Methods and systems for improving infection control in a building

Information

  • Patent Grant
  • 12131821
  • Patent Number
    12,131,821
  • Date Filed
    Wednesday, November 8, 2023
    a year ago
  • Date Issued
    Tuesday, October 29, 2024
    24 days ago
Abstract
A building management system (BMS) for a medical facility that includes a plurality of rooms with at least one of the rooms having a plurality of sensors. An elevated infection risk determination system is operatively coupled to the plurality of sensors for determining when an elevated infection risk occurs in one or more of the rooms. The BMS may include a memory for storing one or more programmable infection risk compliance parameters, an input port for receiving an elevated infection risk alert for the particular room in the medical facility, a control port for providing control commands to one or more building components of the building management system, and a controller. The controller may be configured to provide control commands via the control port in response to receiving the elevated infection risk alert for the particular room based at least in part on one or more programmable infection risk compliance parameters to help mitigate the elevated infection risk in the particular room.
Description
TECHNICAL FIELD

The disclosure generally relates to building management systems, and more particularly to systems and methods for monitoring and manipulating conditions in a building to reduce the risk of infection for building occupants.


BACKGROUND

Hospital Acquired Infections (HAI) and/or Surgical Staff Infections (SSI) are infections caused by virus, bacteria and other environmental factors and are acquired within hospitals or other medical treatment facilities. It is estimated that HAI and SSI infections cost the healthcare industry nearly $40 billion annually. HAI and SSI infections can be transmitted in multiple ways, including, but not limited to, surface contamination, airborne particulates and aspiration. Depending on the medical application, activity, surgical procedure, and/or susceptibility of the patient, it is believed that airborne particulates may contribute up to 90% of the HAI or SSI cases. Room contamination from outside air, such as from door openings in an operating room, were also found to directly correlated to increased HAI and SSI.


What would be desirable is a building management system (BMS) that is configured to improve healthcare hygiene and/or indoor environmental conditions within a building to help reduce HAI and SSI.


SUMMARY

This disclosure generally relates to systems and methods for reducing a risk of infection in a medical facility.


In a first example, a method for controlling a building management system of a medical facility including a plurality of rooms with at least one of the rooms having a plurality of sensors, wherein an elevated infection risk determination system is operative coupled to the plurality of sensors for determining an elevated infection risk in one or more of the rooms of the medical facility may comprise receiving one or more programmable infection risk compliance parameters for a particular room in the medical facility and storing the received one or more programmable infection risk compliance parameters in a memory. The method may further comprise receiving from the elevated infection risk determination system an elevated infection risk alert for the particular room in the medical facility and in response to receiving the elevated infection risk alert for the particular room, controlling the building management system in accordance with the one or more programmable infection risk compliance parameters for the particular room to help mitigate the elevated infection risk in the particular room.


In another example, a building management system (BMS) for a medical facility that includes a plurality of rooms with at least one of the rooms having a plurality of sensors, wherein an elevated infection risk determination system is operatively coupled to the plurality of sensors for determining an elevated infection risk in one or more of the rooms of the medical facility may comprise a memory for storing one or more programmable infection risk compliance parameters for a particular room in the medical facility, an input port for receiving from the elevated infection risk determination system an elevated infection risk alert for the particular room in the medical facility, a control port for providing control commands to one or more building components of the building management system, and a controller operatively coupled to the memory, the input port and the control port. The controller may be configured to provide control commands via the control port in response to receiving the elevated infection risk alert for the particular room to help mitigate the elevated infection risk in the particular room, wherein the one or more control commands control the building management system in accordance with the one or more programmable infection risk compliance parameters for the particular room.


In another example, a method for controlling a building management system of a medical facility, wherein the medical facility includes a plurality of rooms of different room types, with at least one of the rooms having a plurality of sensors, wherein an elevated infection risk determination system is operative coupled to the plurality of sensors for determining an elevated infection risk in one or more of the rooms of the medical facility may comprise receiving one or more programmable infection risk compliance parameters for each of the different room types, receiving from the elevated infection risk determination system an elevated infection risk alert for a particular room in the medical facility having a particular room type, and in response to receiving the elevated infection risk alert for the particular room that has a particular room type, controlling the building management system in accordance with the one or more programmable infection risk compliance parameters that correspond to the particular room type to help mitigate the elevated infection risk in the particular room.


The preceding summary is provided to facilitate an understanding of some of the features of the present disclosure and is not intended to be a full description. A full appreciation of the disclosure can be gained by taking the entire specification, claims, drawings, and abstract as a whole.





BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may be more completely understood in consideration of the following detailed description of various embodiments in connection with the accompanying drawings, in which:



FIG. 1 is a schematic view of a building or other structure that includes an illustrative building management system (BMS) that controls client devices servicing the building or other structure;



FIG. 2 is a schematic block diagram of the illustrative BMS of FIG. 1;



FIG. 3 is a schematic block diagram of an illustrative infection risk reduction system that uses a building management system (BMS);



FIG. 4 is a flow chart of an illustrative method for controlling a building management system to help reduce HAI and SSI in the building;



FIG. 5 shows database entries of illustrative programmable infection risk compliance parameters; and



FIGS. 6-8 are schematic views of rooms including an infection risk reduction system.





While the disclosure is amenable to various modifications and alternative forms, specifics thereof have been shown by way of example in the drawings and will be described in detail. It should be understood, however, that the intention is not to limit aspects of the disclosure to the particular embodiments described. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the disclosure.


DESCRIPTION

The following detailed description should be read with reference to the drawings in which similar elements in different drawings are numbered the same. The detailed description and the drawings, which are not necessarily to scale, depict illustrative embodiments and are not intended to limit the scope of the disclosure. The illustrative embodiments depicted are intended only as exemplary. Selected features of any illustrative embodiment may be incorporated into an additional embodiment unless clearly stated to the contrary.


The disclosure generally relates to building management systems, and more particularly to systems and methods for monitoring and manipulating conditions in a building to help reduce the risk of infection for building occupants. FIG. 1 is a schematic view of a building or structure 10 that includes an illustrative building management system (BMS) 12 for controlling one or more client devices servicing the building or structure 10. The BMS 12, as described herein according to the various illustrative embodiments, may be used to control the one or more client devices in order to control certain environmental conditions (e.g., temperature, ventilation, humidity, lighting, etc.) to reduce the risk of infection for building occupants. While such a BMS 12 may be implemented in a hospital or other clinical setting, it contemplated that the BMS 12 may be included in other buildings such as office buildings, health clubs, movie theaters, restaurants, and even residential homes.


The illustrative BMS 12 shown in FIG. 1 includes one or more heating, ventilation, and air conditioning (HVAC) systems 20, one or more security systems 30, one or more lighting systems 40, one or more fire systems 50, and one or more access control systems 60. These are just a few examples of systems that may be included or controlled by the BMS 12. In some cases, the BMS 12 may include more or fewer systems. In some cases, each system may include a client device configured to provide one or more control signals for controlling one or more building control components and/or devices of the BMS 12.


For instance, in some cases, the HVAC system 20 may include an HVAC control device 22 used to communicate with and control one or more HVAC devices 24a, 24b, and 24c (collectively, 24) for servicing the HVAC needs of the building or structure 10. While the HVAC system 20 is illustrated as including three devices, it should be understood that the structure may include fewer than three or more than three devices 24, as desired. Some illustrative devices may include, but are not limited to a furnace, a heat pump, an electric heat pump, a geothermal heat pump, an electric heating unit, an air conditioning unit, a humidifier, a dehumidifier, an air exchanger, an air cleaner, a damper, a valve, blowers, fans, motors, and/or the like. The HVAC system 20 may further include a system of ductwork and air vents (not explicitly shown). The HVAC system 20 may further include one or more sensors or devices 26 configured to measure parameters of the environment to be controlled. The HVAC system 20 may include more than one sensor or device of each type, as needed to control the system. It is contemplated that large buildings, such as, but not limited to, a hospital, may include a plurality of different sensors in each room or within certain types of rooms. The one or more sensors or devices 26 may include, but are not limited to, temperatures sensors, humidity sensors, carbon dioxide sensors, occupancy sensors, proximity sensors, etc. Each of the sensor/devices 26 may be operatively connected to the controller 22 via a corresponding communications port (not explicitly shown). It is contemplated that the communications port may be wired and/or wireless. When the communications port is wireless, the communications port may include a wireless transceiver, and the controller 22 may include a compatible wireless transceiver. It is contemplated that the wireless transceivers may communicate using a standard and/or a proprietary communication protocol. Suitable standard wireless protocols may include, for example, cellular communication, ZigBee, Bluetooth, WiFi, IrDA, dedicated short range communication (DSRC), EnOcean, or any other suitable wireless protocols, as desired.


