BUILDING MANAGEMENT SYSTEM WITH CONTINUOUS AIR QUALITY MONITORING

Description

CROSS-REFERENCE TO RELATED APPLICATIONS AND CLAIM OF PRIORITY

This application claims priority to and the benefit of U.S. Provisional Application No. 63/433,840, filed Dec. 20, 2022, which is incorporated herein by reference in its entirety.

BACKGROUND

The present disclosure relates generally to building systems. The present disclosure relates more particularly to the collection and monitoring of particles from the air of a building. In building environments, the particles in the air can be monitored and the particles can include pathogens.

SUMMARY

Some implementations relate to an HVAC system of a building including a controller including memory and at least one processor configured to receive, from a plurality of sensors, infectious agent data, the plurality of sensors disposed throughout the building, at least one of the plurality of sensors including an apparatus configured to collect samples, wherein the plurality of sensors configured to continuously test the samples over a sampling period for infectious agents and provide the infectious agent data to the controller. The at least one processor is further configured to, in response to indicating of an infectious agent based on the infectious agent data, determine at least one area of the building exposed to the infectious agent. The at least one processor is further configured to selectively control an amount of equivalent clean air delivered to the at least one area based on the indication of the infectious agent.

In some embodiments, the indication of the infectious agent is at least one of an indication of a presence of the infectious agent, an indication of a change in an amount of the infectious agent, or an indication of exceeding a threshold corresponding with the amount of the infectious agent.

In some embodiments, the at least one processor is further configured to monitor the change in the amount of the infectious agent over a period of time, and wherein selectively controlling the amount of equivalent clean air is based on an increase in the amount of the infectious agent over the period of time in the at least one area of the building.

In some embodiments, selectively controlling the amount of equivalent clean air is in response to an increase in the amount of the infectious agent above a normal background level, and wherein the normal background level is specific to the at least one area of the building.

In some embodiments, the at least one of the plurality of sensors includes a collection apparatus, and wherein the samples are liquid samples collected via the collection apparatus.

In some embodiments, selectively controlling the amount of equivalent clean air includes at least one of increasing an airflow rate or increasing outside air ventilation, air handling unit (AHU) airflow rate, in zone filtration, or in zone disinfection, and wherein the at least one processor are further configured to selectively activate at least one of a negative pressure space relative to rest of the building or a plurality of lighting apparatuses in at least one of the air handling unit or the at least one area.

In some embodiments, the at least one processor is further configured to selectively control, in real-time or near real-time, access to the at least one area of the building, wherein selectively controlling access further includes locking at least one door controlling access to the at least one area.

In some embodiments, the at least one processor is further configured to communicate a presence of the infectious agent to a plurality of individuals selected based on cross-referencing location data of the plurality of sensors and location data of user devices of the plurality of individuals, wherein the communication of the presence further includes a notification to avoid the at least one area of the building.

In some embodiments, the at least one processor is further configured to in response to indicating the infectious agent based on the infectious agent data, determine a plurality of guidelines or procedures corresponding with the at least one area of the building, wherein the plurality of guidelines or procedures are different from a first area of the building and a second area of the building.

In some embodiments, the at least one processor is further configured to generate a graphical user interface (GUI) including graphical information and steps for the determined plurality of guidelines or procedures, wherein the GUI includes at least one interactive item corresponding with implementing the determined plurality of guidelines or procedures and provide the GUI to at least one computing device within the at least one area of the building or associated with the at least one area, wherein the at least one computing device is associated with the at least one area based on at least one of scheduling information, a designation of association, or a previous presence of the at least one computing device within the at least one area.

In some embodiments, the at least one processor is further configured to monitor an amount of the infectious agent in the building, determine controlling the amount of equivalent clear air and the plurality of guidelines or procedures decreased the amount of the infectious agent in the building, and modify the selective control of the amount of equivalent clear air of the air flowing through the air handling unit of the HVAC system.

In some embodiments, the at least one processor is further configured to determine a prevalence of the infectious agent in the building based on cross-referencing external infectious agent data of an external data source with the infectious agent data.

In some embodiments, the at least one processor is further configured to determine a baseline prevalence of the infectious agent in a public area of the building, determine a prevalence of the infectious agent in the at least one area of the building, and modify the selective control of the amount of equivalent clear air of the air flowing through the air handling unit of the HVAC system based on the prevalence in the at least one area being above the baseline prevalence in the public area.

Some implementations relate to a method, including receiving, by at least one processing circuit from a plurality of sensors disposed throughout a building, infectious agent data, at least one of the plurality of sensors including an apparatus configured to collect samples, wherein the plurality of sensors configured to continuously test the samples over a sampling period for infectious agents and provide the infectious agent data to the at least one processing circuit. The method further includes, in response to indicating of an infectious agent based on the infectious agent data, determining, by the at least one processing circuit, at least one area of the building exposed to the infectious agent. The method further includes selectively controlling, by the at least one processing circuit, an amount of equivalent clean air delivered to the at least one area based on the indication of the infectious agent.

In some embodiments, the indication of the infectious agent is at least one of an indication of a presence of the infectious agent, an indication of a change in an amount of the infectious agent, or an indication of exceeding a threshold corresponding with the amount of the infectious agent.

In some embodiments, the method further includes monitoring, by the at least one processing circuit, the change in the amount of the infectious agent over a period of time, and wherein selectively controlling the amount of equivalent clean air is based on an increase in the amount of the infectious agent over the period of time in the at least one area of the building.

In some embodiments, selectively controlling the amount of equivalent clean air is in response to an increase in the amount of the infectious agent above a normal background level, and wherein the normal background level is specific to the at least one area of the building.

In some embodiments, the method further includes in response to indicating the infectious agent based on the infectious agent data, determining, by the at least one processing circuit, a plurality of guidelines or procedures corresponding with the at least one area of the building, wherein the plurality of guidelines or procedures are different from a first area of the building and a second area of the building, generating, by the at least one processing circuit, a graphical user interface (GUI) including graphical information and steps for the determined plurality of guidelines or procedures, wherein the GUI includes at least one interactive item corresponding with implementing the determined plurality of guidelines or procedures, providing, by the at least one processing circuit, the GUI to at least one computing device within the at least one area of the building or associated with the at least one area, wherein the at least one computing device is associated with the at least one area based on at least one of scheduling information, a designation of association, or a previous presence of the at least one computing device within the at least one area, monitoring, by the at least one processing circuit, an amount of the infectious agent in the building, determining, by the at least one processing circuit, controlling the amount of equivalent clear air and the plurality of guidelines or procedures decreased the amount of the infectious agent in the building, and modifying, by the at least one processing circuit, the selective control of the amount of equivalent clear air of the air flowing through the air handling unit of the HVAC system.

In some embodiments, the method further includes determining, by the at least one processing circuit, a baseline prevalence of the infectious agent in a public area of the building, determining, by the at least one processing circuit, a prevalence of the infectious agent in the at least one area of the building, and modifying, by the at least one processing circuit, the selective control of the amount of equivalent clear air of the air flowing through the air handling unit of the HVAC system based on the prevalence in the at least one area being above the baseline prevalence in the public area.

Some implementations relate to one or more non-transitory computer readable mediums storing instructions thereon that, when executed by one or more processors, cause the one or more processors to perform the operations including receive, from a plurality of sensors, infectious agent data, the plurality of sensors disposed throughout the building, at least one of the plurality of sensors including an apparatus configured to collect samples, wherein the plurality of sensors configured to continuously test the samples over a sampling period for infectious agents and provide the infectious agent data to the controller. The one or more non-transitory computer readable mediums storing additional instructions thereon that, when executed by one or more processors, further cause the one or more processors to perform the operations including, in response to indicating of an infectious agent based on the infectious agent data, determine at least one area of the building exposed to the infectious agent. The one or more non-transitory computer readable mediums storing additional instructions thereon that, when executed by one or more processors, further cause the one or more processors to perform the operations including selectively control an amount of equivalent clean air delivered to the at least one area based on the indication of the infectious agent.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a drawing of a building equipped with a HVAC system, according to some embodiments.

FIG. 2 is a block diagram of an airside system that can be implemented in the building of FIG. 1, according to some embodiments.

FIG. 3 is a flowchart for a method of continuous air quality monitoring, according to some embodiments.

