series) data indicating the performance of BMS 400 and the various components thereof. The data generated by building subsystems 428 can include measured or calculated values that exhibit statistical characteristics and provide information about how the corresponding system or process (e.g., a temperature control process, a flow control process, etc.) is performing in terms of error from its setpoint. These processes can be examined by FDD layer 416 to expose when the system begins to degrade in performance and alert a user to repair the fault before it becomes more severe.
Air Quality Detection SystemReferring now to
The air quality detectors 504 can be positioned in different zones 506 of the building. The zones 506 can be located within or outside of the building 10. In some embodiments, the air quality detectors 504 can be located at a building that is not building 10. The detection controller 502 can obtain the air quality measurements from the air quality detectors 504. The air quality measurements can be location specific. For example, the air quality measurements collected by air quality detector 504a can be different than the air quality measurements collected by air quality detector 504b. The detection controller 502 can obtain the data from the air quality detectors 504. The air quality detectors 504 can be communicably coupled via a wired connection with the detection controller 502, or wirelessly (e.g., by communicating with the detection controller 502 via Bluetooth, LoRa, Zigbee, via cellular communications, a wireless network, a building WiFi network, etc.).
Detection controller 502 is configured to obtain the detection results from any of the air quality detectors 504 when results are available from the air quality detectors 504 (e.g., in a real-time basis, in near-real time, in 24 hour intervals, etc.). Detection controller 502 can obtain the detection results and analyze the detection results to identify the indoor air quality or the outdoor air quality. The detection controller 502 can be configured to use known locations of the different air quality detectors 504 and generate appropriate data (e.g., commands, analytical data, control signals, alert data, etc.) for any of a messaging system 508, a control system 510, an analytics system 512, a monitoring system 514, one or more service application system 516, and/or an alert system 518, etc., to perform one or more responsive actions in response to identifying the indoor air quality and the outdoor air quality for the building 10. In some embodiments, the detection controller 502 is also configured to generate and/or provide control signals to the HVAC system 100 of the building 10. In some embodiments, the detection controller 502 is configured to determine and provide informative data for the HVAC system 100 for use by the HVAC system 100 in determining control operations thereof. In some embodiments, the detection controller 502 provides different data to any of the messaging system 508, the control system 510, the analytics system 512, the monitoring system 514, the service application system 516, and/or the alert system 518 based on the indoor air quality and the outdoor air quality.
The detection controller 502 can use the indoor air quality and the outdoor air quality to determine which control operations can be performed to maintain or improve the indoor air quality. For example, the outdoor air quality can be used to determine if the outdoor air quality is above a predetermined threshold. If the outdoor air quality is above the predetermined threshold the detection controller 502 can determine that the indoor air quality can be controlled by recirculating and filtering the indoor air. Similarly, in some embodiments the outdoor air quality can be used to determine that the outdoor air quality is below the predetermined threshold. The detection controller 502 can use the outdoor air quality to determine that the indoor air quality can be controlled by recirculating and filtering the indoor air or by circulating outdoor air into the building 10. For example, the outdoor air quality of the building 10 can be impacted by a weather event, such as a forest fire. The detection controller 502 can determine that the indoor air quality can be controlled by closing an outdoor air intake, increasing filtration of the indoor air and recirculating the indoor air. In some embodiments, the detection controller 502 can use the indoor air quality and the outdoor air quality to determine that an indoor air quality metric is a result of the outdoor air quality. For example, the indoor PM 2.5 metric can be impacted by the pollen metric outside the building 10. Additionally, the detection controller 502 can determine that the indoor PM 2.5 metric can be improved by closing the outdoor air intake.
In some embodiments, the detection controller 502 is located on-site at building 10. In some embodiments, any of the systems 508-518 are located off-site (e.g., in a cloud computing system as part of a service). In some embodiments, the detection controller 502 is also located off-site (e.g., in a cloud computing system) and communicates with the air quality detectors 504 to obtain detection results.
In some embodiments, the detection controller 502 is configured to receive weather data from a data provider 520. The data provider 520 can be a database configured to provide seasonal and/or current weather data. The detection controller 502 may adjust the indoor air quality measurements or the outdoor air quality measurements based on the weather data. The detection controller 502 can use the data provided by the data provider 520.
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In some embodiments, the control system 510 is configured to use the air quality data obtained by the air quality detectors 504 and/or any outputs of the detection controller 502 as inputs to, or to train models of the systems and methods described in greater detail in U.S. application Ser. No. 16/927,759, filed Jul. 13, 2020, the entire disclosure of which is incorporated by reference herein.
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Memory 606 (e.g., memory, memory unit, storage device, etc.) can include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage, etc.) for storing data and/or computer code for completing or facilitating the various processes, layers and modules described in the present application. Memory 606 can be or include volatile memory or non-volatile memory. Memory 606 can include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present application. According to some embodiments, memory 606 is communicably connected to processor 604 via processing circuitry 602 and includes computer code for executing (e.g., by processing circuitry 602 and/or processor 604) one or more processes described herein.
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The air quality detection manager 610 can use any of the detection results, the detector data (e.g., the degree of locality of each of the air quality detectors 504) to determine or select a control action (e.g., a responsive action) from the response database 608. The air quality detection manager 610 can detect the indoor air quality and/or the outdoor air quality. The air quality detection manager 610 can select the control operation described herein to control the indoor air quality.
In some embodiments, the air quality detection manager 610 is configured to provide the control operation and/or any of the collected data to the reporting manager 614 and/or the control signal generator 612. The control signal generator 612 can generate control signals for equipment of the building 10 to implement the control operation, according to some embodiments. In some embodiments, the control signals are provided to the HVAC system 100. In some embodiments, the reporting manager 614 is configured to provide any of the control operations, or the collected data to any of the messaging system 508, the control system 510, the analytics system 512, the monitoring system 514, the service application system 516, or the alert system 518 so that the systems 508-518 can perform their respective functions.
Standard ComplianceReferring now to
The analysis system 702 can assess and determine the requisite operational mode of the Heating, Ventilation, and Air Conditioning (HVAC) system. One such operational mode is the ICM. In some embodiments, activation of the ICM may be prompted by a directive issued by a governing authority. This decision can be driven by public health objectives, either as a responsive measure to a health crisis or as part of a preventive strategy for public health preservation. In various embodiments, the determination to activate the ICM is in response to an escalation in the community spread of disease. For example, when the extent of a spread exceeds a certain threshold, the ICM can be automatically initiated by the analysis system 702 to attempt to inhibit the progression of an infectious disease within the enclosed environment.
In some embodiments, the HVAC system of the building can operate under various modes, each designed for specific conditions or purposes, and each with its own set of operational parameters. Standard X (e.g., ASHRAE 62) mode can represent a typical operational state for the HVAC system, maintaining comfort conditions for occupants while also adhering to industry standards for energy consumption and air quality. When elevated infection risk is detected or declared, the system can switch to ICM, in which infection control measures take precedence, with the HVAC system potentially operating at increased capacity or changing air distribution patterns to enhance airborne pathogen control.
Another mode of operation can be an energy optimization mode, designed to operate the HVAC system at an optimal energy-efficient point. In this mode, ventilation rates can be minimized in line with regulations and pathogen mitigation measures reduced to a safe minimum, to achieve the lowest possible energy usage. Additionally, a minimum energy solution to achieve a Standard Y (e.g., ASHRAE 241) mode can be implemented. In this mode, the BMC controller 366 would balance energy usage and compliance with a specific standard, such as a particular air quality standard, by operating the HVAC system in the optimal energy-efficient manner while still achieving the required standard. The HVAC system can switch between these modes of operation in response to various triggers or requirements, adjusting the building's HVAC operations to meet the present conditions. Specifically, the HVAC system can select and operate in an optimal energy efficiency mode to meet one or more standards. In some embodiments, the efficiency of air cleaning measures can vary over time (e.g., outdoor temperature can drive the variance). In various embodiments, the HVAC system can prioritize other objectives such as energy savings, sustainability, and cost savings, alone or in combination with the air cleaning standards.
In general, the infection control mode (ICM) may correspond to a predetermined set of parameters that govern how the building is to be operated in order to optimize infection control. For example, upon activation of the ICM, the HVAC system may be required to maintain an air turnover rate of 40 Cubic Feet per Minute (CFM) of clean air delivery per occupant in each particular space (e.g., area or zone) of a building. In some examples, ICM can recommend or necessitate changes in occupancy patterns within the building to meet a necessary airflow criteria. With reference to the above example, in order to comply with the 40 CFM of clean air delivery per person, the analysis system 702 may recommend the repositioning of staff members across different areas of the building. Additionally, in some embodiments, the analysis system 702 can generate an ICM metric. This ICM metric can be a quantitative metric that can serve as an objective indicator of the efficacy of the building's infection control measures under the prevailing operational parameters and/or sensor readings. In some embodiments, variables that contribute to this ICM metric can include, but is not limited to, current occupancy levels, total available space, HVAC capacity, and local disease prevalence rates. Accordingly, the ICM metric can provide real-time insights into the infection control status of the building.