In some cases, the security system 30 may include a security control device 32 used to communicate with and control one or more security units 34 for monitoring the building or structure 10. The security system 30 may further include a number of sensors/devices 36a, 36b, 36c, 36d (collectively, 36). The sensor/devices 36 may be configured to detect threats within and/or around the building 10. In some cases, some of the sensor/devices 36 may be constructed to detect different threats. For example, some of the sensor/devices 36 may be limit switches located on doors and windows of the building 10, which are activated by entry of an intruder into the building 10 through the doors and windows. Other suitable security sensor/devices 12 may include fire, smoke, water, carbon monoxide, and/or natural gas detectors, to name a few. Still other suitable security system sensor/devices 36 may include motion sensors that detect motion of intruders in the building 10, noise sensors or microphones that detect the sound of breaking glass, security card pass systems, or electronic locks, etc. It is contemplated that the motion sensor may be passive infrared (PIR) motion sensors, a microwave motion sensor, an ultrasonic motion sensor, a tomographic motion sensor, a video camera having motion detection software, a vibrational motion sensor, etc. In some cases, one or more of the sensor/devices 36 may include a video camera. In some cases, the sensor/devices 36 may include a horn or alarm, a damper actuator controller (e.g. that closes a damper during a fire event), a light controller for automatically turning on/off lights to simulate occupancy, and/or any other suitable device/sensor. These are just examples.


In some cases, the lighting system 40 may include a lighting control device 42 used to communicate with and control one or more light banks 44 having lighting units L1-L10 for servicing the building or structure 10. In some embodiments, one or more of the lighting units L1-L10 may be configured to provide visual illumination (e.g., in the visible spectrum) and one or more of the light units L1-L10 may be configured to provide ultraviolet (UV) light to provide irradiation. The lighting system 40 may include emergency lights, outlets, lighting, exterior lights, drapes, and general load switching, some of which are subject to “dimming” control which varies the amount of power delivered to the various building control devices.


In some cases, the fire system 50 may include a fire control device 52 used to communicate with and control one or more fire banks 54 having fire units F1-F6 for monitoring and servicing the building or structure 10. The fire system 50 may include smoke/heat sensors, a sprinkler system, warning lights, and so forth. In some cases, the access control system 60 may include an access control device 62 used to communicate with and control one or more access control units 64 for allowing access in, out, and/or around the building or structure 10. The access control system 60 may include doors, door locks, windows, window locks, turnstiles, parking gates, elevators, or other physical barrier, where granting access can be electronically controlled. In some embodiments, the access control system 60 may include one or more sensors 66 (e.g., RFID, etc.) configured to allow access to the building or certain parts of the building 10.


In a simplified example, the BMS 12 may be used to control a single HVAC system 20, a single security system 30, a single lighting system 40, a single fire system 50, and/or a single access control system 60. In other embodiments, the BMS 12 may be used to communicate with and control multiple discrete building control devices 22, 32, 42, 52, and 62 of multiple systems 20, 30, 40, 50, 60. The devices, units, and controllers of the systems 20, 30, 40, 50, 60 may be located in different zones and rooms, such as a common space area (a lobby, a waiting room, etc.), in a dedicated space (e.g., a patient room, an operating room, etc.) or outside of the building 10. In some cases, the systems 20, 30, 40, 50, 60 may be powered by line voltage, and may be powered by the same or different electrical circuit. It is contemplated that the BMS 12 may be used to control other suitable building control components that may be used to service the building or structure 10.


According to various embodiments, the BMS 12 may include a host device 70 that may be configured to communicate with the discrete systems 20, 30, 40, 50, 60 of the BMS 12. In some cases, the host device 70 may be configured with an application program that assigns devices of the discrete systems to a particular device (entity) class (e.g., common space device, dedicated space device, outdoor lighting, unitary controller, and so on). In some cases, there may be multiple hosts. For instance, in some examples, the host device 70 may be one or many of the control devices 22, 32, 42, 52, 62.


In some cases, the building control devices 22, 32, 42, 52, 62 may be configured to transmit a command signal to its corresponding building control component(s) for activating or deactivating the building control component(s) in a desired manner. In some cases, the building control devices 22, 32, 42, 52, 62 may be configured to receive a classification of building control component and may transmit a corresponding command signals to their respective building control component in consideration of the classification of the building control component.


In some instances, the building control devices 22, 32, 62 may be configured to receive signals from one or more sensors 26, 36, 66 located throughout the building or structure 10. In some cases, the building control devices 42 and 52 may be configured to receive signals from one or more sensors operatively and/or communicatively coupled with the lighting units L1-L10 and the fire units F1-F6 located throughout the building or structure 10, respectively. In some cases, the one or more sensors may be integrated with and form a part of one or more of their respective building control devices 22, 32, 42, 52, 62. In other cases, one or more sensors may be provided as separate components from the corresponding building control device. In still other instances, some sensors may be separate components of their corresponding building control devices while others may be integrated with their corresponding building control device. These are just some examples. The building control devices 22, 32, 42, 52, 62 and the host device 70 may be configured to use signal(s) received from the one or more sensors to operate or coordinate operation of the various BMS systems 20, 30, 40, 50, 60 located throughout the building or structure 10.


The one or more sensors 26, 36, 66, L1-L10, and F1-F6 may be any one of a temperature sensor, a humidity sensor, an occupancy sensor, a light sensor, a video camera, a current sensor, a smoke sensor and/or any other suitable sensor. In one example, at least one of the sensors 26, 36, 66, or other sensors, may be an occupancy sensor. The building control devices 22, 32, 42, 62 and/or the host device 70 may receive a signal from the occupancy sensor indicative of occupancy within a room or zone of the building or structure 10. In response, the building control devices 22, 32, 42, and/or 62 may send a command to activate one or more building control component(s) located in or servicing the room or zone where occupancy is sensed.


Likewise, in some cases, at least one of the sensors 26 may be a temperature sensor configured to send a signal indicative of the current temperature in a room or zone of the building or structure 10. The building control device 22 may receive the signal indicative of the current temperature from the temperature sensor 26. In response, the building control device 22 may send a command to an HVAC device 24 to activate and/or deactivate the HVAC device 24 that is in or is servicing that room or zone to regulate the temperature in accordance with a desired temperature set point.


In yet another example, one or more of the sensors may be a current sensor. The current sensor may be coupled to the one or more building control components and/or an electrical circuit providing electrical power to one or more building control components. The current sensors may be configured to send a signal to a corresponding building control device, which indicates an increase or decrease in electrical current associated with the operation of the building control component. This signal may be used to provide confirmation that a command transmitted by a building control device has been successfully received and acted upon by the building control component(s). These are just a few examples of the configuration of the BMS 12 and the communication that can take place between the sensors and the control devices.


As shown in FIG. 2, the host device 70 can function as a server, a client, a local controller, or any other suitable device. In the example shown, the host device 70 can perform various communication and data transfer functions as described herein and can execute one or more application functions. The host device 70 can be any of a variety of computing devices, such as a server computer, a desktop computer, a handheld computer, a tablet computer, mobile telephone or other mobile device, and the like. The components of the host device 70 may include, but are not limited to, a controller 104, a system memory 106, and a bus 108 that couples various system components including the system memory 106 to the controller 104.


The controller 104 may include one or more controllers or processors that execute instructions stored in the system memory 106. The controller 104 may include a programmable microprocessor. Such a programmable microprocessor may allow a user to modify the control logic of the host device 70 even after it is installed in the field (e.g., firmware update, application update). When provided, the bus 108 may represent one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.


The system memory 106 of the host device 70 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 112 and/or cache memory 114. The host device 70 may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, the storage system 116 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM or other optical media can be provided. In such instances, each can be connected to the bus 108 by one or more data media interfaces. As will be further depicted and described below, the system memory 106 may include at least one program/utility 118 having a set of program modules that are configured to receive an input from an infection risk determination system and control (or send control commands) to at least a portion of the BMS to mitigate an elevated infection risk.