FIG. 4 is a block diagram of sensors in a networked environment, according to some embodiments.

FIG. 5 is an illustrative example a building with sensors and controls, according to some embodiments.

FIGS. 6-7 are graphical interfaces including interface objects, according to some embodiments.

DETAILED DESCRIPTION

Overview

Referring generally to the FIGS., various example systems and methods are shown and described relating to utilizing sensors and controllers to extract, collect, and test samples for air quality monitoring. According to various implementations, a building management system may include one or more components for extracting, collecting, and testing samples from air. The samples can be in liquid, solid, or gas form based using various techniques on the air in the sensor or received from returned air and/or outdoor air. For example, the water in the air can be condensed into a liquid. In some embodiments, a collection apparatus can collect the samples including infectious agent particles from the air within the building.

Referring now to FIG. 1, a perspective view of a building 10 is shown. Building 10 can be served by a building management system (BMS). A BMS is, in general, a system of devices configured to control, monitor, and manage equipment in or around a building or building area. A BMS can include, for example, a HVAC system, a security system, a lighting system, a fire alerting system, any other system that is capable of managing building functions or devices, or any combination thereof. An example of a BMS which can be used to monitor and control building 10 is described in U.S. patent application Ser. No. 14/717,593 filed May 20, 2015, the entire disclosure of which is incorporated by reference herein.

The BMS that serves building 10 may include 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. In some embodiments, waterside system 120 can be replaced with or supplemented by a central plant or central energy facility (described in greater detail with reference to FIG. 2). An example of an airside system which can be used in HVAC system 100 is described in greater detail with reference to FIG. 2.

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 FIG. 1) or at an offsite location such as a central plant (e.g., a chiller plant, a steam plant, a heat plant, etc.). The working fluid can be heated in boiler 104 or cooled in chiller 102, depending on whether heating or cooling is required in building 10. Boiler 104 may add heat to the circulated fluid, for example, by burning a combustible material (e.g., natural gas) or using an electric heating element. Chiller 102 may place the circulated fluid in a heat exchange relationship with another fluid (e.g., a refrigerant) in a heat exchanger (e.g., an evaporator) to absorb heat from the circulated fluid. The working fluid from chiller 102 and/or boiler 104 can be transported to AHU 106 via piping 108.

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.

Airside System

Referring now to FIG. 2, a block diagram of an airside system 200 is shown, according to some embodiments. In various embodiments, airside system 200 may supplement or replace airside system 130 in HVAC system 100 or can be implemented separate from HVAC system 100. When implemented in HVAC system 100, airside system 200 can include a subset of the HVAC devices in HVAC system 100 (e.g., AHU 106, VAV units 116, ducts 112-114, fans, dampers, etc.) and can be located in or around building 10. Airside system 200 may operate to heat, cool, humidify, dehumidify, filter, and/or disinfect an airflow provided to building 10 in some embodiments.

Airside system 200 is shown to include an economizer-type air handling unit (AHU) 202. Economizer-type AHUs vary the amount of outside air and return air used by the air handling unit for heating or cooling. For example, AHU 202 may receive return air 204 from building zone 206 via return air duct 208 and may deliver supply air 210 to building zone 206 via supply air duct 212. In some embodiments, AHU 202 is a rooftop unit located on the roof of building 10 (e.g., AHU 106 as shown in FIG. 1) or otherwise positioned to receive both return air 204 and outside air 214. AHU 202 can be configured to operate exhaust air damper 216, mixing damper 218, and outside air damper 220 to control an amount of outside air 214 and return air 204 that combine to form supply air 210. Any return air 204 that does not pass through mixing damper 218 can be exhausted from AHU 202 through exhaust damper 216 as exhaust air 222.

Each of dampers 216-220 can be operated by an actuator. For example, exhaust air damper 216 can be operated by actuator 224, mixing damper 218 can be operated by actuator 226, and outside air damper 220 can be operated by actuator 228. Actuators 224-228 may communicate with an AHU controller 230 via a communications link 232. Actuators 224-228 may receive control signals from AHU controller 230 and may provide feedback signals to AHU controller 230. 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 224-228), 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 224-228. AHU controller 230 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 224-228.

Still referring to FIG. 2, AHU 202 is shown to include a cooling coil 234, a heating coil 236, and a fan 238 positioned within supply air duct 212. Fan 238 can be configured to force supply air 210 through cooling coil 234 and/or heating coil 236 and provide supply air 210 to building zone 206. AHU controller 230 may communicate with fan 238 via communications link 240 to control a flow rate of supply air 210. In some embodiments, AHU controller 230 controls an amount of heating or cooling applied to supply air 210 by modulating a speed of fan 238. In some embodiments, AHU 202 includes one or more air filters and/or one or more ultraviolet (UV) lights. AHU controller 230 can be configured to control the UV lights and route the airflow through the air filters to disinfect the airflow as described in greater detail below.

Cooling coil 234 may receive a chilled fluid from central plant 200 via piping 242 and may return the chilled fluid to central plant 200 via piping 244. Valve 246 can be positioned along piping 242 or piping 244 to control a flow rate of the chilled fluid through cooling coil 234. In some embodiments, cooling coil 234 includes multiple stages of cooling coils that can be independently activated and deactivated (e.g., by AHU controller 230, by BMS controller 266, etc.) to modulate an amount of cooling applied to supply air 210.

Heating coil 236 may receive a heated fluid from central plant 200 via piping 248 and may return the heated fluid to central plant 200 via piping 250. Valve 252 can be positioned along piping 248 or piping 250 to control a flow rate of the heated fluid through heating coil 236. In some embodiments, heating coil 236 includes multiple stages of heating coils that can be independently activated and deactivated (e.g., by AHU controller 230, by BMS controller 266, etc.) to modulate an amount of heating applied to supply air 210.

Each of valves 246 and 252 can be controlled by an actuator. For example, valve 246 can be controlled by actuator 254 and valve 252 can be controlled by actuator 256. Actuators 254-256 may communicate with AHU controller 230 via communications links 258-260. Actuators 254-256 may receive control signals from AHU controller 230 and may provide feedback signals to controller 230. In some embodiments, AHU controller 230 receives a measurement of the supply air temperature from a temperature sensor 262 positioned in supply air duct 212 (e.g., downstream of cooling coil 334 and/or heating coil 236). AHU controller 230 may also receive a measurement of the temperature of building zone 206 from a temperature sensor 264 located in building zone 206.

In some embodiments, AHU controller 230 operates valves 246 and 252 via actuators 254-256 to modulate an amount of heating or cooling provided to supply air 210 (e.g., to achieve a setpoint temperature for supply air 210 or to maintain the temperature of supply air 210 within a setpoint temperature range). The positions of valves 246 and 252 affect the amount of heating or cooling provided to supply air 210 by cooling coil 234 or heating coil 236 and may correlate with the amount of energy consumed to achieve a desired supply air temperature. AHU controller 230 may control the temperature of supply air 210 and/or building zone 206 by activating or deactivating coils 234-236, adjusting a speed of fan 238, or a combination of both.

Still referring to FIG. 2, airside system 200 is shown to include a building management system (BMS) controller 266 and a client device 268. BMS controller 266 can include one or more computer systems (e.g., servers, supervisory controllers, subsystem controllers, etc.) that serve as system level controllers, application or data servers, head nodes, or master controllers for airside system 200, central plant 200, HVAC system 100, and/or other controllable systems that serve building 10. BMS controller 266 may communicate with multiple downstream building systems or subsystems (e.g., HVAC system 100, a security system, a lighting system, central plant 200, etc.) via a communications link 270 according to like or disparate protocols (e.g., LON, BACnet, etc.). In various embodiments, AHU controller 230 and BMS controller 266 can be separate (as shown in FIG. 2) or integrated. In an integrated implementation, AHU controller 230 can be a software module configured for execution by a processor of BMS controller 266.

In some embodiments, AHU controller 230 receives information from BMS controller 266 (e.g., commands, setpoints, operating boundaries, etc.) and provides information to BMS controller 266 (e.g., temperature measurements, valve or actuator positions, operating statuses, diagnostics, etc.). For example, AHU controller 230 may provide BMS controller 266 with temperature measurements from temperature sensors 262-264, equipment on/off states, equipment operating capacities, and/or any other information that can be used by BMS controller 266 to monitor or control a variable state or condition within building zone 206.