In general, when a zone fails to meet the required standard for infection control, the analysis system 702 can notify the building manager to reduce occupancy until compliance is achieved. However, in some embodiments, alternative strategies can be adopted to increase the supply of clean air to the affected space. In some embodiments, the analysis system 702 can initiate HVAC ventilation. This refers to the outdoor air delivered by the HVAC system, measured by an outdoor-air flow sensor or estimated from CO2 timeseries data, increasing the concentration of fresh air in the indoor environment. Similarly, in some embodiments, the analysis system 702 can initiate HVAC recirculation. This involves the cleaned fraction of air recirculated from other zones by the HVAC system. The cleaning can be due to in-duct filtration or in-duct UV, with the efficacy measured by a supply-air flow sensor or calculated from outdoor-air flow and (measured or estimated) outdoor-air fraction. In some embodiments, the analysis system 702 can notify the building manager to deploy in-zone air-cleaning devices. These can be pure filtration devices or may also include contained UV devices where UV irradiation occurs inside the device. The effectiveness of these devices can be calculated based on the nameplate device airflow and disinfection fraction, which depends on the filter type and UV intensity. Additionally, the analysis system 702 can initiate in-zone UV irradiation in certain embodiments. This can involve upper-room standard UVC lamps or whole-room far UV (222 nm) lamps, with the effectiveness calculated from the irradiated volume and radiant intensity. In some embodiments, the analysis system 702 can determine the role of passive effects. These include natural particle deposition and deactivation, calculated based on the zone temperature and humidity. In some embodiments, airborne chemical treatment can initiated by the analysis system 702. This can include (bipolar) ionization, aerosolized cleaners (such as triethylene glycol, as used in Grignard Pure), and other methods that add chemicals to the air to actively deactivate infectious particles.
In some embodiments, occupancy sensors can be installed and/or integrated with the analysis system 702 to dynamically calculate compliance and optimize operations. For example, if the zone is 40% occupied, the required clean air is 40% of design. Specifically, the clear airflow can be reduced to save energy and still comply with a code or standard. In some embodiments, occupancy can further be measures use CO2 sensors.
In some embodiments, the analysis system 702 can assess whether the HVAC system is currently meeting, or at least is capable of meeting, the one or more standards as monitored. This evaluation can be facilitated through different modes, which can be tracked and visualized through a user interface (i.e., generated and presented by the content management system 704) to show daily compliance, both actual and simulated. In the ICM, the analysis system 702 operation can be regulated based on the advisories of authoritative bodies such as the CDC. In this mode, the Actual Clean-Air Delivery can be compared against the Target Clean-Air Delivery each day (or hourly, or weekly, etc.), and an alarm or notification can be raised if the target is not met. Furthermore, “Target Clean-Air Delivery” can be time varying based on occupancy. Additionally, a discretionary mode can be applied periodically, for example, quarterly, to verify that the system can actually meet the standard. This can include temporarily switching the system into the ICM, such as by accepting the optimal standard compliance recommendation. The checks conducted in this mode would be similar to when actually operating in ICM. The date for the discretionary check can be selected intelligently, for example, based on weather, to minimize extra energy consumption.
In some embodiments, in a simulated mode, the compliance check is performed by the analysis system 702 every day using a simulation model. In some embodiments, the analysis system 702 can generate compliance documents required by third-party inspection services (e.g., joint commission for hospitals). The generation can include populating standard documents as required, generating content related to collected data, aggregating data sets, and generating visual diagrams and charts. The clean-air delivery predicted for the maximum clean-air recommendation can be compared against the target. Days when the target is not met can be recorded for further analysis, such as determining whether an HVAC system upgrade or in-zone disinfection is necessary. The benefit of this mode is that the analysis system 702 doesn't actually have to be operated in the ICM, thus avoiding energy consumption or comfort penalties. This mode offers a cost-effective and efficient strategy for continuous monitoring and control of indoor infection risk. The simulated mode can predict whether compliance would be achieved if ICM were hypothetically activated. While this method may not be sufficient for full compliance verification, it has an advantage in that the simulated check can be conducted every day without incurring associated energy costs. This approach offers a cost-effective early warning system, alerting facilities management when the HVAC system can require modifications to meet indoor infection control standards.
In some embodiments, the analysis system 702 can also use ICM data to determine the maximum occupancy levels that each space in the building can sustain while still maintaining necessary infection control standards under ICM. Factors that contribute to this calculation can include the volume of the space, the current capacity of the HVAC system, and the target airflow rate per person (e.g., 40 CFM of clean air delivery per person). By comparing the HVAC's available clean air delivery rate to the target rate and accounting for the physical limitations of the space, the analysis system 702 can recommend an optimal maximum occupancy for each space. In response to the room occupancy exceeding the maximum occupancy capacity, the analysis system 702 can provide one or more user devices (e.g., occupants of the building or the particular area or space) an indication corresponding to the maximum occupancy being exceeded
In some embodiments, during the operation of the ICM, the analysis system 702 can receive and analyze various data relevant to infectious risk mitigation. This data, referred to collectively as ICM data, may include but is not limited to environmental data, operation and testing data of the HVAC equipment, and data obtained from various external sources. Environmental data can include information related to indoor air quality or building characteristics. For example, it can include parameters such as relative humidity, temperature, CO2 concentration, particulate matter levels, and presence of specific pathogens or contaminants in the air. Furthermore, the analysis system 702 can receive and analyze HVAC-specific data, which can include the Minimum Efficiency Reporting Value (MERV) rating of the system and current operational data, such as flow measurements, fan speed, temperature settings, and ventilation rates. Moreover, the analysis system 702 can collect/receive and analyze data from various external sources. For example, this can include community-level pathogen spread or prevalence data, obtained from healthcare databases or monitoring systems. In some embodiments, governmental data, such as directives and guidelines on disease prevention, and industry standards pertaining to indoor air quality and ventilation, may also be incorporated into the ICM data set.
In some embodiments, the analysis system 702 can use the collected ICM data to calculate an ICM metric for a specific target, such as a particular room, space, or area within the building. In some embodiments, this ICM metric can be based on the formula: prevalence×occupancy2/airflow, which can represent the expected number of transmissions. For example, if a conference room has an airflow of 1000 CFM, a local disease prevalence rate of 3% (scaling factor of 0.03), and current occupancy of 20 individuals, the ICM score would be computed as ((0.03*(20*20))/1000), resulting in an ICM score of 0.012. In another example, for a smaller office space with an airflow of 500 CFM, a local disease prevalence rate of 4% (scaling factor of 0.04), and a current occupancy of 5 individuals, the computation would be ((0.04*(5*5))/500), resulting in a lower ICM score of 0.002. In another example, room 101 may be listed at 55% (i.e., operating at 55% of ASHRAE 241 IRMM clean air), whereas room 202 may be listed at 105% (i.e., operating at 105% of ASHRAE 241 IRMM clean air).
In yet another example, the ICM metric can be calculated by multiplying the total CFM of the HVAC system by a scaling factor derived from the local disease prevalence rate, divided by the current occupancy level. For instance, if the total HVAC capacity is 4000 CFM, the local disease prevalence rate is 5% (converted to a scaling factor of 0.05), and the building has a current occupancy level of 80 individuals, the ICM score (i.e., ICM metric) would be calculated as (4000*0.05)/80, yielding an ICM score of 2.5. In yet another example, the ICM score can be calculated based on a total available space within the building. In this example, the ICM score can be computed as the product of the total HVAC capacity and the total available space, scaled by the local disease prevalence rate, and divided by the square of the current occupancy level. In this example, the calculation would give more weight to both the HVAC capacity and available space in the building, and a greater emphasis on reducing occupancy. For example, if the total HVAC capacity is 4000 CFM of clean air delivery, the total available space is 2000 square feet, the local disease prevalence rate is 5% (converted to a scaling factor of 0.05), and the building has a current occupancy of 80 individuals, the ICM score would be calculated as ((4000*2000*0.05)/(80*80)), resulting in an ICM score of 6.25.
In addition, the analysis system 702 can also take into account the contributions of supplementary infection control measures implemented within the building when calculating the ICM metric. In some embodiments, if the building incorporates in-zone disinfection units, the system can credit the additional air purification capabilities they provide. Similarly, the analysis system 702 can recognize the impact of certain actions, such as determining if windows have been opened to increase natural ventilation or incorporating UV lights in designated areas (e.g., kill tunnels or upper room UVGI), which contribute to enhanced disinfection efforts. For example, if the building employs an in-zone disinfection unit that delivers an additional 500 CFM of purified air, this additional capacity can be added to the total HVAC capacity in the ICM calculation (i.e., increasing the ICM score). Similarly, if a UV light system in a kill tunnel is determined to reduce pathogen presence by 30%, this can correspondingly reduce the local disease prevalence rate utilized in the calculation, yielding a lower ICM score. Alternatively, if windows are opened and estimated to increase natural ventilation by 10%, this increase can be incorporated into the total HVAC capacity, augmenting the ICM score and thereby reflecting the benefit of natural ventilation.
It should be understood that the ICM metric calculation methods demonstrated herein are illustrative examples and not exhaustive. The flexibility of the analysis system 702 allows for the application of various calculations. Examples of such calculations can include those factoring in regional airflow patterns, accounting for variations in HVAC efficiency or filter quality, assessing the impact of room layout on aerosol distribution, analyzing effects of differing human behavior patterns on disease transmission risk, considering the role of building materials in disease spread, among others.