In one example, the program/utility 118 may be stored in the system memory 106 and may include one or more application program modules (e.g., software), such as fault detection and diagnostics (FDD) module 120 and/or infection risk mitigation module 122. In some cases, the program/utility 118 may include additional program modules as well as an operating system, one or more other application program modules, and program data. The FDD module 120 and/or infection risk mitigation module 122 may execute on the host device 70. In some cases, the FDD module 120 and/or infection risk mitigation module 122 may execute on one or many of the building system controllers 102. In some cases, part of the FDD module 120 and/or infection risk mitigation module 122 is executed on the host device 70 and part of the FDD module 120 and/or infection risk mitigation module 122 is executed on the building system controllers 102. In any scenario, the building system controllers 102 may be connected to the host device 70 through any type of connection such as a network (e.g., network 150), including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In various embodiments, the host device 70 may communicate with one or more devices from the various systems of the building system controllers 102 over the network 150. Such communication can occur via Input/Output (I/O) interface(s) 124. In some cases, the controller 104 of the host device 70 may be operatively coupled to I/O interface(s) 124 via the bus 108, and may use the I/O interface 124 to communicate with devices via the building system controllers 102.



FIG. 3 is a schematic block diagram of an illustrative infection risk reduction system that uses a building management system (BMS) 234. While the BMS 234 is described with respect to a medical facility, it is contemplated that the BMS may service another type of building, such as, but not limited to those described above with respect to FIG. 1. In the example shown, the medical facility may include a plurality of rooms 202 with at least one room of the plurality of rooms including a plurality of sensors. In some cases, more than one room may be provided, each with a plurality of sensors. For example, if a medical facility has three operating rooms, each operating room may have one or more sensors configured to monitor the conditions in the room in which they are located. It is contemplated that other room types may have sensors as well, such an intensive care unit (ICU), patient recovery rooms, etc. Further, different types of sensors or sensor combinations may be provided within the rooms depending on the type of room, the procedures performed in the room, patient privacy expectations in the room, etc. The sensors may include, but are not limited to biohazard detection sensors 204, multimodal sensors 206, and/or active pressure monitors (APM) 207. Some illustrative biohazard detection sensors 204 may include, but are not limited, to carbon monoxide (CO) and/or carbon dioxide (CO2) sensors 208, NOx (oxides of nitrogen) sensors 210, volatile organic chemical (VOC) sensors 212 (e.g., formaldehyde sensors), mold detectors 214, particulate matter (PM) sensors 216, etc. Some illustrative multimodal sensors 206 may include, but are not limited to, temperature sensors 218, humidity sensors 220, passive infrared (PIR) sensors 222, illuminance sensors 224, noise sensors 226, cameras 228, etc. Other sensors may include limit switches and door sensors.


The room(s) 202 and/or sensors 204, 206, 207 may be in communication with an elevated risk determination system 230 over one or more networks 250, such as a local area network (LAN) and/or a wide area network or global network (WAN) including, for example, the Internet. In some embodiments, some portions of the infection risk reduction system 200 may be in communication over a LAN while other portions of the infection risk reduction system 200 may communicate over a WAN. Some portions of the infection risk reduction system 200 may be configured to communicate over both a LAN and a WAN. The elevated risk determination system 230 may include a controller 232 configured to receive data from the one or more sensors 204, 206, 207 and determine if conditions are present that are indicative of an increased likelihood (e.g., an increased risk or chance) that a patient in the room(s) 202 will acquire an infection. The elevated risk determination system 230 may be configured to transmit an alert, such as, but not limited to an elevated infection risk for a particular room in the medical facility to the BMS 234. In some cases, the elevated infection risk alert may be a binary alert, such as a flag that is raised when the risk of infection crosses a threshold. In other cases, the elevated infection risk alert may present the risk along a scale of risk, from low to high. In some cases, the elevated infection risk alert may include additional information such as what sensed conditions caused or formed the basis of the elevated infection risk alert. It is contemplated that the location of the sensor 204, 206, 207 that triggered the alert may be included in and/or accessible from the sensor database 242 of the building management system 234.


The controller 232 may include at least a processor and a memory for storing information, such as, but not limited to risk analysis rules, sensor location information, set points, diagnostic limits, medical procedure information, surgical tool location, etc. The memory may be any suitable type of storage device including, but not limited to, RAM, ROM, EPROM, flash memory, a hard drive, and/or the like. In some cases, the processor may store information within the memory and may subsequently retrieve the stored information from the memory. The controller 232 may further include an input/output block (I/O block) for receiving one or more signals from the sensors 204, 206, 207 and/or for communicating with the building management system 234. The I/O block may be wired and/or wireless.


In some embodiments, the elevated risk determination system 230 may include a user interface 236 that permits the elevated risk determination system 230 to display and/or solicit information, as well as accept one or more user interactions. In one example, the user interface 236 may be a physical user interface that is accessible at the elevated risk determination system 230, and may include a display and/or a distinct keypad. The display may be any suitable display. In some instances, a display may include or may be a liquid crystal display (LCD), and in some cases an e-ink display, fixed segment display, or a dot matrix LCD display. In other cases, the user interface 236 may be a touch screen LCD panel that functions as both display and keypad. The touch screen LCD panel may be adapted to solicit values for a number of operating parameters and/or to receive such values, but this is not required. In still other cases, the user interface 236 may be a dynamic graphical user interface.


In some instances, the user interface 236 need not be physically accessible to a user at the elevated risk determination system 230. Instead, the user interface 236 may be a virtual user interface 236 that is accessible via the network 250 using a mobile wireless device 248 such as a smart phone, tablet, e-reader, laptop computer, personal computer, key fob, or the like. In some cases, the virtual user interface 236 may be provided by an app or apps executed by a user's remote device for the purposes of remotely interacting with the elevated risk determination system 230 controller 232.


The room(s) 202 and/or sensors 204, 206, 207 may be in communication with the building management system 234 over the one or more networks 250. The building management system 234 may include a controller 238 configured to receive data from the one or more sensors 204, 206, 207. The illustrative building management system 234 includes a controller 238. In some embodiments, the controller 238 may be a host controller, such as the host device 70 described with respect to FIGS. 1 and 2. In other embodiments, the controller 238 may be a system controller, such as any of the system controllers described herein. For example, the controller 238 may include at least a processor and a memory for storing information, such as, but not limited to rules, set points, diagnostic limits, medical procedure information, compliance parameters, clinical parameters, etc.


The memory may be any suitable type of storage device including, but not limited to, RAM, ROM, EPROM, flash memory, a hard drive, and/or the like. In some cases, the processor may store information within the memory and may subsequently retrieve the stored information from the memory. The controller 238 may further include an input/output block (I/O block) for receiving one or more signals from the sensors 204, 206, 207 and/or the elevated risk determination system 230. The I/O block may be configured to receive wired or wireless signals. It is further contemplated that the controller 238 may further include a control port for providing control commands to one or more building components of the building management system 234. In some cases, the control commands may be in response to receiving the elevated infection risk alert for a particular room and may be tailored to help mitigate the elevated infection risk in that particular room. The one or more control commands may control the building management system in accordance with one or more programmable infection risk compliance parameters for the particular room, as will be described in more detail herein.


In some embodiments, the building management system 234 may include a user interface 240 that permits the building management system 234 to display and/or solicit information, as well as accept one or more user interactions. In one example, the user interface 240 may be a physical user interface that is accessible at the building management system 234, and may include a display and/or a distinct keypad. The display may be any suitable display. In some instances, a display may include or may be a liquid crystal display (LCD), and in some cases an e-ink display, fixed segment display, or a dot matrix LCD display. In other cases, the user interface 240 may be a touch screen LCD panel that functions as both display and keypad. The touch screen LCD panel may be adapted to solicit values for a number of operating parameters and/or to receive such values, but this is not required. In still other cases, the user interface 240 may be a dynamic graphical user interface.


In some instances, the user interface 240 need not be physically accessible to a user at the building management system 234. Instead, the user interface 240 may be a virtual user interface 240 that is accessible via the network 250 using a mobile wireless device such as a smart phone, tablet, e-reader, laptop computer, personal computer, key fob, or the like. In some cases, the virtual user interface 240 may be provided by an app or apps executed by a user's remote device for the purposes of remotely interacting with the building management system 234 controller 238.


The building management system 234 may maintain a first, or sensor, database 242 of data obtained from the one or more sensors 204, 206, 207. For example, a memory accessible by the processor of the controller 238 may be configured to store the database 242 of sensor data such that historical and current sensor data is readily accessible. In some cases, the building management system 234 may only have access to the multimodal sensors 206 and thus the database 242 of sensor data may only store data for these sensors. The building management system(s) 234 may maintain a second, or rules, database 244 that includes a set of rules or algorithms that may be used to identify actions that should be taken to lower a patient's risk of infection. In some cases, the rules database 244 may also include one or more programmable infection risk compliance parameters. In some cases, the rules or algorithms may be used to control the building management system 234 in accordance with one or more programmable risk compliance parameters for a particular room to help mitigate the elevated infection risk in the particular room. A set of rules may include at least one rule, two or more rules, three or more rules, etc. The elevated infection risk alert may be received from the elevated risk determination system 230 and is based on the detected conditions (e.g., from the sensors 204, 206, 207) in a particular room. The set of rules may determine what action to take to reduce the elevated infection risk, sometimes in accordance with the one or more programmable risk compliance parameters for the particular room. A memory accessible by the processor of the controller 238 may be configured to store the rules database 242 and/or the one or more programmable risk compliance parameters for each room, such that the rules and algorithms are readily accessible.