Client device 268 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 268 can be a computer workstation, a client terminal, a remote or local interface, or any other type of user interface device. Client device 268 can be a stationary terminal or a mobile device. For example, client device 268 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 268 may communicate with BMS controller 266 and/or AHU controller 230 via communications link 272.

Continuous Air Quality Monitoring

Referring now to FIGS. 1-2 generally, in some embodiments, a plurality of sensors including a collection apparatus can be disposed and configured throughout a building. In some embodiments, one or more sensors can be placed throughout building zones 206. Each sensor can be configured to collect condensation, liquid, and/or test (e.g., gaseous, or solid) samples for infectious agents. In some embodiments, the samples can be tested continuously to allow for continuous readings of infectious agents that can be used by the HVAC system 100 and controllers described herein with real-time data regarding potential presence of infectious agents (or an indication of a change in an amount of the infectious agent, or an indication of exceeding a threshold corresponding with the amount of the infectious agent) and infectious agent loads within specific rooms, areas, or spaces within the building. While various embodiments discuss disposing the sensors throughout the building, it should be understood that the techniques described herein can be applied to sensors disposed within the airside system 200, outside the building, or HVAC system equipment described herein. All such modifications are contemplated within the scope of the present disclosure.

As used herein, an “amount of equivalent clear air or airflow (ECA) delivered” refers to the theoretical flow rate of pathogen-free air that, if distributed uniformly within the breathing zone, would have the same effect on infectious aerosol concentration as the sum of actual outdoor airflow, filtered airflow, and inactivation of infectious aerosols. In particular, ECA can quantify the effectiveness of various air treatment strategies combined, such as ventilation, filtration, and disinfection, in terms of their capacity to reduce the concentration of infectious aerosols to an equivalent level that would be achieved by a certain volume of completely clean, pathogen-free air. It should be understood that sources of equivalent clear air can be outside air ventilation, filtration (e.g., via the central AHU or in zone filters), disinfection devices (UVC), along with other air purification technologies. Accordingly, ECA serves as a composite measure for assessing overall air quality in terms of infectious agent reduction, combining various factors that contribute to cleaner indoor air. In one example, ECA can be a standard corresponding with specific guidelines such as ASHRAE Standard 241, which outlines requirement for control of infectious aerosols to reduce risk of disease transmission in the occupiable space in buildings, including requirements for both outdoor air system and air cleaning system design, installation, commissioning, operation, and maintenance.

Each individual sensor can include a collection apparatus that can include one or more pipe systems, fittings, sponge systems, wash systems, suction systems, drip pans, mechanical wipe systems, cone systems, etc. Overtime while the condensation and/or fluid in the air is collected the condensation flows down the surface into cones (crescent-shaped, or wedge-shaped collection systems). In each cone, the fluid nanoparticles can attach to electrodes, as slots in nanoparticles get attached. Accordingly, each sensor can include a collection apparatus configured to collect condensation into cones and each cone can attach nanoparticles of the condensation to electrodes to enable continuous and real-time monitoring of the environment in which a sensor is disposed at. In various embodiments, the sensor can perform quantitative sampling and testing such that the sensor can identify a presence of an infectious agent and identify the amount of the infectious agent (e.g., an indication of a change in an amount of the infectious agent or an indication of exceeding a threshold corresponding with the amount of the infectious agent). Additional details regarding the individual sensors are described below with reference FIG. 4.

Referring generally to infectious agents, the sensor sampling and testing can include performing a quantitative polymerase chain reaction (qPCR) test to detect and identify a virus (e.g., COVID-19, Influenza, Ebola, respiratory syncytial virus (RSV), etc.). Sensor sampling and testing can also detect a bacteria, etc., strep, legionella, and can identify mold or pollen. Sensor sampling and testing can include identifying bioterrorism agents (e.g., anthrax, Ricin, etc.). While various embodiments discuss sampling and testing, it should be understood that the techniques described herein can be applied to sensing and testing to biological or non-biological materials. All such modifications are contemplated within the scope of the present disclosure.

In various embodiments, each sensor can communicate with the BMS controller 266 (or AHU controller 230) via a wired or wireless connection. The sensors can send continuous and real-time indicating current infectious agent presences and infectious agent loads. In some embodiments, the sensors can package multiple readings into a single data package prior to sending the infectious agent data to the BMS controller 266. The BMS controller 266, using the infectious agent data, can generate a real-time map of infectious agent concentration in a building. For example, the map can be generated based on map data of the building (e.g., blueprint), the received continuous sensor data (e.g., infectious agent data), location information of the sensors (e.g., room or area the sensor monitors, floor, current time), and/or historical infectious agent data (e.g., previous infectious agent detections). The map can include indications of severity (or another risk metric) of the concentration throughout the building. For example, rooms (based on the blueprint) may be color-coded based on a level of infectious agent concentration (e.g., green when COVID19 part per million (ppm) is below 10 ppm, yellow when COVID19 ppm is between 10 ppm and 50 ppm, red when COVID19 ppm is above 50 ppm).

In various embodiment, the concentration of infectious agents can be inferred based on the level of carbon dioxide in the air (e.g., when CO2 is above 400 ppm and an infectious agent is detected (irrespective of the ppm) then indicate the space as yellow, when CO2 is above 1000 ppm and an infectious agent is detected (irrespective of the ppm) then indicate the space as red). Additionally, the map and risk metrics can be based on the type of area or room one or more sensors are in. For example, a sensor in a gym with higher CO2 concentrations may indicate the severity (or another risk metric) as less than a classroom even when the ppm for an infectious agent or CO2 are the same (e.g., 40 ppm of COVID, 700 ppm of CO2). In some embodiments, the severity of concentration may be by floor or area of the building. Additionally, in response to identifying a certain area with an infectious agent concentration, presence, or load (e.g., amount or amount compared to a threshold), the BMS controller 266 can resample the area to verify the sample and test.

In various embodiments, the map can be shown as a function of time. In some embodiments, the BMS controller 266 can calculate a dose of exposure of individuals moving through the building, for example, by using BLE badges or other access control badges to determine location. In another example, the BMS controller 266 can ping or access the mobile devices of individuals within the building to determine the location of the individual. Additionally, in response to determining a presence (or amount) of an infectious agent above a threshold, the BMS controller 266 can identify people of the particular areas or spaces determined to contain the infectious agent (i.e., an infectious area). Once an infectious area is determined a message may be sent to each individual within that area in the past predetermined time (e.g., in the past day, in the past 1 hour, in the past 15 minutes). Additionally, the BMS controller 266 can raise or decrease health warnings for buildings and/or particular areas or spaces within the building based on the sampling and testing by the sensor.

In various embodiment, the BMS controller 266 can execute demand controller ventilation based on live (or continuous) readings of the infectious agent rather than or in addition to CO2 readings. Thus, the HVAC equipment described herein can be controlled responsive to real-time readings of sensors determining infectious agent presence and loads within the building. For example, in response to a real-time reading of the presence of the infectious agent in zone 2 of the building, the BMS controller can execute a command to increase (or control) the ventilation of zone 2.

In some embodiments, in response to detecting a presence of an infectious agent in the building, the BMS controller 266 can communicate (e.g., via a message, load speaker, via an application of a mobile device accessed via an API, etc.) to the individuals in the building a safe path to exit the building or go to safe area (collectively a “desired destination”). For example, the safe path may be an exit path without a detected presence of the infectious agent. Additionally, the BMS controller 266 may also prohibit individuals taking certain paths by locking or prohibiting access using the building security system (e.g., disable and/or deny key card or fob access) or other mechanisms to prevent individuals into particular areas of the building (e.g., automatically locking or closing doors).

In various embodiments, individuals may access various areas of the building using a key card, fob, or mobile device. In response to attempting to access a particular area, the BMS controller 266 may alert the individual they are about to enter a high concentration area of a particular infectious agent. Alternatively, the BMS controller 266 or the individual device scanned may notify the individual (e.g., audio, visual, or a notification on the phone) that the pathway is closed. In various embodiments, the BMS controller 266 may restrict or completely block access to a particular area of the building when a concentration, presence, or load of an infectious agent is determined. For example, if a high concentration in the gym is determined, the BMS controller 266 in communication with the building security system may lock all doors and disable access into the area until a demand controlled ventilation process occurs and the concentration, presence, or load of the infectious agent is below a threshold (e.g., 10 ppm, 0 ppm). In the above example, the BMS controller 266 may also limit access to the area for a predetermined time (e.g., 30 minutes, 1 hour, 1 day) after the area is below a threshold.