In various embodiments, the analysis system 702 can use this calculated clean air delivery metric (i.e., ICM metric) along with a given occupancy and the standard requirement, such as 40 CFM of clean air delivery per person in ICM, to determine if the building is maintaining compliance with one or more infection control standards. If discrepancies are found, the analysis system 702 can generate alerts or notifications to the relevant personnel. For example, the analysis system 702 may recommend that occupancy levels in specific areas be reduced to meet the required air change rate, or that HVAC setpoints be adjusted, such as increasing airflow or modifying temperature settings. In some embodiments, the analysis system 702 can recommend supplementary measures to enhance indoor air quality, such as opening windows to increase natural ventilation, activating ultraviolet (UV) light systems or kill tunnels (e.g., positioned in air ducts) for pathogen neutralization, modifying filtration settings, or upgrading to higher MERV filters, as appropriate.
In some embodiments, the analysis system 702 can also be configured to test and validate the infection control mode (ICM), where the analysis system 702 evaluates the readiness and effectiveness of various building systems, specifically the HVAC system, to transition into ICM if necessary. That is, a building inspection mode (BIM) can be activated as a proactive measure to verify the proper functioning of all systems under an activated ICM. For example, the BIM can be configured to determine if the HVAC system and other equipment will function adequately should the ICM be activated. In the BIM mode, the analysis system 702 can initiate compliance testing. This can include temporarily activating and operating equipment as if the ICM were in effect, thus simulating the conditions under which these systems would operate during a real-world infection control scenario. In some embodiments, during the temporary activation of equipment, temporary sensors can be installed throughout the building to gather data when the BIM is activated. Accordingly, BIM is a real-time test of the system's capability to meet the requirements of ICM and maintain an environment that aligns with one or more infection control standards.
In some embodiments, the analysis system 702 can validate the environment, specific spaces within a building that are used as benchmarks to assess the current state of the overall building. These validated environments, chosen for their representative characteristics such as size, layout, HVAC system capacity, and typical occupancy, can be monitored. By monitoring these spaces, the analysis system 702 can establish baseline ICM metrics and determine the real-world operation of the building's systems under ICM conditions. In the event of changes in the building's operational status or in response to updated infection control guidelines, these validated environments can serve as a point of reference for recalibrating the building's ICM parameters. Specifically, a validated environment refers to one or more spaces within a building that are selected as benchmarks to evaluate the building's overall condition. These environments are characterized by factors like size, layout, HVAC system capacity, and unusual occupancy levels, allowing for continuous monitoring to establish baseline ICM metrics and assess the building's system performance under ICM conditions.
In some embodiments, the analysis system 702 can measure and calculate various parameters to evaluate the current performance and efficiency levels of the HVAC system and other equipment. For example, the analysis system 702 can determine if the building is currently meeting 90% of the standards set by guidelines such as ASHRAE Standard X (e.g., standard 241, standard 62), and how much energy is being consumed to achieve that level of compliance. Through BIM testing and validation, the analysis system 702 can determine the present operational status of the building's systems. That is, the testing and validation conducted in BIM can provide a predictive function and a comprehensive record of the building's state of readiness and response. For example, these logs, recording the real-time and historical operational status of the building's systems, can be presented as evidence to governmental bodies, such as code inspectors, to demonstrate compliance with relevant standards and regulations. Additionally, the logs can provide building operators proof of state over time of the HVAC system when ran in ICM.
In some embodiments, the analysis system 702 can intermittently activate the BIM. Under this mode, the building's systems, including the HVAC system, operate as if in a high-risk infection scenario. For example, an objective of the BIM can be to achieve a clean air delivery rate of X cubic feet per minute (CFM) of clean air delivery per person (e.g., 10, 20, 30, 40, 50, 100 CFM/person, etc.), a target aligned with one or more certain infection control guidelines or standards. To reach this benchmark, the HVAC system's operational parameters may be dynamically adjusted. For example, ventilation rates may be increased up to maximize the intake of fresh, uncontaminated air. Similarly, temperature and humidity settings can be altered to levels that are less conducive to the survival and spread of infectious pathogens. Additionally, air filtration effectiveness can be optimized through adjustments in fan speeds or temporary engagement of higher efficiency filters, if available. Accordingly, these adaptations can mimic the demands that would be placed on the HVAC system during activated of the ICM. The HVAC system's responses and overall performance during BIM activation can be tracked and recorded.
In some embodiments, the analysis system 702 can generate recommendations to improve the building's readiness for potential changes in environmental conditions or health-related standards. Based on an analysis of current occupancy levels, HVAC capacity, local disease prevalence rates, and other pertinent factors, the analysis system 702 can identify areas of potential improvement and recommend actionable measures. These recommendations can include suggestions such as adjusting the HVAC's airflow rates, altering the timing or extent of filtration cycles, or implementing additional pathogen mitigation measures such as in-zone disinfection units or increased ventilation.
Referring to the content management system 704 generally, the content management system 704 can use the clean-air solution, where values representing both the current state (e.g., calculated from actual data) and each of the recommended options (e.g., estimated via simulation) are displayed on a user interface. The average occupancy can be measured by occupancy-counting sensors/algorithms if available, or otherwise assumed equal to some fraction of design occupancy. The target clean-air delivery can be computed from the average occupancy and the values from one or more standards. The actual clean-air delivery can be computed by the existing model from airflow and other data. Additionally, a calculation of maximum compliant occupancy can be performed, providing the highest number of occupants that would comply with the standard based on the actual clean-air delivery. An ASHRAE 241 compliance score would also be displayed. This 0-100 score indicates compliance with the standard, calculated from the ratio of actual to target clean-air delivery in a lookup table (e.g., 0% leads to 0 points, 100% results in 90 points, 200% yields 100 points, with linear interpolation). Additionally, the ICM metric can also be displayed.
Accordingly, in some embodiments, the content management system 704 may be configured to implement an infection risk score as a compliance indicator with ASHRAE 241 standards. In particular, the infection risk score may be calculated by dividing the amount of clean air delivered to a space by the amount of clean air required as per the standard guidelines. In some embodiments, the 0-100 score can be an infection risk score indicative of the amount of clean air delivered divided by the amount a model determines is necessary or optimal based on, for example, the ASHRAE standard. For example, a score of 50 would indicate the building is operating at 50% of the target level of pathogen free air. In some embodiments, the infection risk score is derived from a formula that is interpretable by building operators, providing a percentage indicative of compliance with ASHRAE 241.
The content management system 704 may utilize specific clean air delivery rates such as 50 CFM/person to align with ASHRAE 241 standards. In some implementations, such specific clean air delivery rates may be used in buildings where clean air delivery metrics are considered important (e.g., stadiums). In some embodiments, the numerator in the infection risk score formula may represent the actual amount of clean air delivered, which can be measured against the ASHRAE 241 standards, to determine a score ranging from 0 to 100. In some embodiments, the score may be adapted to reflect compliance with other building health standards by adjusting the required amount of clean air delivery in the score's formula. For example, the content management system 704 may calculate different scores based on the standards for ventilation rates as per ASHRAE 62.1, or infection reduction goals outlined in public health guidelines or standards. It should be understood that the infection risk score is not limited to a range of 0 to 100 and may exceed 100 when the actual environmental performance surpasses the target conditions set by the standards. It should also be understood that the infection risk score is not limited to a numerical range and alternative representations, such as color-coded indicators, graphical scales, or categorical levels, may be employed to convey the compliance level with the one or more standards.
In some embodiments, the content management system 704 may further be configured to compare gas phase pollutants and calculate a score that indicates the building's compliance with standards targeting gas phase contaminant reduction (i.e., identify general health and wellbeing of occupants). For example, the score may reflect how effectively the building's air handling system removes specific chemical contaminants relative to the levels prescribed by health standards. In some embodiments, the content management system 704 may also calculate scores for particle filtration effectiveness, providing a metric that indicates compliance with standards for particulate matter reduction. For example, the score may assess the capability of air filtration systems in removing particles of various sizes, including those relevant to infectious disease transmission. In some embodiments, the content management system 704 may compute an infectious phase score, which indicates the building's overall risk level for infectious diseases based on the air handling system's performance relative to the guidelines set by ASHRAE 241 and other health standards. Non-limiting examples of environments and circumstances where this score can be relevant include, but are not limited to, in healthcare settings or during times of heightened public health concerns, such as a pandemic.
In some embodiments, the content management system 704 utilizes specific quantitative benchmarks to calculate the aforementioned scores, tying directly into compliance standards such as ASHRAE 241. For example, if ASHRAE 62.1 specifies that the outside air ventilation rate should result in a CO2 measurement of 1200 parts per million (ppm) of carbon dioxide (CO2) during occupancy, the content management system 704 may calculate a gas phase score by comparing the measured CO2 levels to this standard. If the building's air handling system reports CO2 levels at 850 ppm, the score would reflect a 100% compliance rate (i.e., Current CO2 reading—400/Required CO2 reading—400), whereas levels at 750 ppm would result in a lower score, indicating only 66% compliance, since the actual levels are 50% higher than the standard allows. Similarly, for particle filtration effectiveness, if the standard requires a system to remove 95% of particles sized 0.3 microns, and the system is tested to remove 96%, the score may reflect a higher compliance rate exceeding 100%. In contrast, a 90% removal rate would yield a score that indicates non-compliance, prompting necessary adjustments.