The rules database 244 may be downloaded onto the controller 238 of the building management system 234 from an external server(s) 246 over a network 250, although this is not required. The network 250 may be a wide area network or global network (WAN), such as the internet. The external server(s) 246 may be a suite of hardware and software which may sometimes be referred to as “the cloud.” In some cases, the communication may pass through an intermediary server or cloud network, but this is not required. In some cases, the cloud may provide the ability for communication amongst the building management system 234, the elevated risk determination system 230, the external server(s) 246, and/or one or more remote devices 248. While the external server(s) 246 is illustrated as connected to a building management system 234, the external server(s) 246 may be connected to a plurality of building management systems. The external server(s) 246 may collect and store sensor data 254 from the various sensors 204, 206, 207 from the one or more connected building management systems 234. The external server(s) 246 may include a controller 252 configured to analyze the sensor data and determine if the rules stored in a network rules database 256 need to be or could be improved by updating the rules from time to time.


Returning to the elevated risk determination system 230, the data from the sensors 204, 206, 207 may be analyzed for conditions that increase a risk of infection to a patient. Some conditions that may increase a risk of infection include, but are not limited to, a high particulate count, a high humidity level, a low humidity level, a high room temperature, high traffic into, out of, and/or within the room, high biological particle levels, low air changes per hour (ACH), low air velocity, high air velocity, high mold conditions, etc. These are just some examples of conditions which may impact a risk of infection. While the terms “high” and “low” are relative terms, it should be understood that as used herein, high is to be interpreted as exceeding or above a predetermined threshold while low is to be interpreted as under or below a predetermined threshold. The predetermined threshold may be user defined, defined by one or more programmable risk compliance parameters, or a combination thereof.


When the elevated risk determination system 230 detects a condition that is indicative of an elevated risk of infection in a particular room 202 of the one or more rooms, the elevated risk determination system 230 transmits an alert or signal to the building management system 234. In some cases, the elevated infection risk alert may include additional information such as what sensed conditions caused or formed the basis of the elevated infection risk alert. In response, the controller 238 of the building management system 234 may apply appropriate rules in the rules database 244, and the applied rules may inform the controller 238 how to control the building management system 234 in that particular room. This may include changing one or more control parameters of the building management system 234 as dictated by the one or more rules that correspond to elevated infection risk alert. It is contemplated that a change in the control of the building management system 234 or change in control parameter of the building management system 234 may vary depending on the particular room that resulted in the elevated infection risk alert (e.g., an operating room, a general patient room, a waiting room, etc.), a condition of a patient or patients in the particular room, (e.g., respiration issues, germ shedding, open wound, broken bone, etc.) a degree of severity of the elevated infection risk alert if provided, etc. These are just some examples of factors that may be considered by the rules when defining an action to take in response to an elevated infection risk alert. It is contemplated that some scenarios may require a more conservative control or change to the building management system 234 while other conditions may require more severe changes in the control of the building management system 234.


In some cases, the processing of the sensor data may be performed in the cloud or remote from the controller 232 of the elevated risk determination system 230, although this is not required. In some embodiments, an elevated infection risk alert may be sent to a remote device 248 by the elevated risk determination system 230. The remote device 248 may be any internet connected device including a smart phone, tablet, e-reader, laptop computer, personal computer, etc. The notification may be received by an application program code (app) or other module 260 within the remote device 248. Once the notification has been received at the notification module 260, the notification may be displayed on the user interface 2586 of the device 248. In some cases, an audio alert (e.g., a beep or chime) or a haptic alert (e.g., a vibration) may accompany the notification.


It is contemplated that the rules database 244 may be tailored to the particular rooms within the building. For example, the rules database 244 may include a plurality of rules established for a particular type of room based on a risk of infection in the type of rooms. For example, operating rooms, where there may be a lot of people coming and going as well open pathways to the body, may have more strict rules dictating tighter control of the environment than a patient room where a patient is recovering from a surgery. The appropriate set of rules may be downloaded to the controller 238 in response to a user identifying the details of the rooms 202, sometimes including available sensors 204, 206, 207 in the rooms, to the controller 238. The user may enter room details at the user interface of the controller 238, through a remote device, or through a web client, as described above. It is contemplated that the sensors 204, 206, 207 may be named or identified such that they are associated with a particular room in the building.



FIG. 4 is a flow chart 300 of an illustrative method for controlling a building management system 234. To begin, infection risk compliance parameters may be received at the building management system 234 and stored in the rules database 244, as shown at block 302. Each hospital may want to define their own infection risk compliance parameters for the various rooms in their facility, based on their own compliance criteria. That is, the infection risk compliance parameters may be tailored to each hospital, and then to different room(s) in the hospital. Then, when the rules are applied, which may take into account the infection risk compliance parameters, the building management system 234 may respond differently in different hospitals.


It is contemplated that the infection risk compliance parameters may be manually entered by a user (e.g., an installer or the medical facility) at the controller 238 (or a remote device 248) or the user may use the controller 238 (or a remote device 248) to send a request to the external server(s) 246 to obtain the rules database, as shown at block 302. Alternatively, or additionally, the controller 238 may automatically request the rules database from the external server(s) 246. Alternatively, or additionally, the controller 238 may be configured to automatically request the most up-to-date rules from the external server(s) 246 at predetermined time schedules. It is further contemplated that additionally, or alternatively, the external server(s) 246 may be configured to automatically send or push revised rules to the controller 238 as the rules are updated.


The infection risk compliance parameters may be stored in the rules database 244 of the building management system 234, as shown at block 304. The infection risk compliance parameters may define, at least in part, how the building management system 234 responds to an elevated infection risk alert from the elevated risk determination system 230. The infection risk compliance parameters, which may be references by the rules, may help dictate how the building management system 234 responds based on the particular elevated infection risk alert, the cause of the elevated infection risk alert, the particular room or room type (e.g., operating room, recovery room, patient room, intensive care unit room, etc.) to which the elevated infection risk alert applies, etc. It is contemplated that the controller 238 may receive infection risk compliance parameters for each of the different room types such that the building management system 234 may be controlled in accordance with the room type when an elevated infection risk occurs in the particular room. In some embodiments, the infection risk compliance parameters may be specific to a particular patient or type of patient. For example, if a high-infection-risk patient is present in a room (e.g. open wound, weak immune system, etc.), a user may input this information to the controller 238, and the rules may cause the controller 238 to control the environment in that room differently than if a low-infection-risk patient (e.g. dehydrated) were in the room.


Referring briefly to FIG. 5, which illustrates an example rules database 400. The rules database 400 illustrated in FIG. 5 is not intended to provide a complete listing of the events which may result in a recommended action or control change in the building management system 234. Instead, the rules database 400 is provided as an example of some illustrative rules that may be created for reducing a patient's risk of infection. Each rule 420a, 420b, 420c, 420d, 420e, 420f (collectively, 420) is shown in a separate row and may include a room type 402, a reason for the elevated infection risk alert 404, one or more actions 406, 408, 410 that may be taken by the building management system 234 to help mitigate the risk, a patient type 412, an alert severity 414, and/or an occupancy of the room 416. The rules 420 may take into consideration compliance parameters (e.g., default values, customized by a hospital, etc.).


In a first example rule 420a, if an elevated particle count is detected, the air changes per hour (ACH) may be increased. In another example rule 420b, if an elevated biological particle count is detected the ACH may be increased and an ultraviolet (UV) light activated to kill the biological particles. In some instances, the UV light may be positioned within an air duct or other portion of the air handling system, although this is not required. In another example rule 420c, if there is elevated traffic in a room (e.g., more people than expected and/or doors opening more than expected) the ACH may be increased and a UV light activated to kill the biological particles. In yet another example rule 420d, if elevated humidity is detected, the ACH may be increased and a dehumidifier activated. In yet another example rule 420e, if the patient condition is indicative of a higher risk for infection, the ACH may be increased, a UV light activated, and the humidity increased. In another example rule 420f, if conditions are indicative of an elevated risk of mold, the ACH may be increased, a dehumidifier activated, and the temperature of the room decreased. In some cases, the ACH may be increased to increase the volume of air, to maintain directional air, and/or to maintain a cleanliness of the air. These are just some examples and are not intended to be limiting.