In some embodiments, an exhaust damper 216 of the HVAC system 100 can be disposed at one or more security checkpoints (e.g., at metal detector, at all exterior doors, at a designated door or area where individuals enter the building) or entrances to a building. Sensors can be disposed within the exhaust damper 216 to function as a “breathalyzer” to identify sick individuals or groups before they enter into the building.

The risk metrics (e.g., severity, impact, seriousness, priority of particular infectious agents) can be based on amount of infectious agents sensed versus indication of humanness within the environment. In particular, humanness could be human gene sensing that all humans emit, typical CO2 occupancy estimation, or direct occupancy sensing via badges. In some embodiments, any measurement (e.g., concentration, load, or presence) of a particular infectious agent (e.g., COVID19) may be a risk, no matter the humanness of the environment. However, in various embodiments, a measurement of a particular infectious agent may not be an indication of a risk unless the concentration is above a particular threshold (e.g., ppm, percentage within the area, etc.). Accordingly, the infectious agent concentration, presence, or load can be cross-referenced to the humanness within the environment to measure how many people that may get sick and how severe the sickness may be. In various embodiments, the BMS controller 266 can cross-correlate time readings with access data and/or location system information to estimate whether one person is really sick or five people are sick but not as severe.

In various embodiments, the risk metrics can be based on amount of infectious agent sensed versus indication of density within the environment. In particular, density can be determined based on individuals accessing the building or CO2 levels within the building. Accordingly, the infectious agent concentration, presence, or load can be cross-referenced to the density within the environment to measure how many people that may get sick and how severe the sickness may be.

In some embodiments, the sampling and testing of the sensors can be used by the BMS controller 266 to determine who may be sick in an environment and with what infectious agent or agents. The BMS controller 266 can also correlate time readings, access data, and location information with the sensors to determine an infection point. The infection point can be a particular area within the building where the infectious agent has spread (e.g., elevator, access control point, lab, room 105). If an infection point can be determined, the BMS controller 266 can notify groups of individuals (corresponding to individuals that where at the infection point) to isolate who might be sick. Accordingly, proactively notifying groups of individuals can improve contact tracing and reduce the risk of spread of the particular infectious agent.

In some embodiments, the sampling and testing of the sensors can be used by the BMS controller 266 to determine a general prevalence of an infectious agent within a space (e.g., during flu season to determine potential flu exposure). Accordingly, general prevalence can improve scheduling of individuals within particular areas of the building. For example, in response to determining a general prevalence (e.g., presence of the infectious agent within most areas of the building) of the flu virus within a building, the building administrator can shut down the school for a two days. In another example, in response to determining a general prevalence of a cold virus within a building, the building administrator can schedule works to work remotely for three days. Accordingly, depending on the desire and request of the building administrator, the sensors can be disposed according to one or more preferences (e.g., determining general prevalence, determining particular individuals who are sick).

In various embodiments, the building can include a disinfection tunnel (DT) or sanitization tunnel disposed or stationed outside or just within entrances of the buildings. Individuals attempting to enter the building can walk through them or ride through them on two wheelers, where the tunnel can spray a mist of sodium hypochlorite solution or another type of disinfectant spray. For example, the tunnel can be equipped with infrared detectors (sensor-based) that activates the disinfectant spray whenever a person enters. In some embodiments, sensors can be disposed (e.g., placed) prior to and after the DT to detect actual disinfection or kill rate.

In various embodiments, any disinfectant system, including but not limited to, ultraviolet-C (UVC) light, far-UVC light, Ultraviolet germicidal irradiation (UVGI), or another disinfectant mechanism may be disposed throughout the building that can be turned on or activated (e.g., all day, at a predetermined time, or in response to detecting a presence or load of an infectious agent). This can selectively control the amount of equivalent clear air delivered. Accordingly, sensors disposed within or around the area providing light or a disinfectant mechanism can continuously collect and test samples to determine the concentration or presence of the infectious agent over a period of time to determine if the lights or disinfectant mechanism reduce the concentration or eliminated the presence of the infectious agent.

In various embodiments, a report on effectiveness of disinfection can be generated and provided to the various systems described herein and external systems. For example, the sensors or BMS controller 266 can execute one or more math functions over time to determine the effectiveness of the actions taken to reduce the spread of the infectious agent (e.g., lights, access restrictions, disinfection tunnel, adjusting exhaust damper).

Referring now to FIG. 3, a flowchart for a method 300 of continuous air quality monitoring, according to some embodiments. HVAC system 100 can be configured to perform method 300. Further, any computing device described herein can be configured to perform method 300.

In broad overview of method 300, at block 310, the one or more processing circuits (e.g., AHU controller 130 and/or BMS controller 266 in FIG. 2) can receive, from a plurality of sensors disposed throughout a building, infectious agent data. At block 320, the one or more processing circuits can determine at least one area of the building exposed to the infectious agent. At block 330, the one or more processing circuits can control an airflow source of air flowing through an air handling unit of an HAC system based on an indication of the infectious agent. Additional, fewer, or different operations may be performed depending on the particular arrangement. In some embodiments, some, or all operations of method 300 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.

At block 310, the one or more processing circuits can receive, from a plurality of sensors disposed throughout the building, infectious agent data, at least one of the plurality of sensors including an apparatus configured to collect samples, wherein the plurality of sensors configured to continuously test the samples over a sampling period for infectious agents and provide the infectious agent data to the controller. In general, the processing circuits aggregate and analyze data from various sensors to monitor the building's environmental health. Specifically, this data includes readings on air quality, temperature, humidity, the presence of infectious agents, among other measurements. For example, a sensor in a high-traffic area might report increased levels of airborne pathogens, prompting a response from the HVAC system. In another example, a sensor in a more isolated area could provide data indicating cleaner air quality, leading to different HVAC adjustments.

At block 320, the one or more processing circuits can in response to indicating of an infectious agent based on the infectious agent data, determine at least one area of the building exposed to the infectious agent. In some embodiments, the indication of the infectious agent is at least one of an indication of a presence of the infectious agent, an indication of a change in an amount of the infectious agent, or an indication of exceeding a threshold corresponding with the amount of the infectious agent. Furthermore, this determination enables continuous, targeted responses to mitigate the spread of the infectious agent within the building. Specifically, the processing circuits can activate containment measures, such as adjusting airflow or issuing alerts to restrict access to the affected area. For example, if an increase in an infectious agent is detected in a particular floor, the system may initiate enhanced air filtration in that zone while sending notifications or controlling a security systems (e.g., locking doors) to restrict entry until the area is deemed safe.

In some embodiments, the processing circuits can monitor the change in the amount of the infectious agent over a period of time, and wherein selectively controlling the amount of equivalent clean air is based on an increase in the amount of the infectious agent over the period of time in the at least one area of the building. In particular, the processing circuits can track and analyze trends in the levels of infectious agents, enabling proactive adjustments to the building's environmental controls. For example, if there's a gradual increase in an infectious agent in a specific wing of the building, the processing circuits might incrementally increase air filtration or reduce air circulation to that area (i.e., adjust an amount of ECA delivered). In another example, a sudden spike in infectious agent levels in a common area could prompt immediate redirection of airflow to isolate and address the contamination.

In some embodiments, selectively controlling the amount of equivalent clean air is in response to an increase in the amount of the infectious agent above a normal background level, and wherein the normal background level is specific to the at least one area of the building. In particular, the normal background level can correspond with a normal prevalence of an infectious agent in the particular area of the building. For example, in a surgery room of a hospital, a normal background level could be extremely low, reflecting the stringent sterility requirements in such an environment. In another example, a normal background level of a nursing home floor could be slightly higher, accounting for the typical presence of various pathogens in a residential care setting. In some embodiments, the normal background level may be multi-dimensional across various air quality measurements. Specifically, it may include a combination of factors like particulate matter, humidity, and specific pathogen concentrations. For example, in a laboratory setting, the normal background level might encompass low pathogen levels as well as specific humidity and particulate matter parameters critical for experimental integrity.