In some embodiments, the infectious phase score computed by the content management system 704 can reflect the building's compliance with ASHRAE 241's air change rate per hour (ACH) standards to mitigate airborne infection risk. For example, if a building achieves the standard ACH of 6, the score would indicate low infection risk. However, an actual ACH of 4 would yield a score of approximately 66.67, signifying that the building is operating at two-thirds the recommended level for infection control. Accordingly, these scores can computed in real-time (or near real-time) and can provide immediate feedback for building operators to address any discrepancies, facilitating continuous alignment with the a standard (e.g., ASHRAE 241, infection reduction standard, ASHRAE 62.1).
It should be understood that various embodiments discussed herein discuss features relating to monitoring and/or modifying performance to satisfy the ASHRAE 241 standard, but in various other embodiments, the present features can be used to meet any type of standard or target metrics, and all such modifications are contemplated within the scope of the present disclosure.
In some incorporations, content management system 704 can be configured to interface with a room allocation system to increase compliance with one or more infection control standards. This content management system 704 can dynamically change the number of spaces available in a room based on the mode of operation at the time. The infection control mode (ICM) is one of the modes of the HVAC system that may assessed and acted upon by the content management system 704. In some circumstances, the activation of the ICM may be initiated by a government order. After the initiation of the ICM the content management system 704 can generate and modify content presented within the building and to user of the building to provide.
Generally, the ICM may correspond to predetermined indicators that can be used by the content management system 704 to monitor and regulate how the building is to be occupied in order to maintain compliance with the one or more infection control standards. For example, immediately after activation of the ICM, the meeting room panel may be programmed to display a decreased room occupancy based on the configuration of the room allocation system. In some embodiments, the ICM can automatically set how many occupants may be set in a room allocation to increase compliance. In this example, in order to comply, the content management system 704 may determine which spaces are compliant, can be compliant, or are not compliant by using the floor plans (or other building data). In some embodiments, the content management system 704 may recommend the installation of zone disinfection units to bring over occupied rooms into compliance. Further, in some embodiments, the content management system 704 can use periodic compliance checks to track compliance over time. Accordingly, the activation of the test over time under this mode can provide accurate insights into the compliance status of the building during ICM.
In some embodiments, the content management system 704 can collect or receive various data inputs to generate targeted and specific content. Data inputs may include current occupancy levels, air quality indicators, ventilation rates, and building compliance status relative to infection control standards. Upon receiving these data inputs, the content management system 704 processes this information through a set of pre-defined algorithms or models (e.g., AI, GAI) to generate relevant content. The content generation process may involve formatting the information into understandable messages, incorporating real-time updates, and selecting an appropriate delivery medium for each piece of content. The content management system 704 can dynamically adapt the content based on ongoing changes in the data inputs. In some embodiments, the content management system 704 can distribute the generated content or changes to various systems via application programming interfaces (APIs). APIs allow the system 704 to establish communication with different systems, such as room allocation system, booking platforms, HVAC control systems, digital signage systems, and mobile applications used by the building occupants.
In some embodiments, during the operation of the ICM, the content management system 704 can analyze numerous data based on occupancy in spaces relevant to infectious risk diminution. This ICM data may include ventilation flow, clean air delivery, and IAQ audit, among others. To measure compliance, ventilation flow data may be assessed through an estimate of airflow and occupancy without the use of sensors. Further, clean air delivery may be calculated through the installation of temporary sensors and assessment of steps needed to comply. Moreover, a measure of compliance may be obtained using CO2 measurements along with ventilation rates. All these measurements may be assessed to determine overall compliance with the one or more infection control standards once ICM has been entered into and to regulate the number of rooms or spaces available for use in accordance with the compliance guidelines.
In some embodiments, the content management system 704 can use accumulated data to calculate compliant room occupancy. For instance, room occupancy can be measured by evaluating building data, room data, and an overall assessment of the space. For example, these measurements may be used to assess which rooms should be disabled to keep the building in compliance. Accordingly, the content management system 704 in communication with the room allocation system, may prohibit room reservations if the data displays a risk of going over occupancy and causing noncompliance by displaying (or providing) room occupancy on meeting room panels. Further, the content management system 704 can dynamically change the number of spaces (e.g., on a calendar, via a booking system) available in a room based on the mode of operation to increase compliance. For example, in a room with a usual occupancy of sixty people, compliance may be attained by dividing the number of people by 4 and controlling occupancy within the space by moving people to different spaces. In another example, meeting rooms that would risk noncompliance can also be hidden or shown as unavailable to prevent occupants from entering thereby increasing steps towards compliance.
In some embodiments, the content management system 704 can use this calculated room occupancy measurement along with the compliance standard to assess if the building is preserving compliance in accordance with ICM standards. If there are deviations from the infection control standard(s), the content management system 704 can dynamically modify the room occupancy number displayed on meeting room panels or using the room allocation system, disable rooms that can cause noncompliance. For example, the content management system 704 can recommend the use of reservation systems for cubicles and meeting rooms.
For example, the content management system 704 can interface with a building's internal public announcement system, generating audio alerts or notifications that inform occupants of current infection control standards and building's compliance status. These notifications can include real-time updates on optimal occupancy numbers, the need for additional safety measures, or changes in the building's operation due to ICM. In another example, the content management system 704 can interact with digital signage within the building, presenting visual updates regarding the building's compliance with infection control standards. For instance, this can involve dynamically changing digital posters or electronic billboards to reflect current ventilation rates, air quality indexes, and optimal occupancy levels. In yet another example, the content management system 704 can interface with a building's mobile application or web portal. It can push notifications or updates related to the building's compliance with infection control standards directly to occupants' smartphones or computers. This can involve updates about specific rooms' compliance status, recommendations for occupancy adjustments, or alerts regarding changes in the building's operational mode.
In some embodiments, the content management system (CMS) 704 can be configured to generate a graphical representation of compliance of a building for various standards or set requirements. For example, the CMS 704 can calculate the clean air delivery rate for each room or designated space within the building and compares it with the targeted clean air delivery rate. In some embodiments, the target can be determined by the occupancy of each space and the benchmark standard of CFM per person under the ICM. To create the graphical representations, the CMS 704 can color codes (or provide an indication) in each space based on its level of compliance with the target clean air delivery rate. For example, spaces that are meeting or exceeding the target can be represented in green on a heat map, while those that are not may be colored in red on the heat map.
In instances where a room is not meeting the target, the analysis system 702 can suggest possible remedial measures, such as reducing the occupancy of the space, adjusting the HVAC settings, or employing additional infection control measures. Additionally, the CMS 704 can output graphical representations that can be interacted with to select or adjust the HVAC system using the remedial measures. In some embodiments, the CMS 704 can utilize a combination of different data sources and estimation methods to derive an estimation of the building's compliance status. For example, CO2 measurements and ventilation rates can be employed to estimate occupancy and airflow respectively.
In some embodiments, the CMS 704 can communicate with the building's internal systems, including room booking and scheduling systems, to implement and enforce the ICM parameters. For example, if a space within the building is approaching or has already exceeded its safe occupancy limit (e.g., as determined by the target clean air delivery rate of that space), the CMS 704 can automatically prevent further room bookings via the building's booking system. In another example, the CMS 704 can also interface with an email exchange service used for scheduling meetings or events. If a proposed invitee list for a meeting exceeds the safe occupancy limit of the designated room, the CMS 704 can suggest an alternative, larger venue or limit the number of invitees.
In some embodiments, the analysis system 702 can be configured to provide an override mode (e.g., via a graphical interface generated by CMS 704) which can temporarily supersede the ICM activation (e.g., when building operators have implemented alternative pathogen mitigation measures). For example, if end-zone disinfection units, such as ultraviolet (UV) light systems or high-efficiency particulate air (HEPA) filters, have been added to the building, the risk of airborne infection may be sufficiently mitigated, thereby reducing the necessity for strict adherence to the ICM's guidelines. When activated, the override mode allows for the adjustment of building operations to a level that balances energy efficiency and comfort with the enhanced infection control provided by these additional measures. In some embodiments, the analysis system 702 continues to monitor parameters and can reactivate ICM if it determines that the risk level has increased beyond a pre-determined threshold. In some embodiments, the CMS 704 can determine and provide the various trade-offs associated with compliance to the ICM. In particular, the CMS 704 can analyze and synthesize data from different sources, such as the HVAC system's operational parameters, current occupancy levels, and other data (generally referred to herein as the ICM data set).
In some embodiments, the content management system 704 can facilitate automatic adjustments of setpoints on a daily basis, depending on the mode chosen by the building managers. In some embodiments, the mode selection can also be automated based on user preferences, predicted occupancy, and weather conditions. One such mode can be the “Optimal Standard Compliance”, which minimizes energy such that the actual clean-air delivery is greater than or equal to the target clean-air delivery. This mode would be in addition to the three existing recommendations and would be set as the default mode for Infection-Control Mode, but building managers can choose an option with extra airflow if they prefer. Another mode, the “User-Chosen Standard Multiplier”, allows the building manager to specify the fraction of the standard target that they want to meet, which can be higher or lower. This target fraction can be adjusted automatically based on community prevalence or other data.