The action(s) 406, 408, 410 may be specific to the reason for the alert, the room type, the alert severity, and/or the patient type. For example, in some cases, only one action is taken by the building management system 234 while in other cases, multiple actions are taken by the building management system 234. In some embodiments, the action 406, 408, 410 may include automatically adjusting a control parameter of the building management system 234. In other embodiments, a user may be required to approve the control change prior to the controller 238 adjusting the control parameter of the building management system 234. Alternatively, or additionally, a user may be required to verify a condition before a control change is implemented. For example, a user may be required to verify that increase ventilation to a room will not adversely affect the indoor air quality (for example, by bringing in dust from a construction project).


Returning to FIG. 4, the controller 238 of the building management system 234 may be configured to receive an elevated infection risk from the elevated risk determination system 230, as shown at block 306. As described above, the elevated risk determination system 230 monitors the sensor data from each room 202 equipped with sensors 204, 206, 207. When the elevated risk determination system 230 determines a condition in a particular room is consistent with an elevated infection risk, the elevated risk determination system 230 may issue or send an elevated infection risk alert to the building management system 234. In some cases, the elevated infection risk alert may be a binary alert, such as a flag that is raised when the risk of infection crosses a threshold. In other cases, the elevated infection risk alert may present the risk along a scale of risk, from low to high. In some cases, the elevated infection risk alert may include additional information such as what sensed conditions caused or formed the basis of the elevated infection risk alert.


In some instances, the elevated infection risk is then mitigated or addressed by controlling the building management system 234 in accordance with the action(s) 406, 408, 410 defined by rule. The rules may reference one or more infection risk compliance parameters, as shown at block 308. In some cases, the elevated risk determination system 230 may take into account the room type, room location, severity of the alert, and/or other condition or parameter before issuing the elevated infection risk alert. In other cases, the elevated risk determination system 230 may issue an elevated infection risk alert for a particular room, and in response, the controller 238 of the building management system 234 may apply appropriate rules in the rules database 244, along with one or more infection risk compliance parameters, to determine how the controller 238 controls the building management system 234 in that particular room. It is contemplated that the action taken may vary based on a combination of the room type, room location, a severity of the alert, and/or a reason for the alert. In some embodiments, the elevated infection risk alert may cause the controller 238 of the building management system 234 to alert a maintenance crew of required maintenance in or near the particular room which resulted in the elevated infection risk alert. For example, dirty air filters may be detected by an air particle count above a threshold value. In some embodiments, the elevated infection risk alert may cause controller 238 of the building management system 234 to alert a cleaning crew to clean a particular room to help reduce the elevated infection risk alert. For example, images from security cameras can be processed to determine if a particular room has been wiped down by a cleaning crew. Elevated infection risk alerts may be generated if the cleaning is not performed in compliance with cleaning rules. It is contemplated that there may be different cleaning rules for different room types (e.g., operating room, intensive care unit room, recovery room, patient room). It is further contemplated that the clean rules may vary over time for a particular room in accordance with factors that change over time (e.g., occupied, unoccupied, infection risk factors, etc.). In another example, when a low-infection-risk patient is moved out of a room and a high-infection-risk patient in moved into the room, an elevated infection risk alert from the elevated risk determination system 230 may cause the controller 238 of the building management system 234 to control the environment differently and may even schedule an extra cleaning beyond the normal cleaning schedule.


In some embodiments, the building management system 234 may be configured to adjust parameters in other rooms, spaces, and/or corridors to proactively prevent a similar increased risk that has been detected in a particular room. For example, rooms, spaces, and/or corridors adjoining a particular room that has been identified as having conditions consistent with an increased risk of infection may have control parameters manipulated prior to the conditions in said room, space, and/or corridor deteriorating to a level in which an increased risk of infection is identified.



FIG. 6 illustrates a first dedicated space 500 in which the conditions may be manipulated to reduce the risk of infection. In the illustrated embodiment, the dedicated space 500 may be an operating room or suite. The operating room 500 may include equipment for performing the procedure, such as, but not limited to, an operating table 502, a back table 506, a case cart 504, an anesthesia machine and equipment stack 508, etc. The operating room 500 may further include a plurality of sensors similar in form and function to the sensors 204, 206, 207 described above. The location, arrangement, and number of sensors can vary depending on the application, size of the room, etc. For example, the operating room 500 may include a plurality of velocity sensors 510 positioned about or around the operating table 502. In some cases, the velocity sensors 510 may be positioned between air handling vents 512 (e.g., air inputs, air returns, and/or air recirculating vents). As described above, the air velocity may be manipulated (e.g., increased or decreased) to reduce a patient's risk of infection based on the measure of air velocity at sensors 510. In some embodiments, the operating room 500 may include particle counters 514. It is contemplated that the particle counters 514 may be positioned at or near the air handling vents 512, although this is not required. It is contemplated that a high particle count may indicate a need to replace a filter, increase an air changeover rate, decrease an air changeover rate, etc. In some embodiments, the operating room 500 may include additional air quality sensors, such as, but not limited to total volatile organic compound (TVOC) samplers 516 and/or gas sensors 518.


The operating room 500 may further include one or more environment sensors 520. The environmental sensor(s) may include, but are not limited to temperature sensors, humidity sensors, dew point sensors, air density sensors, etc. In some embodiments, the operating room 500 may further include one or more context or image sensors 522 (which may or may not be high definition). The context sensors 522 can include, but are not limited to monitoring activity (e.g., people entering and/or exiting a room, washing hands, following protocols, etc.), monitoring the location of the occupants of the operating room 500, monitoring the posture of the occupants, monitoring gestures performed by the occupants, monitoring the attire of the occupants, etc.


The data from the sensors 510, 512, 514, 516, 518, 520, 522 may be recorded and analyzed at, for example, a processing unit (not explicitly shown) which may be a building management controller or a separate processing device. The processing unit may issue building control commands based on the sensor data. In some cases, the processing unit may identify a risk of infection (e.g., SSI and/or HAI) based on the sensor data. The processing unit may then adjust a building control parameter (e.g., transmit a change in control parameter to a particular device of the building management system) to mitigate or reduce the risk of infection. Alternatively, or additionally, the processing unit may transmit a recommending to be viewed and/or approved by an appropriate staff member prior to implementing the change. It is contemplated that sensor data may be trended, monitored, displayed, and/or analyzed in real time and viewable on display in the operating room 500 or a location exterior to the room 500. In some cases, the processing unit may be configured to generate compliance reports and/or HAI/SSI risk reports (automatically or in response to user input).



FIG. 7 illustrates another dedicated space 600 in which the conditions may be manipulated to reduce the risk of infection. In the illustrated embodiment, the dedicated space 600 may be a patient room which may include intensive care unit patient rooms and/or other specialized patient rooms. The patient room 600 may include equipment and/or furniture for patient care and/or comfort, such as, but not limited to, a patient bed 602, a toilet room 604, etc. The patient room 600 may further include a plurality of sensors similar in form and function to the sensors 204, 206, 207 described above. The location, arrangement, and number of sensors can vary depending on the application, size of the room, etc. For example, the patient room 600 may include a plurality of velocity sensors 606 positioned about or around the patient bed 602, doors 608, etc. In some cases, the velocity sensors 606 may be positioned between air handling vents 608 (e.g., air inputs, air returns, and/or air recirculating vents). As described above, the air velocity may be manipulated (e.g., increased or decreased) to reduce a patient's risk of infection based on the measured air velocity at sensors 606. In some embodiments, the patient room 600 may include particle counters 610. It is contemplated that the particle counters 610 may be positioned at or near the air handling vents 608, although this is not required. It is contemplated that a high particle count may indicate a need to replace a filter, increase an air changeover rate, decrease an air changeover rate, etc. In some embodiments, the patient room 600 may include additional air quality sensors, such as, but not limited to total volatile organic compound (TVOC) samplers 612 and/or gas sensors 614. While not explicitly shown, the toilet room 604 may include an exhaust system which may be a constant volume exhaust or a variable (e.g., controllable) exhaust.


The patient room 600 may further include one or more environment sensors 616. The environmental sensor(s) may include, but are not limited to temperature sensors, humidity sensors, dew point sensors, air density sensors, etc. In some embodiments, the patient room 600 may further include one or more context or image sensors 618 (which may or may not be high definition). The context sensors 618 can include, but are not limited to monitoring activity (e.g., people entering and/or exiting a room, washing hands, following protocols, etc.), monitoring the location of the occupants of the patient room 600, monitoring the posture of the occupants, monitoring gestures performed by the occupants, monitoring the attire of the occupants, etc.