In some embodiments, the at least one of the plurality of sensors includes a collection apparatus, and wherein the samples are liquid samples collected via the collection apparatus. In general, the liquid samples could be collected in the collection apparatus from coils in a sensor housing (e.g., cooling or heating). Specifically, the liquid samples could be condensation or moisture that accumulates on these coils, indicative of various environmental conditions or the presence of infectious agents. For example, the collection apparatus might gather moisture from a cooling coil, which is then analyzed for pathogens or pollutants. In some embodiments, the plurality of sensors can collect solid samples from surfaces or particulates and/or gaseous samples from the ambient air.

In some embodiments, the processing circuits can determine a prevalence of the infectious agent in the building based on cross-referencing external infectious agent data of an external data source with the infectious agent data. Specifically, governmental data or community spread data can be cross-referenced with the building's data to enhance the accuracy of risk assessment and inform more targeted response strategies. For example, comparing the building's data with community spread reports from local health authorities can help determine if the prevalence of an infectious agent within the building is higher or lower than in the general public. Accordingly, the prevalence can be determined with respect to local or regional trends, allowing the building's management to adapt their safety protocols and HVAC system adjustments in response to the changing external risk levels.

Additionally, the processing circuits can (1) determine a baseline prevalence of the infectious agent in a public area of the building, (2) determine a prevalence of the infectious agent in the at least one area of the building, and (3) modify the selective control of the amount of equivalent clear air of the air flowing through the air handling unit of the HVAC system based on the prevalence in the at least one area being above the baseline prevalence in the public area. The baseline prevalence can correspond with a public space of the building. For example, the baseline prevalence might correspond to the average levels of infectious agents typically found in a lobby or a cafeteria. Thus, if the prevalence in a specific office area or a conference room exceeds this baseline, it indicates a heightened risk in those areas. The prevalence of the infectious agent in the at least one area can include data on specific pathogens or overall air quality metrics. For example, if the air in a particular wing shows a higher concentration of a certain pathogen than the lobby, this discrepancy could prompt a response. Modifying the selective control based on a comparison of these prevalence's could include increasing air filtration or reducing air circulation in the affected area. For example, if the air quality in a patient ward in a hospital is worse than in the common areas, the processing circuits might redirect cleaner air to the ward or increase the rate of air exchange in that area.

At block 330, the one or more processing circuits can selectively control an amount of equivalent clear air delivered to the at least one area based on the indication of the infectious agent. Specifically, the processing circuits can adjust the volume, direction, or quality of the airflow based on the detected level of infectious agents. For example, the processing circuits might increase the airflow in contaminated areas to dilute airborne pathogens. Furthermore, the processing circuits can activate additional air purification measures like HEPA filters or UV light sanitizers. In particular, these adjustments are dynamically made to respond to real-time data about air quality. For example, if a sensor detects an increase in infectious agents in a particular section of the building, the processing circuits can immediately (e.g., in real time or near real time) alter airflow to that area to mitigate the risk.

In some embodiments, selectively controlling the amount of equivalent clean air includes at least one of increasing an airflow rate or increasing outside air ventilation, air handling unit (AHU) airflow rate, in zone filtration, or in zone disinfection, and wherein the at least one processor are further configured to selectively activate at least one of a negative pressure space relative to rest of the building or a plurality of lighting apparatuses (e.g., UV lights) in at least one of the air handling unit or the at least one area. That is, to reduce or eliminate the infectious agent in the area, the processing circuits can increase the rate of air exchange or enhance air filtration capabilities (i.e., increase an amount of ECA delivered). For example, in a hospital room with a detected infectious agent, the airflow rate might be increased to rapidly replace the contaminated air. In another example, if a high level of pathogens is detected in an office space, the system could increase the intake of outside air to dilute the indoor air. Additionally or alternatively, the processing circuits can activate a negative pressure space in the area to contain the spread of the agent. For example, in a hospital isolation room, creating a negative pressure environment would prevent contaminated air from escaping to other parts of the building. Additionally or alternatively, the processing circuits can activate UV lighting in the ducting or in the area to neutralize airborne pathogens. For example, UV lights in the HVAC ducts can be turned on to disinfect air circulating through the building.

Referring to ECA in greater detail, the processing circuits (e.g., controller 230 or 266 of FIG. 2) can dynamically manage and control various aspects of indoor air quality (IAQ) to ensure a healthy environment. One aspect of this control is increasing the airflow rate. By elevating the volume of air circulated throughout the building, the processing circuits can dilute airborne pathogens, thereby reducing their concentration in the indoor environment. In some embodiments, enhancing outside air ventilation can be used. Introducing a greater volume of outside air into the building's circulation helps in displacing the potentially contaminated indoor air, thus lowering the overall concentration of infectious agents. Additionally, in some embodiments, localized approaches such as in-zone filtration can be employed (e.g., the processing circuit can generate and provide a notification with installation instruction to building management or an HVAC company to install). This can include installing high-efficiency air filters, like HEPA filters, within specific areas of the building. Furthermore, in some embodiments, in-zone disinfection methods, including UVC irradiation, can be utilized to actively neutralize pathogens in the air of specific areas. Accordingly, the processing circuits can adjust various factors in response to real-time data, providing a customized approach to maintaining optimal air quality, ensuring the ECA is effectively managed across different areas of the building for a safer and healthier indoor environment.

To quantify the ECA delivered, a mathematical model can be used that incorporates various factors such as the volume of the space, the rate and effectiveness of air filtration, the rate of outdoor air ventilation, the efficiency of disinfection methods like UVC, among other factors. This model can be used to calculate the ECA by comparing the combined effect of these air treatment strategies to the theoretical flow rate of completely clean air that would achieve the same reduction in infectious aerosol concentration. For example, if a room with a volume of 100 cubic meters utilizes an air filtration system that filters 50% of airborne pathogens and includes an outdoor air ventilation system that introduces 30 cubic meters of clean air per hour, the model would calculate the ECA by assessing how these factors collectively reduce the concentration of infectious aerosols to a level equivalent to a specified volume of pathogen-free air. In some embodiments, the ECA can be adjusted to reflect different environmental conditions or changes in the occupancy and usage of the space. For example, if the number of occupants in a room increases, leading to a higher production of aerosols, the ECA model could be updated to account for this change by adjusting the required volume of clean air to maintain the same level of aerosol reduction. Similarly, if newer air purification technologies are introduced or if existing systems are upgraded (e.g., installing more efficient filters or increasing the rate of outdoor air ventilation), the ECA value could be recalculated to reflect these improvements.

In some embodiments, to determine the ECA of any device in accordance with standards like ASHRAE 241, various evaluations can be performed by the processing circuits. This can include measuring the device's airflow rate, filtration efficiency, and the effectiveness of any incorporated disinfection technology, such as UVC. By comparing these measured values against the benchmarks set by the ASHRAE 241 Standard, which include criteria for outdoor air system and air cleaning system design, as well as installation, commissioning, operation, and maintenance requirements, it's possible to calculate an amount of ECA to deliver. This calculation takes into account the device's individual contribution to reducing infectious aerosol concentrations and integrates with and complements other air treatment strategies within the space. Additionally, this assessment may include testing under various environmental conditions and occupant scenarios to ensure the device's performance aligns with the standard's guidelines for maintaining a safe and healthy indoor environment.

For example, minimum equivalent clean air (ECA) delivery rate required in the breathing zone for occupiable space to mitigate long-range transmission in infection risk management mode (IRMM) (V_ECAi) can be determined in accordance with:

V ECA i = ECA i * P Z , IRMM

• • where V_ECAi is the minimum equivalent clear airflow rate required in the breathing zone to mitigate long-range transmission risk in IRMM, cfm (L/s), ECA_i is the equivalent clean airflow rate required per person in IRMM, cfm (L/s) per person, and P_Z,IRMM is the number of people in the breathing zone in IRMM. P_Z,IRMM can default to the number of occupants used to calculate the ventilation rate per the applicable standard or design occupancy or lower number of occupants during IRMM accepted by the owner. Where the occupancy category for a proposed space or zone is not listed, the requirements for the listed occupancy category that is most similar in terms of occupant density and activities shall be used. Where the occupancy category for a proposed space or zone involves group vocalization above a conversational level, the equivalent clean airflow rate required per person in IRMM shall be multiplied by a factor of 2. In a dwelling unit, the breathing zone consists of the habitable space as defined in ANSI/ASHRAE Standard 62.22. It is a region within the dwelling-unit habitable space between planes 3 and 72 in. (75 and 1800 mm) above the floor and more than 2 ft (600 mm) from the walls or fixed air-conditioning equipment.