Standard Compliance ProcessesReferring now to
In broad overview of method 800, at 810, the controller can receive an activation signal corresponding to an infection control mode. At 820, the controller can initiate the ICM including activating one or more interventions. Additional, fewer, or different operations may be performed depending on the particular arrangement. In some embodiments, some, or all operations of method 800 may be performed by one or more processors executing on one or more computing devices, systems, or servers. In various embodiments, each operation may be re-ordered, added, removed, or repeated.
Referring to method 800 in more detail, at block 810 the controller can receive an activation signal corresponding to an infection control mode (ICM). In some embodiments, the activation signal can be prompted by changes in public health guidelines or directives issued by governmental agencies, or by a surge in community spread evidenced by an increased local disease prevalence rate. The activation signal can be received in the form of digital notifications from public health databases or via a manual input from building management, aligning the operational procedures with health data. The signal can contain information, such as the type of pathogen involved, its transmission mode, and recommended preventative measures. In certain instances, the activation signal can be auto-generated by the controller itself, based on predefined trigger conditions such as a certain threshold of IAQ data, or external data feeds such as real-time public health advisories. Upon receiving this signal, the controller can then transition the building's operational state into the ICM, initiating a range of interventions aimed at minimizing the risk of airborne pathogen transmission and enhancing overall indoor air quality.
At block 820, the controller can initiate the ICM including activating one or more interventions, wherein the one or more interventions include operating HVAC equipment of the building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards. Upon receiving this signal, the controller is configured to initiate the necessary protocols to transition the building's operational mode into the ICM. This transition can involve adjusting various settings on the HVAC equipment, updating the algorithms used for environmental data analysis, and engaging with other interconnected systems within the building. To activate these interventions, the controller can adjust the HVAC equipment's settings, such as fan speeds, damper positions, and temperature setpoints, to enhance the system's air purification capability and meet the enhanced air change rates required under ICM.
In some embodiments, the controller can interface with supplementary infection control devices, such as UV disinfection systems, to improve the effectiveness of the overall infection control strategy. The controller can also interface with security systems to monitor and regulate occupancy levels, verifying that the clean air delivery rates per occupant are within the thresholds specified by the ICM. Throughout the execution of the ICM, the controller continuously monitors the indoor environment and makes adjustments to maintain compliance with the infection control standards.
In some embodiments, the controller can meet the ICM requirements and facilitate compliance with predefined infection control standards. For example, in response to an ICM requirement for increased air change rates to mitigate airborne pathogen transmission, the controller can adjust the HVAC settings to increase ventilation rates significantly above baseline levels. This adjustment can involve recalibrating fan speeds, optimizing damper positions for maximum airflow, and enhancing filter operation to capture a higher percentage of airborne contaminants. Simultaneously, to maintain an environment that adheres to infection control standards, the controller operates within a set of parameters that facilitate air quality indices, such as particulate matter concentration, CO2 levels, and humidity, are kept within the thresholds defined by health and safety guidelines. This can involve a separate set of operations, such as engaging UV-C air sterilization units when sensors detect particulate matter levels that exceed acceptable standards, or adjusting humidity controls to maintain an environment that is less conducive to pathogen survival and transmission.
In some embodiments, initiating the ICM to meet the specific ICM requirements can inherently include maintaining an environment that adheres to established infection control standards. The two objectives can be integrated within the operational strategy of the controller. Specifically, meeting ICM requirements, such as elevated air change rates or enhanced filtration efficiency, can simultaneously contribute to the broader objective of maintaining a safe and healthy indoor environment. For example, when the controller increases ventilation rates to reduce pathogen load in the air as part of the ICM, this action also supports the continuous achievement of air quality standards by facilitating adequate fresh air intake and dilution of indoor pollutants.
In various embodiments, the range of potential interventions can encompass various strategies to optimize the clean air delivery and thereby reduce the risk of airborne pathogen transmission. For example, the controller can increase the frequency of air changes, enhance the filtration efficiency by adjusting filter settings or recommending a filter upgrade to a higher MERV rating. In another example, if the building has variable air volume (VAV) systems, the controller can override the minimum air volumes to increase airflow. In yet another example, the controller can also engage heat recovery ventilators to augment fresh air supply, or activate humidifiers or dehumidifiers to maintain optimal humidity levels which can influence pathogen survivability. In yet another example, in response to real-time occupancy data, the controller may selectively activate zonal controls, verifying that areas with higher occupancy receive priority in clean air delivery. In yet another example, the controller can interface with lighting controls to reduce the use of lights when areas are unoccupied, minimizing heat generation and reducing the HVAC load.
In some embodiments, the controller can generate a graphical representation displaying (or providing) compliance levels of a plurality of spaces within the building, wherein the graphical representation includes an indication of the infection risk score and an indication whether the plurality of spaces meeting the one or more infection control standards and operate the HVAC equipment based on changes in occupancy levels, wherein operating includes adjusting HVAC system parameters. In generating the graphical representation, the controller can utilize the real-time data collected from various sensors distributed throughout the building. This data can include parameters such as air quality metrics, occupancy counts, and HVAC operational statuses. By algorithmically modeling and translating these parameters into a visual format, the controller can create a compliance map of the building. This compliance map can utilize color gradations or numerical scoring to indicate the compliance level of each space within the building, based on the defined infection control standards. The graphical representation can be dynamically updated to reflect real-time changes in the building's conditions. It can also be layered with additional data visualizations, such as HVAC operational parameters, sensor readings, or occupancy levels, to provide a view of the building's state under the infection control mode.
In some embodiments, the controller can determine a minimum energy solution that is compliant with the one or more infection control standards. In particular, determining the minimum energy solution can include (1) calculating an optimal one or more HVAC system parameters to balance between HVAC capacity and energy usage that satisfies the one or more infection control standards, (2) modifying the one or more HVAC system parameters based on conditions of the building in response to real-time data collected from temporary sensors or permanent sensors installed within the building, and (3) monitoring and updating the minimum energy solution as the conditions of the building change. For example, the minimum energy solution can include adopting a control schedule of the HVAC system's various components, such as adjusting damper positions for optimal airflow or modulating fan speeds according to occupancy levels. In another example, the minimum energy solution can include strategically timing the activation of energy-intensive infection control measures (e.g., UV disinfection units), to coincide with periods of high occupancy or heightened infection risk. In some embodiments, the controller can also (1) determine a minimum operating cost that is compliant with the one or more infection control standards, (2) determine a minimum energy and maintenance cost that is compliant with the one or more infection control standards, and/or (3) determine a minimum sustainability cost that is compliant with the one or more infection control standards.
In some embodiments, the controller can initiate additional infection control measures including at least one of activating in-room ultraviolet (UV) light units, increasing airflow of the HVAC system, adjusting occupancy levels of the building, or adjusting filtration capabilities of the HVAC equipment. In some embodiments, the initiation can in response to the actual environmental condition after a period of time (e.g., 1 hour, 1 day) being below or outside the one or more infection control standards. In some embodiments, the controller can have pre-programmed operational interfaces or APIs to communicate with the various devices and systems involved in infection control measures and the ICM. For example, the controller can interact with the UV light systems via a digital interface, instructing the devices to activate or adjust their disinfection cycle times as required. To increase airflow, the controller can adjust the fan speed or damper positions of the HVAC system, utilizing real-time feedback from sensors to fine-tune the system's performance. For occupancy adjustments, the controller can interface with the building's access control or security systems to monitor real-time occupancy levels and, if necessary, limit entry to certain areas to maintain compliance with infection control standards. Similarly, the controller can manipulate the filtration capabilities of the HVAC equipment, for example, by adjusting the operational parameters of the system or signaling for the replacement of filters when their efficiency falls below a set threshold. Furthermore, the controller can also adjust the operation of in-room air-cleaning devices, which can include standalone air filters or combined UV/filter units. This adjustment can be made based on the ICM data and can include increasing or decreasing the air-cleaning cycles or intensity to maintain the infection control standards within the room or space.
In some embodiments, the controller can determine one or more spaces within the building as validated environments, in response to determining the one or more spaces, monitor ICM data of the one or more spaces to assess a current state of the building, and provide the current state of the building. For example, the controller can continuously collect and analyze ICM data from a network of sensors strategically positioned throughout the identified spaces. This real-time data can include information like temperature, humidity, particulate counts, and other air quality indicators, giving the controller a detailed understanding of the indoor environment's state. In some embodiments, upon processing this data, the controller can then generate a report detailing the current state of the building, including any deviations from infection control standards. This report can be transmitted digitally to relevant stakeholders such as building managers, maintenance teams, or health and safety officials.
Referring to methods 800 and 900, for example at block 830 of method 800, the controller can determine an infection risk score that reflects the adherence of the building's HVAC equipment to established infection control standards. For example, the infection risk score can be derived by comparing the real-time data against predefined benchmarks to quantify the building's compliance level. In some embodiments, the infection risk score can computed by analyzing the actual environmental conditions within the building, such as the air change rate per hour (ACH), levels of specific airborne contaminants, particulate matter (PM) concentration, or one or more other measured values, and comparing these measurements to the target environmental conditions. That is, the infection risk score can indicate the percentage of compliance with each critical parameter set by the infection control standards. For example, the ACH can be measured against the recommended rates for different occupancy levels and room types. The target conditions can be based on predetermined values outlined in the infection control standards, which may include ASHRAE standards or government health guidelines, such as ASHRAE 241. For example, these guidelines can specify minimum ventilation rates or maximum allowable concentrations of certain contaminants. In some embodiments, the controller uses this comparison to generate an infection risk score. That is, the score can integrate multiple IAQ parameters to provide an overall assessment of the building's air quality and infection control status. For example, the infection risk score can be a weighted average of individual compliance scores for factors like CO2 levels, particulate matter, and VOCs.