The data from the sensors 606, 610, 612, 614, 616, 618, may be recorded and analyzed at, for example, a processing unit (not explicitly shown) which may be a building management controller or a separate processing device. The processing unit may issue building control commands based on the sensor data. In some cases, the processing unit may identify a risk of infection (e.g., SSI and/or HAI) based on the sensor data. The processing unit may then adjust a building control parameter (e.g., transmit a change in control parameter to a particular device of the building management system) to mitigate or reduce the risk of infection. Alternatively, or additionally, the processing unit may transmit a recommending to be viewed and/or approved by an appropriate staff member prior to implementing the change. It is contemplated that sensor data may be trended, monitored, displayed, and/or analyzed in real time and viewable on display in the patient room 600 or a location exterior to the room 600. In some cases, the processing unit may be configured to generate compliance reports and/or HAI/SSI risk reports (automatically or in response to user input).



FIG. 8 illustrates another dedicated space 700 in which the conditions may be manipulated to reduce the risk of infection. In the illustrated embodiment, the dedicated space 700 may be a general use space, such as, but not limited a patient examination room. The general use space 700 may include equipment and/or furniture for patient care and/or comfort, such as, but not limited to, an examination table 702, a sink 704, one or more chairs 706, etc. The general use space 700 may further include a plurality of sensors similar in form and function to the sensors 204, 206, 207 described above. The location, arrangement, and number of sensors can vary depending on the application, size of the room, etc. For example, the general use space 700 may include a plurality of velocity sensors 708 positioned about or around the examination table 702, doors (not explicitly shown), etc. In some cases, the velocity sensors 708 may be positioned between air handling vents 710 (e.g., air inputs, air returns, and/or air recirculating vents). As described above, the air velocity may be manipulated (e.g., increased or decreased) to reduce a patient's risk of infection based on the measured air velocity at sensors 708. In some embodiments, the general use space 700 may include particle counters 712. It is contemplated that the particle counters 712 may be positioned at or near the air handling vents 710, although this is not required. It is contemplated that a high particle count may indicate a need to replace a filter, increase an air changeover rate, decrease an air changeover rate, etc. In some embodiments, the general use space 700 may include additional air quality sensors, such as, but not limited to total volatile organic compound (TVOC) samplers 714 and/or gas sensors (not explicitly shown).


The general use space 700 may further include one or more environment sensors 716. The environmental sensor(s) may include, but are not limited to temperature sensors, humidity sensors, dew point sensors, air density sensors, etc. In some embodiments, the general use space 700 may further include one or more context or image sensors 718 (which may or may not be high definition). The context sensors 718 can include, but are not limited to monitoring activity (e.g., people entering and/or exiting a room, washing hands, following protocols, etc.), monitoring the location of the occupants of the general use space 700, monitoring the posture of the occupants, monitoring gestures performed by the occupants, monitoring the attire of the occupants, etc.


The data from the sensors 708, 712, 714, 614, 716, 718, may be recorded and analyzed at, for example, a processing unit (not explicitly shown) which may be a building management controller or a separate processing device. The processing unit may issue building control commands based on the sensor data. In some cases, the processing unit may identify a risk of infection (e.g., SSI and/or HAI) based on the sensor data. The processing unit may then adjust a building control parameter (e.g., transmit a change in control parameter to a particular device of the building management system) to mitigate or reduce the risk of infection. Alternatively, or additionally, the processing unit may transmit a recommending to be viewed and/or approved by an appropriate staff member prior to implementing the change. It is contemplated that sensor data may be trended, monitored, displayed, and/or analyzed in real time and viewable on display in the general use space 700 or a location exterior to the space 700. In some cases, the processing unit may be configured to generate compliance reports and/or HAI/SSI risk reports (automatically or in response to user input).


Those skilled in the art will recognize that the present disclosure may be manifested in a variety of forms other than the specific embodiments described and contemplated herein. Accordingly, departure in form and detail may be made without departing from the scope and spirit of the present disclosure as described in the appended claims.

Claims
  • 1. A building management system (BMS) for a facility that includes a plurality of regions, the building management system comprising: a plurality of sensors for sensing one or more parameters associated with an infection risk in the plurality of regions of the facility;an elevated infection risk determination system operatively coupled to the plurality of sensors, the elevated infection risk determination system configured to monitor for an elevated infection risk in each of the plurality of regions of the facility based at least in part on the one or more parameters sensed by the plurality of sensors;a control port for providing control commands to one or more building components of the building management system;a controller operatively coupled to the elevated infection risk determination system and the control port, the controller configured to: provide one or more control commands via the control port to one or more components of the building management system associated with a first region of the plurality of regions of the facility in response to the elevated infection risk determination system identifying an elevated infection risk associated with the first region of the facility to help mitigate the elevated infection risk associated with the first region of the facility; andprovide one or more control commands via the control port to one or more components of the building management system associated with a second region of the plurality of regions of the facility in response to the elevated infection risk determination system identifying an elevated infection risk associated with the second region of the facility to help mitigate the elevated infection risk associated with the second region of the facility.
  • 2. The building management system (BMS) of claim 1, wherein the elevated infection risk determination system is configured to monitor an elevated infection risk in each of the one or more of the plurality of regions of the facility by predicting the elevated infection risk in each of the one or more of the plurality of regions of the facility prior to the elevated infection risk actually occurring in the corresponding region of the facility.
  • 3. The building management system (BMS) of claim 2, wherein the controller is configured to provide control commands to proactively control one or more components of the building management system associated with the first region to help proactively mitigate a predicted elevated infection risk in the first region.
  • 4. The building management system (BMS) of claim 3, wherein the controller is configured to provide control commands to proactively control one or more components of the building management system associated with the second region to help proactively mitigate a predicted elevated infection risk in the second region.
  • 5. The building management system (BMS) of claim 1, wherein the plurality of regions correspond to a plurality of zones of the facility.
  • 6. The building management system (BMS) of claim 1, wherein the plurality of regions correspond to a plurality of rooms of the facility.
  • 7. The building management system (BMS) of claim 1, wherein the elevated infection risk includes a degree of severity of the elevated infection risk.
  • 8. The building management system (BMS) of claim 7, wherein the controller is configured to provide one or more control commands via the control port that control one or more components of the building management system associated with the first region that are based on the degree of severity of the elevated infection risk associated with the first region of the facility.
  • 9. The building management system (BMS) of claim 7, wherein the controller is configured to provide control commands via the control port that control one or more components of the building management system associated with the second region that are based on the degree of severity of the elevated infection risk associated with the second region of the facility.
  • 10. The building management system (BMS) of claim 1, wherein the elevated infection risk includes an indication of a cause of the elevated infection risk.
  • 11. The building management system (BMS) of claim 10, wherein the controller is configured to provide control commands via the control port that control one or more components of the building management system associated with the first region that are based on the cause of the elevated infection risk associated with the first region of the facility.
  • 12. The building management system (BMS) of claim 10, wherein the controller is configured to provide control commands via the control port that control one or more components of the building management system associated with the second region that are based on the cause of the elevated infection risk associated with the second region of the facility.
  • 13. The building management system (BMS) of claim 1, wherein the plurality of sensors comprise one or more of a temperature sensor, a humidity sensor, a pressure sensor, biohazard sensor and a video camera.
  • 14. A method for controlling a building management system of a facility, the building management system including a heating, ventilation, and/or air conditioning (HVAC) system, wherein the facility includes a plurality of regions serviced by the HVAC system, the method comprising: monitoring for an elevated infection risk in each of the plurality of regions of the facility based at least in part on one or more parameters sensed by a plurality of sensors of the building management system;providing one or more first control commands to the HVAC system in response to identifying an elevated infection risk in a first region of the plurality of regions of the facility, the one or more first control commands are configured to help mitigate the elevated infection risk associated with the first region of the facility; andproviding one or more second control commands to the HVAC system in response to identifying an elevated infection risk in a second region of the plurality of regions of the facility, the one or more second control commands are configured to help mitigate the elevated infection risk associated with the second region of the facility.
  • 15. The method of claim 14, wherein the HVAC system comprises one or more first HVAC components servicing the first region and one or more second HVAC components servicing the second region, and wherein: one or more of the first control commands are configured to cause one or more of the first HVAC components to help mitigate the elevated infection risk associated with the first region of the facility; andone or more of the second control commands are configured to cause one or more of the second HVAC components to help mitigate the elevated infection risk associated with the second region of the facility.
  • 16. The method of claim 14, wherein monitoring for the elevated infection risk includes predicting the elevated infection risk prior to the elevated infection risk actually occurring.
  • 17. The method of claim 16, wherein the one or more first control commands are configured to proactively control at least part of the HVAC system to help mitigate the elevated infection risk associated with the first region of the facility.
  • 18. The method of claim 16, wherein the one or more second control commands are configured to proactively control at least part of the HVAC system to help mitigate the elevated infection risk associated with the second region of the facility.
  • 19. A non-transitory computer readably medium storing instructions thereon that when executed by one or more processors cause the one or more processors to: monitor for an elevated infection risk in each of a plurality of regions of a facility based at least in part on one or more parameters sensed by a plurality of sensors;provide one or more first control commands to a building management system of the facility in response to identifying an elevated infection risk in a first region of the plurality of regions of the facility, wherein the one or more first control commands are configured to help mitigate the elevated infection risk associated with the first region of the facility; andprovide one or more second control commands to the building management system of the facility in response to identifying an elevated infection risk in a second region of the plurality of regions of the facility, wherein the one or more second control commands are configured to help mitigate the elevated infection risk associated with the second region of the facility.
  • 20. The non-transitory computer readably medium of claim 19, wherein identifying the elevated infection risk includes predicting the elevated infection risk prior to the elevated infection risk actually occurring, and wherein: the one or more first control commands are configured to proactively control at least part of the building management system to help mitigate the elevated infection risk associated with the first region of the facility; andthe one or more second control commands are configured to proactively control at least part of the building management system to help mitigate the elevated infection risk associated with the second region of the facility.
Parent Case Info