In some embodiments, for air distribution and natural ventilation, a clean airflow rate to each zone can be calculation, which shall be greater than or equal to the minimum equivalent clean air (ECA) required, which can be determined in accordance with:

∑ [ z f * ( V OT + V VMS ) ] + ∑ V ACS + V NV ≥ V ECA i

• • where z_f refers to the zone air fraction, calculated by dividing the supply airflow rate to the zone by the total supply airflow rate to all zones, V_OT refers to the outdoor air intake flow rate measured in cubic feet per minute (cfm) or liters per second (L/s), V_VMS refers to the multizone air cleaning system equivalent clean airflow rate, computed as a V_ACS for an air cleaning system whose output is shared amongst zones, also in cfm or L/s, V_ACS refers to the air cleaning system equivalent clean airflow rate, typically as a function of the recirculated airflow rate to be treated (VRC), and V_NV refers to the outdoor airflow rate from a natural ventilation system, measured in the same units, and V_ECAi refers to the minimum equivalent clean airflow rate required in the breathing zone, also expressed in cfm or L/s.

In some embodiments, various methods of testing can be implemented to determine the ECA of various devices. For example, effectiveness tests can be conducted following general industry standards, focusing on evaluating the filter's capability to reduce airborne pathogens and assessing the overall effectiveness of the air cleaning systems. In another example, safety elements of these systems can be examined or tested to ensure they do not emit harmful byproducts or exceed established safety thresholds. When specific standards do not cover the effectiveness or safety performance of a system, custom tests can be performed by an independent laboratory. These tests provide a comprehensive assessment of the system's performance under a variety of operating conditions. Accordingly, the ECA values derived from these devices can be assured to be accurate, reliable, and in compliance with general health and safety guidelines.

Additionally or alternatively, the processing circuits can selectively control, in real-time or near real-time, access to the at least one area of the building, wherein selectively controlling access further includes locking at least one door controlling access to the at least one area. Specifically, this control might include automatically engaging locks on doors leading to the affected area to prevent entry or exit. For example, if a high concentration of an infectious agent is detected in a specific wing or area of a building, the processing circuits could lock the doors to that wing, limiting exposure and containing the spread until remediation efforts are complete.

In some embodiments, the processing circuits can communicate a presence of the infectious agent to a plurality of individuals selected based on cross-referencing location data of the plurality of sensors and location data of user devices of the plurality of individuals, wherein the communication of the presence further includes a notification to avoid the at least one area of the building. In particular, the processing circuits may send alerts or messages directly to the mobile devices of individuals who are in or near the affected area. Specifically, these notifications can include details about the detected agent and instructions to avoid the area for safety reasons. Moreover, the cross-referencing of sensor and user device locations provides that only those individuals in the vicinity or with a high likelihood of entering the area receive the alert. For example, employees working on the same floor as the detected infectious agent would receive a notification, while those in a different part of the building (or different building on the same campus) would not. In another example, visitors entering the building might receive an alert if their intended destination within the building is near an area with a detected infectious agent.

In some embodiments, the processing circuits can in response to indicating the infectious agent based on the infectious agent data, determine a plurality of guidelines or procedures corresponding with the at least one area of the building (e.g., in combination with or alternatively to delivering an amount of ECA), wherein the plurality of guidelines or procedures are different from a first area of the building and a second area of the building. For example, in a hospital's waiting area, the guidelines might include increased social distancing and mandatory mask-wearing, while in its intensive care unit, the procedures might involve stricter access control and enhanced personal protective equipment requirements. In another example, a corporate office might implement reduced occupancy in common areas like cafeterias but maintain normal operations in isolated office spaces. In particular, guidelines or procedures can be tailored to the specific activities and risk levels associated with each area. Specifically, areas with higher public interaction may have more stringent guidelines compared to less frequented zones. Moreover, these guidelines can be dynamically updated as the situation within the building evolves or as new information about the infectious agent becomes available.

In some embodiments, the processing circuits can generate a graphical user interface (GUI) including graphical information and steps for the determined plurality of guidelines or procedures, wherein the GUI includes at least one interactive item corresponding with implementing the determined plurality of guidelines or procedures. Specifically, the interactive item (i.e., actionable element) can be a button or item that influences an actionable activity (e.g., selection an action or perform an action related to air quality monitoring). In particular, the interactive item could initiate a process such as activating an air purifier or adjusting HVAC settings directly from the GUI. For example, a button in the GUI could allow users to instantly modify air filtration levels in their specific location. In some embodiments, the processing circuit can provide the GUI to at least one computing device within the at least one area of the building or associated with the at least one area, wherein the at least one computing device is associated with the at least one area based on at least one of scheduling information, a designation of association, or a previous presence of the at least one computing device within the at least one area. For example, the scheduling information could include room bookings, ensuring that the GUI related to that room's air quality appears on devices booked for meetings there. In another example, a designation of association could be based on the department or team affiliation of a user, linking their device to specific areas commonly used by their group. In yet another example, a previous presence of the at least one computing device within the at least one area could tailor the GUI to show guidelines and controls relevant to areas where the device was recently detected. Accordingly, this ensures that the GUI is contextually relevant and useful to its users, improving compliance and effectiveness of the guidelines.

In some embodiments, the processing circuits can (1) monitor an amount of the infectious agent in the building, (2) determine controlling the amount of equivalent clear air and the plurality of guidelines or procedures decreased the amount of the infectious agent in the building, and (3) modify the selective control of the amount of equivalent clear air of the air flowing through the air handling unit of the HVAC system. Monitoring can include continuously assessing air quality data from sensors and comparing it against established infectious agent thresholds. For example, sensors might track changes in particulate matter that could indicate the presence of an infectious agent. Determining the controls and guidelines have decreased the amount of the infectious agent can include analyzing trends in the collected data over time and comparing these against the periods before and after implementing specific controls. For example, a noticeable reduction in airborne pathogens following the adjustment of HVAC settings or the implementation of new safety guidelines would indicate their effectiveness. Modifying the selective control can include making further adjustments to the HVAC settings based on the effectiveness of the previous changes, such as fine-tuning air filtration rates or ventilation patterns. For example, if the data shows a significant improvement in air quality, the processing circuits might reduce the intensity of the air purification measures (e.g., reduce the amount of ECA delivered) to maintain a balance between air quality and energy efficiency.

In some embodiments, a map can be generated and presented using the infectious agent data. The map, created by integrating data from multiple sources, could provide a visual representation of the concentration of infectious agents across different areas. The processing circuits could utilize the building's blueprint as a base, overlaying continuous sensor data that reflects current conditions, along with historical infectious agent data to offer context and trend analysis. Each sensor's location, whether it's monitoring a specific room, area, or floor, would be pinpointed on the map, providing readings of infectious agent levels. The map could also include time stamps to show how the risk evolves throughout the day. In some embodiments, severity or risk metrics, such as the concentration of infectious agents like COVID-19, could be visually represented (e.g., through a color-coding system). For example, areas with low concentrations (below 10 ppm) could be marked in green, indicating a relatively safe environment. Moderate levels (10 ppm to 50 ppm) might be highlighted in yellow. High-risk areas (above 50 ppm) would be marked in red.

In some embodiments, method 300, encompassing steps similar to those in blocks 310-330, can be effectively adapted for use in “moving buildings or areas” like subways and public buses. In a subway train, sensors integrated throughout each carriage could monitor air quality, temperature, humidity, and the presence of infectious agents. For instance, increased levels of airborne pathogens detected near the doors as passengers board could prompt the onboard HVAC system to enhance air filtration or circulation. Conversely, sensors in less crowded carriages might indicate cleaner air, leading to different HVAC adjustments in those areas. Similarly, in a public bus scenario, processing circuits responding to pathogen presence could adjust airflow to isolate contaminated areas, like the front half of the bus, by increasing air exchange with the outside or activating localized air purifiers. This could be complemented by real-time mobile alerts to passengers, advising precautionary measures. The bus's HVAC system might also dynamically adjust to increase filtration efficiency, especially in areas with higher pathogen concentrations.