In some embodiments, at block 830 or in method 900, the infection risk score is generated by a formula that quantifies the extent of compliance with the infection control standards. For example, the score can be calculated using the ratio of the actual environmental condition to the target condition, such as the actual ACH divided by the target ACH, multiplied by 100 to yield a percentage score. This score is then provided to the building operators, serving as a concise indicator of the current infection control status within the building. In one example, the controller can determine an actual environmental condition of the building maintained by the HVAC system by collecting data from environmental sensors installed throughout the building or within HVAC equipment. These sensors can measure real-time parameters such as temperature, humidity, particulate matter (PM) concentration, and specific airborne contaminant levels. The controller can process this data to assess the current state of the building's environment against predefined thresholds and performance targets set by relevant health standards.
In some embodiments, the infection risk score is generated by a formula or mathematical function that quantifies the extent of compliance with the infection control standards. For example, the score can be calculated using the ratio of the actual environmental condition to the target condition, such as the actual ACH divided by the target ACH, multiplied by 100 to yield a percentage score. The score can then be provided to the building operators, serving as an indicator of the current infection control status within the building. For example, the controller can determine an actual environmental condition of the building maintained by the HVAC system by collecting data from environmental sensors installed throughout the building or within HVAC equipment. The sensors can measure real-time parameters such as temperature, humidity, particulate matter (PM) concentration, and specific airborne contaminant levels. The controller can process this data to determine the current state of the building's environment against predefined thresholds and performance targets set by relevant health standards.
For example, in an implementation where the target clean air delivery rate is specified by ASHRAE standards as 20 cubic feet per minute (CFM) per person, if the actual clean air delivery measured by the HVAC system is 15 CFM per person, the infection risk score would be calculated by the formula
resulting in a score of 75. This score, reflecting the HVAC system's operation at 75% of the ASHRAE-recommended clean air delivery rate, would signal to building operators the need for enhancements in the HVAC operation to meet the target clean air delivery rate. In another example, in an implementation where the target ACH as per ASHRAE standards is 6, if the HVAC system's actual measured ACH is 4, the infection risk score would be determined by the formula (4 ACH/6 ACH)*100, resulting in a score of approximately 66.67. This score would indicate that the building's HVAC system is operating at two-thirds the optimal level for infection control, as per the ASHRAE standard. Thus, the determined score can then be used to prompt adjustments to the HVAC operations.
In some embodiments, a method, executed by one or more processing circuits, can include receiving an activation signal corresponding to an infection control mode (ICM). The method can further include initiating the ICM including activating one or more interventions, wherein the one or more interventions include operating HVAC equipment of the building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards. The method can further include determining an actual environmental condition of the building maintained by the HVAC system. At block 830 or in method 900, the method can further include determining an infection risk score based on a performance of the HVAC equipment of the building based on the one or more infection control standards. The infection risk score corresponds to an analysis of the actual environmental condition of the building and a target environmental condition based on the one or more infection control standards.
At block 840 or in method 900, the method can further include providing the infection risk score. That is, providing can include generating a visual representation of the score on a dashboard accessible to building managers and health officers. For example, providing can include sending automated alerts if the score falls below a predefined threshold, indicating a need for immediate corrective action. In another example, providing can include generating periodic compliance reports for regulatory review. In some embodiments, providing can involve integrating the score into a building's existing management system to facilitate real-time monitoring and responsive control. That is, the infection risk score can be continuously updated and displayed with other building metrics. For example, facility managers can access a view of the building's health status, enabling informed decision-making.
Referring now to
In broad overview of method 900, at block 910, the controller can receive an environmental dataset including indoor air quality (IAQ) data and operational parameters of HVAC equipment. At block 920, the controller can generate a clean air delivery metric for a target area of the building to satisfy an infection control standard. At block 930, the controller can initiate a mode to assess compliance with the control standard. Additional, fewer, or different operations may be performed depending on the particular arrangement. In some embodiments, some, or all operations of method 800 may be performed by one or more processors executing on one or more computing devices, systems, or servers. In various embodiments, each operation may be re-ordered, added, removed, or repeated.
Referring to method 900 in more detail, at block 910 the controller can receive an environmental dataset including indoor air quality (IAQ) data and one or more operational parameters or sensor readings of HVAC equipment of the building. The IAQ data can include, but is not limited to, temperature data, humidity data, carbon dioxide data, particulate matter (PM) data, volatile organic compounds (VOCs) data, radon data, carbon monoxide data, biological allergen data, information specific airborne pathogens or pollutants detected, historical IAQ trends, and external environmental factors such as outdoor air quality and weather conditions that can influence indoor air. Furthermore, the operational parameters of the HVAC equipment can include a history of settings and adjustments, maintenance records, energy usage data, and real-time data on current operational status. Sensor readings can include data gathered from various sensors installed throughout the building or within the HVAC system, capturing information on aspects such as temperature, humidity, airflow rates, particulate levels, or presence of specific airborne contaminants. These operational parameters and sensor readings collectively provide an overview of the building's existing environment, which the controller can utilize to optimize its decision-making process in managing the HVAC system for effective infection control.
In some embodiments, the controller can interface with other systems in the building to determine environmental factors and to optimize environmental parameters for disease prevention and control. For example, the controller can optimize conditions for infection control. These algorithms may identify correlations between various environmental factors and disease transmission risk, anticipate potential changes in indoor air quality that can elevate this risk, and adjust HVAC settings accordingly. For example, the controller can communicate with the building's security system to obtain real-time occupancy data, enabling dynamic adjustment of HVAC operation based on the number of individuals present. Furthermore, the controller can interface with lighting systems to gauge potential heat generation, which can affect indoor temperature, air circulation, and, consequently, pathogen dispersal.
In some embodiments, based on known occupancy throughout the building, the controller can direct (e.g., notify via a mobile phone notification, alert over an intercom or through a building alert system) people in high occupancy areas to move to or towards a low occupancy area (e.g., spread people out evenly across the building). For example, if an employee is working on a computer in zone A but the area has a high occupancy, the controller can provide a notification on the computer that there desktop is being transferred to a computer in zone B. In this example, the employee would be forced by the controller to move to a different area of the building where there is lower occupancy. In another example, if an employee is scheduled to conduct a meeting in building C but the particular building is over occupied, the employee may be provided a notification by the controller offering a different meeting room in building D which is currently under occupied (e.g., allowing the employee to accept the new meeting room).
In some embodiments, the controller can employ algorithms designed to optimize conditions for infection control. These algorithms may identify correlations between various environmental factors and disease transmission risk, anticipate potential changes in indoor air quality that can elevate this risk, and adjust HVAC settings accordingly. For example, if the data suggests an increased risk of airborne transmission, the controller can adjust the HVAC system to increase filtration or air exchange rates when the building enters ICM mode. Moreover, the controller can leverage machine learning techniques to enhance ICM performance over time. By analyzing patterns in past data and the effectiveness of previous HVAC adjustments under ICM, the controller can update its predictive models and proactively optimize HVAC settings to satisfy one or more infection control standards in the future.
In some embodiments, the controller can calculate a target clean air delivery rate for the target area based on occupancy data and the one or more infection control standards. In some embodiments, the controller can also take into account real-time changes in the environment or the building usage while calculating the target clean air delivery rate. For example, the controller can dynamically adjust the target rate in response to sudden increases in room occupancy or changes in outdoor air quality that can impact indoor air quality.
In some embodiments, the controller can validate a current state of the building including current infection control measures and generate and provide adjustments for compliance with the one or more infection control standards. In some embodiments, the controller can compare the current state of the building with stored benchmarks or desired states to assess the effectiveness of current infection control measures. Based on this comparison, the controller can then suggest specific adjustments, which can include changes to HVAC system operation, recommended maintenance, or structural changes (e.g., installation of additional ventilation or filtration equipment to facilitate compliance with the infection control standards).
At block 920, the controller can generate a clean air delivery metric for a target area of the building to satisfy one or more infection control standards based on one or more parameters including at least one of a room occupancy, a room volume, or a performance specification of the HVAC equipment. In addition to HVAC capacity and other contributing factors, the clean air delivery metric (i.e., the ICM metric), can integrate the impacts of multiple intervention methods deployed in the building. For example, if the building employs auxiliary disinfection units within specific zones, the controller can account for the supplemental air purification capabilities they provide, increasing the overall clean air delivery rate. Similarly, the control can quantify the impact of additional ventilation actions, such as the opening of windows to increase natural air circulation, or the incorporation of ultraviolet (UV) light systems in specific areas such as air ducts, that contribute to increasing the infection control effectiveness.