This is a continuation of co-pending U.S. patent application Ser. No. 17/196,297, filed Mar. 9, 2021, and entitled “METHODS AND SYSTEMS FOR IMPROVING INFECTION CONTROL IN A BUILDING”, which is a continuation of U.S. patent application Ser. No. 16/246,437, filed Jan. 11, 2019, entitled “METHODS AND SYSTEMS FOR IMPROVING INFECTION CONTROL IN A BUILDING”, now U.S. Pat. No. 10,978,199, both of which are incorporated herein by reference.

US Referenced Citations (519)
Number Name Date Kind
191512 Bennett Jun 1877 A
4009647 Howorth Mar 1977 A
4375637 Desjardins Mar 1983 A
4918615 Suzuki et al. Apr 1990 A
4939922 Smalley et al. Jul 1990 A
5566084 Cmar Oct 1996 A
5727579 Chardack Mar 1998 A
5745126 Jain et al. Apr 1998 A
5751916 Kon et al. May 1998 A
5777598 Gowda et al. Jul 1998 A
5973662 Singers et al. Oct 1999 A
5990932 Bee et al. Nov 1999 A
6065842 Fink May 2000 A
6139177 Venkatraman et al. Oct 2000 A
6144993 Fukunaga et al. Nov 2000 A
6157943 Meyer Dec 2000 A
6229429 Horon May 2001 B1
6238337 Kambhatla et al. May 2001 B1
6334211 Kojima et al. Dec 2001 B1
6353853 Gravlin Mar 2002 B1
6369695 Horon Apr 2002 B2
6375038 Daansen et al. Apr 2002 B1
6429868 Dehner et al. Aug 2002 B1
6473084 Phillips et al. Oct 2002 B1
6487457 Hull et al. Nov 2002 B1
6580950 Johnson et al. Jun 2003 B1
6598056 Hull et al. Jul 2003 B1
6619555 Rosen Sep 2003 B2
6704012 Lefave Mar 2004 B1
6720874 Fufidio et al. Apr 2004 B2
6741915 Poth May 2004 B2
6796896 Laiti Sep 2004 B2
6801199 Wallman Oct 2004 B1
6816878 Zimmers et al. Nov 2004 B1
6876951 Skidmore et al. Apr 2005 B2
6882278 Winings et al. Apr 2005 B2
6904385 Budike, Jr. Jun 2005 B1
6907387 Reardon Jun 2005 B1
6911177 Deal Jun 2005 B2
6993403 Dadebo et al. Jan 2006 B1
6993417 Osann, Jr. Jan 2006 B2
7023440 Havekost et al. Apr 2006 B1
7031880 Seem et al. Apr 2006 B1
7062722 Carlin et al. Jun 2006 B1
7110843 Pagnano et al. Sep 2006 B2
7139685 Bascle et al. Nov 2006 B2
7164972 Imhof et al. Jan 2007 B2
7183899 Behnke Feb 2007 B2
7200639 Yoshida Apr 2007 B1
7222111 Budike, Jr. May 2007 B1
7222800 Wruck May 2007 B2
7257397 Shamoon et al. Aug 2007 B2
7280030 Monaco Oct 2007 B1
7292908 Borne et al. Nov 2007 B2
7295116 Kumar et al. Nov 2007 B2
7302313 Sharp et al. Nov 2007 B2
7308323 Kruk et al. Dec 2007 B2
7308388 Beverina et al. Dec 2007 B2
7313447 Hsiung et al. Dec 2007 B2
7346433 Budike, Jr. Mar 2008 B2
7356548 Culp et al. Apr 2008 B1
7379782 Cocco May 2008 B1
7383148 Ahmed Jun 2008 B2
7434742 Mueller et al. Oct 2008 B2
7447333 Masticola et al. Nov 2008 B1
7466224 Ward et al. Dec 2008 B2
7496472 Seem Feb 2009 B2
7512450 Ahmed Mar 2009 B2
7516490 Riordan et al. Apr 2009 B2
7548833 Ahmed Jun 2009 B2
7551092 Henry Jun 2009 B1
7557729 Hubbard et al. Jul 2009 B2
7567844 Thomas et al. Jul 2009 B2
7596473 Hansen et al. Sep 2009 B2
7610910 Ahmed Nov 2009 B2
7626507 Lacasse Dec 2009 B2
7664574 Imhof et al. Feb 2010 B2
7682464 Glenn et al. Mar 2010 B2
7702421 Sullivan et al. Apr 2010 B2
7729882 Seem Jun 2010 B2
7755494 Melker et al. Jul 2010 B2
7761310 Rodgers Jul 2010 B2
7774227 Srivastava Aug 2010 B2
7797188 Srivastava Sep 2010 B2
7819136 Eddy Oct 2010 B1
7822806 Frank et al. Oct 2010 B2
7856370 Katta et al. Dec 2010 B2
7978083 Melker et al. Jul 2011 B2
7984384 Chaudhri et al. Jul 2011 B2
7986323 Kobayashi et al. Jul 2011 B2
8024666 Thompson Sep 2011 B2
8086047 Penke et al. Dec 2011 B2
8099178 Mairs et al. Jan 2012 B2
8151280 Sather et al. Apr 2012 B2
8176095 Murray et al. May 2012 B2
8218871 Angell et al. Jul 2012 B2
8219660 McCoy et al. Jul 2012 B2
8271941 Zhang et al. Sep 2012 B2
8294585 Barnhill Oct 2012 B2
8302020 Louch et al. Oct 2012 B2
8320634 Deutsch Nov 2012 B2
8334422 Gutsol et al. Dec 2012 B2
8344893 Drammeh Jan 2013 B1
8375118 Hao et al. Feb 2013 B2
8473080 Seem et al. Jun 2013 B2
8476590 Stratmann et al. Jul 2013 B2
8516016 Park et al. Aug 2013 B2
8558660 Nix et al. Oct 2013 B2
8639527 Rensvold et al. Jan 2014 B2
8698637 Raichman Apr 2014 B2
8816860 Ophardt et al. Aug 2014 B2
8869027 Louch et al. Oct 2014 B2
8904497 Hsieh Dec 2014 B2
8936944 Peltz et al. Jan 2015 B2
8947437 Garr et al. Feb 2015 B2
8950019 Loberger et al. Feb 2015 B2
9000926 Hollock et al. Apr 2015 B2
9002532 Asmus Apr 2015 B2
9030325 Taneff May 2015 B2
9098738 Bilet et al. Aug 2015 B2
9105071 Fletcher et al. Aug 2015 B2
9175356 Peltz et al. Nov 2015 B2
9235657 Wenzel et al. Jan 2016 B1
9240111 Scott et al. Jan 2016 B2
9256702 Elbsat et al. Feb 2016 B2
9280884 Schultz et al. Mar 2016 B1
9292972 Hailemariam et al. Mar 2016 B2
9311807 Schultz et al. Apr 2016 B2
9320662 Hayes et al. Apr 2016 B2
9322566 Wenzel et al. Apr 2016 B2
9355069 Elbsat et al. May 2016 B2
9370600 Dupuis et al. Jun 2016 B1
9373242 Conrad et al. Jun 2016 B1
9396638 Wildman et al. Jul 2016 B2
9406212 De Luca et al. Aug 2016 B2
9418535 Felch et al. Aug 2016 B1
9418536 Felch et al. Aug 2016 B1
9436179 Turney et al. Sep 2016 B1
9449219 Bilet et al. Sep 2016 B2
9477543 Henley et al. Oct 2016 B2
9497832 Verberkt et al. Nov 2016 B2
9513364 Hall et al. Dec 2016 B2
9526380 Hamilton et al. Dec 2016 B2
9526806 Park et al. Dec 2016 B2
9536415 De Luca et al. Jan 2017 B2
9558648 Douglas Jan 2017 B2
9568204 Asmus et al. Feb 2017 B2
9581985 Walser et al. Feb 2017 B2