Expanding further on the subway example, the implementation of method 300 in this context can address the unique challenges of a constantly changing environment. The subway cars, continuously moving between stations and varying in passenger load, demand a dynamic response system. Sensors could be placed at strategic locations like near doors, seating areas, and ventilation units to continuously monitor for changes in air quality and pathogen levels. When a high concentration of an infectious agent is detected, the processing circuits could immediately activate enhanced air purification systems, such as HEPA filters or UV lights, within specific subway cars. This response would be particularly important during peak hours when passenger density increases the risk of airborne transmission. Additionally, the processing circuits could adjust the internal airflow to prevent the spread of contaminants from one car to another. In the event of a significant health risk, the processing circuits might also communicate with the train operator or central control to take broader actions, such as temporarily halting service or diverting the train to a less crowded route. Additionally, in response to the detection of high levels of infectious agents, some cars of the subway may be automatically closed off to passengers, limiting access to those areas until they are deemed safe again.

Referring now to FIG. 4, a block diagram of sensors 420 in a networked environment, according to some embodiments. In some embodiments, the sensor(s) 420 can be configured to collect samples (e.g., liquid and fluid, solid, gaseous). A sensor 420 can be configured to collect, test, and provide infectious agent data over a sampling period. In some embodiments, the multi-spectral analysis system 424 can continuously test the samples collected by the collection apparatus 422 to allow for continuous readings of infectious agents that can be used by the HVAC system 100 and controllers described herein with real-time data regarding potential presence of infectious agents and infectious agent loads within specific rooms, areas, or spaces within the building. For example, the sensor 420 could be, but is not limited to, particle counters, particulate matter (PM) sensors, volatile organic compound (VOC) sensors, CO2 sensors, temperature and humidity sensors, aerosol mass spectrometers, or infrared spectrometers. As used herein, “continuous air quality monitoring” refers to the regular and systematic measurement of various air quality parameters over a period of time (e.g., sampling period), which may range from frequent intervals to near-constant monitoring. This approach does not imply non-stop measurement but encompasses consistent assessments at predefined intervals, providing an understanding of air quality trends and immediate detection of any anomalies or hazardous conditions. The frequency of these assessments can be customized to suit the specific needs of the environment being monitored.

In general, the sensors 420 include integrated processing circuits and memory components. These elements enable the sensor to execute a variety of instructions for its operation. The processing circuitry is configured to interpret data collected by the sensor, performing tasks such as initial data analysis, calibration, and error detection. Meanwhile, the memory component stores operational software, calibration data, and temporarily holds the collected data (e.g., infectious agent data). This configuration allows the sensor 420 to function autonomously, processing and preparing data for further analysis by the multi-spectral analysis system 424 or for direct use by the HVAC system 100 and its controllers. Accordingly, the sensor 420 can operate efficiently and reliably in a range of environmental conditions, providing accurate and timely data regarding the presence of infectious agents.

In some embodiments, the collection apparatus 422 is configured to gather fluids, such as those obtained from the condensation of cooling coils, solid samples from surfaces or particulates, and gaseous samples from the ambient air. The apparatus may include mechanisms like condensate traps for fluid collection, particulate filters for solids, and air samplers for gaseous samples. For example, the collection apparatus 422 could be, but is not limited to, devices such as fluid collectors for a variety of liquid sources (e.g., condensation from cooling coils, environmental moisture), solid sample collectors (e.g., surface swabs, particulate filters), and gas samplers (e.g., air quality monitors, vapor analyzers). In one example, the collection apparatus 422 can be configured to collect condensation from a cooling coil (disposed within sensor 420). The collection apparatus 422 can include one or more pipe systems, fittings, sponge systems, wash systems, suction systems, drip pans, mechanical wipe systems, etc. Condensation that forms on the cooling coil of sensor 420 can be collected by the collection apparatus 422 and provided to the multi-spectral analysis system 424 for analysis and testing. Additionally, the collection apparatus 422 can collect liquid from a heating coil (also disposed within sensor 420), upon the liquid vapor in the air condensing.

Referring still to the cooling coil and heating coil example. While the coiling/dehumidification water in the air condenses on the surface of the cooling coil, making the entire surface of the cooling coil wet. Over time this water flows down the surface (based on gravitational force) of the cooling coil and is collected by the collection apparatus 422, e.g., in a drain pan or drip pan or collection pan. In some cases, the particles of the sample are collected in the condensate water and are representative of the particles in the air. This condensate water could be fed directly to the multi-spectral analysis system 424 by the collection apparatus 422. In some embodiments, the collection apparatus 422 could be installed to collect moisture from a thermo-electric cooler of the sensor 420. The collection apparatus 422 could cause moisture in the air to condense onto a plate. Dirt in the air would be trapped in the water and the water would be collected for analysis. In some embodiments, the collection apparatus 422 can wipe the plate to ensure a clean start on each cycle.

In some embodiments, the multi-spectral analysis system 424 provides a broader range of testing capabilities, enabling the sensor 420 to analyze fluids, solids, and gases for the presence of infectious agents. The multi-spectral analysis system 424 could encompass a variety of analytical techniques, such as spectrometry, chromatography, and molecular biology methods, which are adaptable to different sample types. For example, the multi-spectral analysis system 424 could be, but is not limited to, an analytical tool capable of processing and analyzing a wide range of sample types, including spectrometry for fluid analysis (e.g., infrared, mass spectrometry), microscopic techniques for solid samples (e.g., electron, atomic force microscopy), and advanced gas analysis methods (e.g., gas chromatography, mass spectrometry).

The collection apparatus 422 and the multi-spectral analysis system 424 are configured to work together efficiently. The collection apparatus 422 gathers fluids, solids, and gases, and then transports these samples directly to the multi-spectral analysis system 424. For fluid samples, this could involve pathways or pumps that move the liquid. Solid samples could be transported in a way that prevents contamination, while gaseous samples are channeled through airtight tubing. At the multi-spectral analysis system 424, each sample type is analyzed using appropriate techniques.

Referring in great detail to the transport of the samples by the collection apparatus 422, the system is designed to handle each type of sample with precision. Fluid samples, such as those collected from condensation, are moved through channels that are either sloped to utilize gravity or equipped with pumps for active transport. These channels are sealed and constructed to prevent any leakage or evaporation, ensuring that the samples reach the multi-spectral analysis system 424. Solid samples, which could range from surface swabs to particulate matter, can be handled in a manner that minimizes their exposure to external elements. They can be transported in enclosed carriers that protect them from any potential contaminants. For gaseous samples, the collection apparatus 422 can use airtight tubing systems. These tubes can maintain a consistent pressure and composition of the gas sample from the point of collection to the analysis system. Once these samples are delivered to the multi-spectral analysis system 424, they undergo an analysis.

Additionally, as shown, the analyzed and tested samples can be saved into infectious agent data and provided to the AHU controller 230 or the BMS controller 266 (not shown) over network 410. Network 410 represents a digital communication system, comprising wired or wireless connections, which facilitates the transmission of data between the sensors 420 and controllers 230 and 266. The conversion of samples into infectious agent data can include processing the physical samples through the multi-spectral analysis system 424, which then translates the results into digital data formats. This digital data, encapsulating detailed information about the presence and concentration of infectious agents, is subsequently relayed over the network 420 to the appropriate control systems for further action or monitoring.

Referring now to FIG. 5, an illustrative example a building 500 with sensors and controls, according to some embodiments. As shown, the building 500 can include area sensors 502, 504, 506, 508, 510, 512, 514, 516, 518 (shown with a designated letter A-I). In particular, each sensor can be positioned within an area of the building. In general, an “area” of the building can refer to any distinct zone or section within the structure, such as individual rooms, common spaces, corridors, HVAC zones, or any other designated part of the building that has specific use or occupancy characteristics. For example, sensors 502-506 are positioned in a designated public area of the building 500 (e.g., most commonly trafficked areas of people, such as entrances, dining areas, hallways, etc.). In another example, sensors 508-516 are positioned within various rooms or spaces of the building. In yet another example, sensor 518 is positioned with HVAC ducting 520, shown in dotted lines within the building 500. In some embodiments, the sensors 502-518 can be configured to collect various samples. Each sensor can be uniquely configured to collect particular samples in the various areas. Some sensors can be temporary or permanent. For example, temporary sensors can be installed (e.g., sensor 514) when a particular area is indicated as having a certain level or presence of an infectious agent. In some embodiments, the building 500 can include various IoT devices 522, 525, 526, 526, 530. For example, the IoT devices 522-530 can control access to various areas of building 500.