For example, an in-zone disinfection unit that offers an additional 500 CFM of purified air can effectively increase the total clean air delivery rate considered in the ICM metric calculation, resulting in a more favorable metric. A UV light system in an air duct reducing the pathogen concentration by a certain percentage can proportionally reduce the assumed infection risk in the respective area, consequently improving the overall ICM metric. Additionally, the control can incorporate various other data channels into the clear air delivery metric generation such as, but not limited to, calculations taking into account regional airflow patterns, variations in HVAC system efficiency, filter quality, the influence of room layout on aerosol distribution, the effects of differing human behavior patterns on disease transmission risk, and the role of building materials in disease propagation.
In some embodiments, the controller uses this calculated clean air delivery metric (i.e., ICM metric) in conjunction with the actual occupancy and relevant standard requirements, such as the recommended 40 CFM of clean air delivery per person under ICM conditions, to assess whether the building is maintaining compliance with established infection control standards. If discrepancies are identified, the controller can generate alerts or recommendations to relevant personnel. This can include advice to reduce occupancy levels in specific areas to maintain the required air change rate or suggestions to adjust HVAC settings such as increasing airflow or modifying temperature parameters. Additionally, the controller can recommend supplemental measures to further improve indoor air quality, such as the activation of UV light systems or other disinfection methods, or enhancements to the air filtration system.
In some embodiments, the controller can, in response to determining the clean air delivery metric is below a threshold, generate a notification including one or more recommendations to increase the clean air delivery metric. In some embodiments, the controller, utilizing the clean air delivery metric as an indicator of the infection control effectiveness, can detect when this metric falls below a certain threshold indicative of a potential standard violation. Upon such detection, the controller can generate and disseminate a notification containing recommendations on how to enhance the clean air delivery rate and consequently the infection control effectiveness. For example, these recommendations can include adjustments to the HVAC system, introduction of supplemental air purification units, modifications in room occupancy, or changes in behavioral patterns. In some embodiments, the controller can generate and provide a recommendation for a maximum occupancy capacity of the target area based on one or more infection control standards corresponding to an infection control mode (ICM) of the building. This recommendation is based on one or more infection control standards associated with the active ICM of the building, and the goal to maintain a clean air delivery rate that meets these standards. In some embodiments, the controller can, in response to the room occupancy exceeding the maximum occupancy capacity, provide one or more user devices an indication corresponding to the maximum occupancy being exceeded. In some embodiments, the controller can initiate a building inspection mode (BIM) to operate the HVAC equipment of the building to assess readiness of the HVAC system to transition into ICM. This mode serves as a proactive assessment of the HVAC system's readiness to transition into the ICM, and can include an examination of the HVAC system's ability to deliver the required air exchange rates, operate under modified settings, or integrate with other infection control measures.
At block 930, the controller can initiate a mode to assess compliance with the one or more infection control standards based on the clean air delivery metric. In some embodiments, the controller can initiate the protocols to transition the building's operational mode into compliance assessment. This transition can include adjusting various settings on the HVAC equipment, updating the algorithms used for environmental data analysis, and engaging with other interconnected systems within the building. To activate these assessments, the controller can adjust the HVAC equipment's settings, such as fan speeds, damper positions, and temperature setpoints, to evaluate the system's air purification capability and determine if it meets the enhanced air change rates required for infection control. In some embodiments, the controller can interface with supplementary infection control devices, such as UV disinfection systems, to verify the effectiveness of the overall infection control strategy. The controller can also interface with security systems to monitor and regulate occupancy levels, verifying that the clean air delivery rates per occupant are within the thresholds specified by the infection control standards. Throughout the execution of the compliance assessment mode, the controller can continuously monitors the indoor environment and makes adjustments to maintain compliance with the infection control standards. In some embodiments, initiating the mode can include initiating a building inspection mode (BIM) to operate the HVAC equipment of the building to assess readiness of the HVAC system to transition into ICM.
In some embodiments, the controller can determine an environmental condition of the building and a target environmental condition based on an analysis of the clean air delivery metric against the one or more infection control standards. That is, the analysis of the clean air delivery metrics can include comparing real-time data with predefined standards and adjusting HVAC operations accordingly. For example, the controller can increase ventilation rates if particulate matter levels exceed safe thresholds. The environmental condition can be measured in terms of IAQ factors such as temperature, humidity, and contaminant levels. For example, an environmental condition can be a high concentration of VOCs in a specific area. The target environmental condition can be a predefined safe level for all IAQ factors. For example, the target condition can be maintaining CO2 levels below 800 ppm in occupied rooms.
In some embodiments, the controller can generate and provide a graphical representation displaying compliance levels of at least the target area of the building. The graphical representation can include an indication of the clean air delivery metric and an indication whether the target area meets the one or more infection control standards. That is, generating the graphic representation can include visualizing data trends over time to show IAQ improvements or declines. For example, a line graph can be generated particulate levels decreasing after an HVAC adjustment. The compliance levels can be represented as color-coded status indicators. For example, color-coded status indicators can be green for compliant, red for non-compliant. Providing the graphical representation can include displaying it on a building management system interface accessible to facility managers. For example, the graphical representation can be a dashboard view summarizing compliance across different zones. The indication of the clean air delivery metric can be shown as a numeric value or percentage. For example, clean air delivery metric can be 450 CFM of clean air delivery. The indication whether the target area meets the one or more infection control standards can be shown as a pass/fail marker or a compliance percentage. For example, the indication can indicate 85% compliance with current IAQ standards.
In some embodiments, a method, executed by one or more processing circuits, can also include receiving an environmental dataset including indoor air quality (IAQ) data and one or more operational parameters or sensor readings of HVAC equipment of the building. For example, the environmental dataset can be data collected from temperature and humidity sensors, CO2 monitors, and VOC detectors. The method can further include generating a clean air delivery metric for a target area of the building based on one or more parameters including at least one of a room occupancy, a room volume, or a performance specification of the HVAC equipment. For example, generating a clean air delivery metric can include calculating the required air exchange rate based on the number of occupants and room size.
In some embodiments, one or more computer-readable storage media having instructions stored thereon that, when executed by one or more processors, can cause the one or more processors to perform operations including receiving an activation signal corresponding to an infection control mode (ICM). The one or more computer-readable storage media having additional instructions stored thereon that, when executed by the one or more processors, can cause the one or more processors to perform additional operations including initiating the ICM including activating one or more interventions, wherein the one or more interventions include operating HVAC equipment of the building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards. The one or more computer-readable storage media having additional instructions stored thereon that, when executed by the one or more processors, can cause the one or more processors to perform additional operations including determining an actual environmental condition of the building maintained by the HVAC system. The one or more computer-readable storage media having additional instructions stored thereon that, when executed by the one or more processors, can cause the one or more processors to perform additional operations including determining an infection risk score based on a performance of the HVAC equipment of the building based on the one or more infection control standards, wherein the infection risk score corresponds to an analysis of the actual environmental condition of the building and a target environmental condition based on the one or more infection control standards. The one or more computer-readable storage media having additional instructions stored thereon that, when executed by the one or more processors, can cause the one or more processors to perform additional operations including providing the infection risk score.
In some embodiments, one or more computer-readable storage media having instructions stored thereon that, when executed by one or more processors, can cause the one or more processors to perform operations including receiving an environmental dataset including indoor air quality (IAQ) data and one or more operational parameters or sensor readings of HVAC equipment of the building. The one or more computer-readable storage media having additional instructions stored thereon that, when executed by the one or more processors, can cause the one or more processors to perform additional operations including generating a clean air delivery metric for a target area of the building based on one or more parameters including at least one of a room occupancy, a room volume, or a performance specification of the HVAC equipment.
Configuration of Exemplary EmbodimentsAlthough the FIGS. show a specific order of method steps, the order of the steps may differ from what is depicted. Also, two or more steps can be performed concurrently or with partial concurrence. Such variation will depend on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations can be accomplished with standard programming techniques with rule based logic and other logic to accomplish the various connection steps, calculation steps, processing steps, comparison steps, and decision steps.
The construction and arrangement of the systems and methods as shown in the various exemplary embodiments are illustrative only. Although only a few embodiments have been described in detail in this disclosure, many modifications are possible (e.g., variations in sizes, dimensions, structures, shapes and proportions of the various elements, values of parameters, mounting arrangements, use of materials, colors, orientations, etc.). For example, the position of elements can be reversed or otherwise varied and the nature or number of discrete elements or positions can be altered or varied. Accordingly, all such modifications are intended to be included within the scope of the present disclosure. The order or sequence of any process or method steps can be varied or re-sequenced according to alternative embodiments. Other substitutions, modifications, changes, and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments without departing from the scope of the present disclosure.
As used herein, the term “circuit” may include hardware structured to execute the functions described herein. In some embodiments, each respective “circuit” may include machine-readable media for configuring the hardware to execute the functions described herein. The circuit may be embodied as one or more circuitry components including, but not limited to, processing circuitry, network interfaces, peripheral devices, input devices, output devices, sensors, etc. In some embodiments, a circuit may take the form of one or more analog circuits, electronic circuits (e.g., integrated circuits (IC), discrete circuits, system on a chip (SOCs) circuits, etc.), telecommunication circuits, hybrid circuits, and any other type of “circuit.” In this regard, the “circuit” may include any type of component for accomplishing or facilitating achievement of the operations described herein. For example, a circuit as described herein may include one or more transistors, logic gates (e.g., NAND, AND, NOR, OR, XOR, NOT, XNOR, etc.), resistors, multiplexers, registers, capacitors, inductors, diodes, wiring, and so on).