Expanding on the function and placement of sensors 502-518 in building 500, each sensor is designated to a specific location to monitor environmental variables. For example, sensor 502 could be located near the main entrance to track air quality where foot traffic is highest, potentially utilizing the measurements as a baseline prevalence of an infectious agent. Sensor 514 (e.g., a temporary installation) could be positioned in a conference room used for large gatherings, specifically to monitor CO2 levels and airborne pathogens, alerting to any changes that exceed normal ranges. These sensors 502-518 can measure parameters like temperature and humidity but can also detect finer details such as particulate matter (PM) size or specific pathogen presence. Sensor 518, placed within the ducting 520, can monitor air passing through the HVAC system for pathogens. Based on its readings, the air handling unit can modify airflow to specific areas of the building. If an infectious agent is detected, the system can redirect air away from affected zones, increase filtration in those areas, increase outdoor air intake, or activate a negative pressure room.

The IoT devices 522-530, dispersed at critical points, are multifunctional. For example, device 526 might be linked to a meeting room, programmed to allow entry only when air quality parameters are within safe limits. If sensor 510 in the same room detects high levels of CO2 or an airborne pathogen, device 526 could temporarily lock the room or redirect occupants to a safer area, effectively preventing exposure. The IoT devices 522-530 can also be programmed for conditional access; for example, allowing only personnel with specific clearances during an environmental alert, ensuring that only authorized and necessary personnel can enter sensitive areas during potential health risk events. Additionally, devices near entrances (e.g., IoT device 522) might include biometric scanners, controlling access based on health data like temperature or vaccination status. In sensitive areas like research labs, access might be restricted to only those who meet specific health criteria, such as recent negative test results. IoT devices 522-530 equipped with cameras can enforce mask-wearing policies, allowing entry only to compliant individuals. In response to varying infection risks, the IoT devices 522-530 can adjust their parameters: for example, during a high-risk period, access to communal areas might be limited, or entry to certain floors might be restricted to essential personnel only.

In a nursing home example, sensors could be positioned differently across floors to address varying air quality needs; for example, sensors on the first floor, a public and high-traffic area, would focus on general air quality and pathogen detection, while sensors on the second floor, housing more vulnerable residents, would have heightened sensitivity to airborne pathogens. In a hospital, the placement and function of sensors would vary significantly between areas: sensors in surgery rooms would be tuned for the highest levels of air purity and contaminant detection, while sensors in general wards might focus more on overall air quality and comfort levels. Each area's specific requirements would dictate the sensor setup, ensuring that air quality is maintained according to the particular needs of the space.

Referring now to FIG. 6, a graphical interface 600 including interface objects, according to some embodiments. The user interface 600 may be presented within the user client application of a computing device 610 (e.g., user device, mobile device). In some embodiments, the user interface 600 is generated and provided by a controller (e.g., BMS controller 266 or AHU controller 230) of the HVAC system 100. The content can contain an actionable element (e.g., activity or action). In some embodiments, the user interface 600 may contain one or more actionable (or interactable) buttons or items (e.g., 602, 604, 606, 608, 609) that influences an actionable activity (e.g., selection an action or perform an action related to air quality monitoring). In general, the user interface 600 of FIG. 6 depicts an infection dashboard with actions to monitor or update the air quality of the building that, upon selection, the processing circuits can initiate and/or perform the action to monitor or improve the air quality of a building. As shown, the summary button 602 can be selected, which can in turn present a summary dashboard of current access controls, HVAC controls, and guidance of the building, including specific areas (e.g., floors, spaces, rooms).

The access controls button 604 can be selected, which can in turn present current access of the particular user of the computing device 610 to particular areas of the building. For example, building access could be allowed but floor 2 access could be disallowed because of recent detection of an infectious agent in that area. In another example, access to a specific wing of the building might be limited to essential personnel only during high-risk periods. The HVAC controls button 606 can be selected, which can in turn present current HVAC controls of the HVAC system 100 to particular areas of the building. For example, control #1 of floor 2 could be set to increase air filtration and circulation in response to an air quality alert. In another example, control #2 of room 101 could be adjusted to reduce airflow (i.e., controlling the amount of ECA delivered) and limit the potential spread of contaminants. The HVAC controls button 608 can be selected, which can in turn present current guidance controls of the HVAC system 100 to particular areas of the building. The plurality of guidelines or procedures can be different from a first area of the building and a second area of the building. For example, a list of guidelines could be provided such as wear a mask, open windows, and limit in-person meetings. In another example, guidelines could include enhanced cleaning protocols and restricted use of communal areas. The update now button 609 could be configured to perform sampling and testing of the sensors within the building. This action can provide the most current environmental data, including air quality and potential infectious agents. The results from this real-time analysis can then promptly updated on the user interface 600, providing an up-to-date overview of the building's conditions. Additionally, the last updated time can be presented on the user interface 600.

Referring now to FIG. 7, a graphical interface 700 including interface objects, according to some embodiments. The graphical interface 700 can be presented on a computing device 610 such as a user device and/or mobile device. As shown, the graphical interface 700 can be shown in response to selecting the summary interface object 602 of the interface dashboard of graphical interface 600. In some embodiments, the HVAC system 100 can provide notifications that presents GUIs such as the one shown in FIG. 7. For example, when computing device 610 is within a particular location of a building, the HVAC system 100 can provide a notification that presents the current summary interface that is customized to the particular individual and their role and responsibility within the particular building. Additionally, some companies or businesses may have a campus with multiple building. In some embodiments, prior to the computing device 610 entering a particular building on the campus, the HVAC system 100 can provide the summary interface or a different notification that presents on the viewport of the computing device 610 that includes current information and controls of the particular building on the campus.

In some embodiments, the user can select various actionable elements such as the WHY? buttons 612, 614, and 616 regarding the disallowed access to floor 2, room 101, and room 105. Upon selection of the WHY? buttons 612, 614, and 616, the user interface 700 can present a pop-up or separate screen that provides detailed explanations and data regarding the specific reasons for access restrictions to floor 2, room 101, and room 105, such as recent air quality reports or detected infectious agents. In some embodiments, the user can select various actionable elements such as the WHAT? buttons 618, 620, 622 regarding the HVAC controls of floor 2, room 101, and room 105. Upon selection of the WHAT? buttons 618, 620, 622, the user interface 700 can present a pop-up or separate screen that displays the current HVAC settings or adjustments made for floor 2, room 101, and room 105, along with the rationale for these specific controls. In some embodiments, the user can select various actionable elements such as the “Where to obtain a mask?” button 624 and the “Re-schedule in-person meetings” button 626 regarding the current guidelines or procedures. Upon selection of the button 624, the user interface 700 can present a pop-up or separate screen that shows locations within the building where masks are available, including any relevant safety guidelines. Upon selection of the button 626, the user interface 700 can present a pop-up or separate screen that assists in rescheduling in-person meetings to virtual formats or to safer locations within the building, based on current health advisories and room availability.

It should be understood that each infection dashboard can be uniquely tailored to an individual, linked to their specific account as an employee or customer of the building. This personalized dashboard means that the access controls and guidance displayed on the dashboard can vary depending on the user's role or status, offering customized information and restrictions. For example, the dashboard for a nurse may show different access permissions and health guidelines compared to those for a doctor or a receptionist, reflecting their distinct responsibilities and areas of access within the building. Additionally, to access the user client application and its features, including the personalized infection dashboard, a user may need to set up an account. This account setup process can involve providing details like role, contact information, relevant health status, and setting up a username, password, and/or biometric ensuring that the dashboard's information and controls are customized to the user's specific needs and access privileges within the building.

Configuration of Exemplary Embodiments

Although 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 could 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 comprise 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 comprising 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 comprise 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.