The “circuit” may also include one or more processors communicably coupled to one or more memory or memory devices. In this regard, the one or more processors may execute instructions stored in the memory or may execute instructions otherwise accessible to the one or more processors. In some embodiments, the one or more processors may be embodied in various ways. The one or more processors may be constructed in a manner sufficient to perform at least the operations described herein. In some embodiments, the one or more processors may be shared by multiple circuits (e.g., circuit A and circuit B may include or otherwise share the same processor which, in some example embodiments, may execute instructions stored, or otherwise accessed, via different areas of memory). Alternatively, or additionally, the one or more processors may be structured to perform or otherwise execute certain operations independent of one or more co-processors. In other example embodiments, two or more processors may be coupled via a bus to enable independent, parallel, pipelined, or multi-threaded instruction execution. Each processor may be implemented as one or more general-purpose processors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), or other suitable electronic data processing components structured to execute instructions provided by memory. The one or more processors may take the form of a single core processor, multi-core processor (e.g., a dual core processor, triple core processor, quad core processor, etc.), microprocessor, etc. In some embodiments, the one or more processors may be external to the apparatus, for example the one or more processors may be a remote processor (e.g., a cloud based processor). Alternatively, or additionally, the one or more processors may be internal and/or local to the apparatus. In this regard, a given circuit or components thereof may be disposed locally (e.g., as part of a local server, a local computing system, etc.) or remotely (e.g., as part of a remote server such as a cloud based server). To that end, a “circuit” as described herein may include components that are distributed across one or more locations.
The present disclosure contemplates methods, systems, and program products on any machine-readable media for accomplishing various operations. The embodiments of the present disclosure can be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwired system. Embodiments within the scope of the present disclosure include program products including machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a general purpose or special purpose computer or other machine with a processor. By way of example, such machine-readable media can include RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions.
Claims
1. An HVAC system of a building comprising:
- a controller comprising one or more processors configured to: receive an activation signal corresponding to an infection control mode (ICM); initiate the ICM comprising activating one or more interventions, wherein the one or more interventions comprise operating HVAC equipment of the building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards; determine an infection risk score based on a performance of the HVAC equipment of the building based on the one or more infection control standards, wherein the infection risk score corresponds to an analysis of an environmental condition of the building and a target environmental condition based on the one or more infection control standards; and provide the infection risk score.
2. The HVAC system of claim 1, wherein the environmental condition correspond to one or more measured values of air quality parameters within the building, and wherein the one or more measured values is at least one of an air change rate per hour (ACH), a level of specific airborne contaminant, or a particulate matter (PM) concentration.
3. The HVAC system of claim 2, wherein the target environmental condition corresponds to a predetermined value of the air quality parameters defined by the one or more infection control standards, wherein the one or more infection control standards are at least one of a ASHRAE standard or a government health standard.
4. The HVAC system of claim 1, wherein the controller is further configured to:
- determine a minimum energy solution that is compliant with the one or more infection control standards, wherein determining the minimum energy solution comprises: calculating one or more HVAC system parameters to balance between HVAC capacity and energy usage that satisfies the one or more infection control standards; modifying the one or more HVAC system parameters based on conditions of the building in response to data collected from temporary sensors or permanent sensors installed within the building; and monitoring and updating the minimum energy solution as the conditions of the building change.
5. The HVAC system of claim 1, wherein the controller is further configured to determine at least one:
- a minimum operating cost that is compliant with the one or more infection control standards;
- a minimum energy and maintenance cost that is compliant with the one or more infection control standards; or
- a minimum sustainability cost that is compliant with the one or more infection control standards.
6. The HVAC system of claim 1, wherein the controller is further configured to:
- generate a graphical representation providing compliance levels of a plurality of spaces within the building, wherein the graphical representation comprises an indication of the infection risk score and an indication whether the plurality of spaces meeting the one or more infection control standards; and
- operate the HVAC equipment based on changes in occupancy levels, wherein operating comprises adjusting HVAC system parameters.
7. The HVAC system of claim 1, wherein the controller is further configured to:
- in response to the environmental condition after a period of time being below or outside the one or more infection control standards, initiate additional infection control measures comprising at least one of activating in-room ultraviolet (UV) light units, increasing airflow of the HVAC system, adjusting an operation of an in-room air cleaning device, adjusting occupancy levels of the building, or adjusting filtration capabilities of the HVAC equipment.
8. The HVAC system of claim 1, wherein the controller is further configured to:
- determine one or more spaces within the building as validated environments;
- in response to determining the one or more spaces, monitor ICM data of the one or more spaces to assess a current state of the building; and
- provide the current state of the building.
9. An HVAC system of a building comprising:
- a controller comprising one or more processors configured to: receive an environmental dataset comprising indoor air quality (IAQ) data and one or more operational parameters or sensor readings of HVAC equipment of the building; generate a clean air delivery metric for a target area of the building based on one or more parameters to satisfy one or more infection control standards comprising at least one of a room occupancy, a room volume, or a performance specification of the HVAC equipment; and initiate a mode to assess compliance with the one or more infection control standards based on the clean air delivery metric.
10. The HVAC system of claim 9, wherein the controller is further configured to:
- in response to determining the clean air delivery metric is below a threshold, generate a notification comprising one or more recommendations to increase the clean air delivery metric.
11. The HVAC system of claim 10, wherein the controller is further configured to:
- generate and provide a recommendation for a maximum occupancy capacity of the target area based on the clean air delivery metric corresponding to an infection control mode (ICM) of the building; and
- in response to the room occupancy exceeding the maximum occupancy capacity, provide one or more user devices an indication corresponding to the maximum occupancy capacity being exceeded.
12. The HVAC system of claim 9, wherein the controller is further configured to:
- calculate a target clean air delivery rate for the target area based on occupancy data and the one or more infection control standards.
13. The HVAC system of claim 9, wherein the controller is further configured to:
- validate a current state of the building comprising current infection control measures; and
- generate and provide adjustments for compliance with the one or more infection control standards.
14. The HVAC system of claim 9, wherein initiating the mode comprises:
- initiating a building inspection mode (BIM) to operate the HVAC equipment of the building to assess readiness of the HVAC system to transition into ICM.
15. The HVAC system of claim 9, wherein the controller is further configured to:
- determine an environmental condition of the building and a target environmental condition based on an analysis of the clean air delivery metric against the one or more infection control standards; and
- generate and provide a graphical representation displaying compliance levels of at least the target area of the building, wherein the graphical representation comprises an indication of the clean air delivery metric and an indication whether the target area meets the one or more infection control standards.
16. A method, comprising:
- receiving, by one or more processing circuits, an activation signal corresponding to an infection control mode (ICM);
- initiating, by the one or more processing circuits, the ICM comprising activating one or more interventions, wherein the one or more interventions comprise operating HVAC equipment of a building to meet ICM requirements maintaining an environment corresponding to one or more infection control standards;
- determining, by the one or more processing circuits, an infection risk score based on a performance of the HVAC equipment of the building based on the one or more infection control standards, wherein the infection risk score corresponds to an analysis of an environmental condition of the building and a target environmental condition based on the one or more infection control standards; and
- providing, by the one or more processing circuits, the infection risk score.
17. The method of claim 16, wherein the environmental condition correspond to one or more measured values of air quality parameters within the building, and wherein the one or more measured values is at least one of an air change rate per hour (ACH), a level of specific airborne contaminant, or a particulate matter (PM) concentration.
18. The method of claim 17, wherein the target environmental condition corresponds to a predetermined value of the air quality parameters defined by the one or more infection control standards, wherein the one or more infection control standards are at least one of a ASHRAE standard or a government health standard.
19. The method of claim 16, further comprising:
- determining, by the one or more processing circuits, a minimum energy solution that is compliant with the one or more infection control standards, wherein determining the minimum energy solution comprises: calculating one or more HVAC system parameters to balance between HVAC capacity and energy usage that satisfies the one or more infection control standards; modifying the one or more HVAC system parameters based on conditions of the building in response to data collected from temporary sensors or permanent sensors installed within the building; and monitoring and updating the minimum energy solution as the conditions of the building change.
20. The method of claim 16, further comprising:
- determining, by the one or more processing circuits, a minimum operating cost that is compliant with the one or more infection control standards;
- determining, by the one or more processing circuits, a minimum energy and maintenance cost that is compliant with the one or more infection control standards; and
- determining, by the one or more processing circuits, a minimum sustainability cost that is compliant with the one or more infection control standards.
Type: Application
Filed: Jun 21, 2024
Publication Date: Dec 26, 2024
Inventors: Jonathan D. Douglas (Mequon, WI), Bernard P. Clement (Mequon, WI), Brennan H. Fentzlaff (Oconomowoc, WI), Michael J. Risbeck (Madison, WI), Michael J. Wenzel (Grafton, WI), Matthew J. Asmus (Watertown, WI), Christopher R. Amundson (Grafton, WI), Shawn D. Schubert (Oak Creek, WI)
Application Number: 18/751,110