9591267 Lipton et al. Mar 2017 B2
9606520 Noboa et al. Mar 2017 B2
9612601 Beyhaghi et al. Apr 2017 B2
9613518 Dunn et al. Apr 2017 B2
9618224 Emmons et al. Apr 2017 B2
9640059 Hyland May 2017 B2
9672360 Barkan Jun 2017 B2
9696054 Asmus Jul 2017 B2
9710700 Bilet et al. Jul 2017 B2
9715242 Pillai et al. Jul 2017 B2
9721452 Felch et al. Aug 2017 B2
9729945 Schultz et al. Aug 2017 B2
9778639 Boettcher et al. Oct 2017 B2
9784464 Yamamoto et al. Oct 2017 B2
9798336 Przybylski Oct 2017 B2
9843743 Lewis et al. Dec 2017 B2
9852481 Turney et al. Dec 2017 B1
9856634 Rodenbeck et al. Jan 2018 B2
9872088 Fadell Jan 2018 B2
9875639 Bone et al. Jan 2018 B2
9911312 Wildman et al. Mar 2018 B2
9940819 Ferniany Apr 2018 B2
9956306 Brais et al. May 2018 B2
9982903 Ridder et al. May 2018 B1
9986175 Frank et al. May 2018 B2
10007259 Turney et al. Jun 2018 B2
10031494 Holaso Jul 2018 B2
10055114 Shah et al. Aug 2018 B2
10071177 Kellogg, Jr. Sep 2018 B1
10087608 Dobizl et al. Oct 2018 B2
10101730 Wenzel et al. Oct 2018 B2
10101731 Asmus et al. Oct 2018 B2
10175681 Wenzel et al. Jan 2019 B2
10222083 Drees et al. Mar 2019 B2
10222767 Holaso et al. Mar 2019 B2
10223894 Raichman Mar 2019 B2
10228837 Hua et al. Mar 2019 B2
10235865 Thyroff Mar 2019 B2
10251610 Parthasarathy et al. Apr 2019 B2
10282796 Elbsat et al. May 2019 B2
10288306 Ridder et al. May 2019 B2
10303843 Bitran et al. May 2019 B2
10317864 Boettcher et al. Jun 2019 B2
10332043 Nair et al. Jun 2019 B2
10332382 Thyroff Jun 2019 B2
10359748 Elbsat et al. Jul 2019 B2
10386820 Wenzel et al. Aug 2019 B2
10402767 Noboa et al. Sep 2019 B2
10514178 Willmott et al. Dec 2019 B2
10514817 Hua et al. Dec 2019 B2
10520210 Park et al. Dec 2019 B2
10544955 Przybylski Jan 2020 B2
10558178 Willmott et al. Feb 2020 B2
10559180 Pourmohammad et al. Feb 2020 B2
10559181 Pourmohammad et al. Feb 2020 B2
10565844 Pourmohammad et al. Feb 2020 B2
10600263 Park et al. Mar 2020 B2
10602474 Goldstein Mar 2020 B2
10605477 Ridder Mar 2020 B2
10607147 Raykov et al. Mar 2020 B2
10619882 Chatterjee et al. Apr 2020 B2
10627124 Walser et al. Apr 2020 B2
10673380 Wenzel et al. Jun 2020 B2
10678227 Przybylski et al. Jun 2020 B2
10706375 Wenzel et al. Jul 2020 B2
10726711 Subramanian et al. Jul 2020 B2
10732584 Elbsat et al. Aug 2020 B2
10767885 Przybylski et al. Sep 2020 B2
10775988 Narain et al. Sep 2020 B2
10796554 Mncent et al. Oct 2020 B2
10809682 Patil et al. Oct 2020 B2
10809705 Przybylski Oct 2020 B2
10824125 Elbsat et al. Nov 2020 B2
10854194 Park et al. Dec 2020 B2
10871298 Ridder et al. Dec 2020 B2
10876754 Wenzel et al. Dec 2020 B2
10890904 Turney et al. Jan 2021 B2
10900686 Willmott et al. Jan 2021 B2
10901446 Nesler et al. Jan 2021 B2
10909642 Elbsat et al. Feb 2021 B2
10915094 Wenzel et al. Feb 2021 B2
10917740 Scott et al. Feb 2021 B1
10921972 Park et al. Feb 2021 B2
10921973 Park et al. Feb 2021 B2
10928790 Mueller et al. Feb 2021 B2
10948884 Beaty et al. Mar 2021 B2
10949777 Elbsat et al. Mar 2021 B2
10955800 Burroughs et al. Mar 2021 B2
10956842 Wenzel et al. Mar 2021 B2
10962945 Park et al. Mar 2021 B2
10969135 Willmott et al. Apr 2021 B2
11002457 Turney et al. May 2021 B2
11009252 Turney et al. May 2021 B2
11010846 Elbsat et al. May 2021 B2
11016648 Fala et al. May 2021 B2
11016998 Park et al. May 2021 B2
11022947 Elbsat et al. Jun 2021 B2
11024292 Park et al. Jun 2021 B2
11036249 Elbsat Jun 2021 B2
11038709 Park et al. Jun 2021 B2
11042139 Deshpande et al. Jun 2021 B2
11042924 Asmus et al. Jun 2021 B2
11061424 Elbsat et al. Jul 2021 B2
11068821 Wenzel et al. Jul 2021 B2
11070389 Schuster et al. Jul 2021 B2
11073976 Park et al. Jul 2021 B2
11080289 Park et al. Aug 2021 B2
11080426 Park et al. Aug 2021 B2
11086276 Wenzel et al. Aug 2021 B2
11094186 Razak Aug 2021 B2
11108587 Park et al. Aug 2021 B2
11113295 Park et al. Sep 2021 B2
11119458 Asp et al. Sep 2021 B2
11120012 Park et al. Sep 2021 B2
11131473 Risbeck et al. Sep 2021 B2
11150617 Ploegert et al. Oct 2021 B2
11151983 Park et al. Oct 2021 B2
11156996 Schuster et al. Oct 2021 B2
11158306 Park et al. Oct 2021 B2
11182047 Nayak et al. Nov 2021 B2
11188093 Ko et al. Nov 2021 B2
11195401 Pourmohammad Dec 2021 B2
11217087 Pelski Jan 2022 B2
11226126 Przybylski et al. Jan 2022 B2
11243523 Llopis et al. Feb 2022 B2
11268715 Park et al. Mar 2022 B2
11268996 Mtullo et al. Mar 2022 B2
11269505 Fala et al. Mar 2022 B2
11272011 Laughton et al. Mar 2022 B1
11272316 Scott et al. Mar 2022 B2
11275348 Park et al. Mar 2022 B2
11275363 Przybylski et al. Mar 2022 B2
11281169 Chatterjee et al. Mar 2022 B2
11288754 Elbsat et al. Mar 2022 B2
11314726 Park et al. Apr 2022 B2
11314788 Park et al. Apr 2022 B2
11334044 Goyal May 2022 B2
11353834 Mueller et al. Jun 2022 B2
11356292 Ploegert et al. Jun 2022 B2
11360451 Pancholi et al. Jun 2022 B2
11361123 Ploegert et al. Jun 2022 B2
20020111698 Graziano et al. Aug 2002 A1
20020130868 Smith Sep 2002 A1
20020175815 Baldwin Nov 2002 A1
20030028269 Spriggs et al. Feb 2003 A1
20030030637 Grinstein et al. Feb 2003 A1
20030046862 Wolf et al. Mar 2003 A1
20030071814 Jou et al. Apr 2003 A1
20030078677 Hull et al. Apr 2003 A1
20030083957 Olefson May 2003 A1
20030103075 Rosselot Jun 2003 A1
20030171851 Brickfield et al. Sep 2003 A1
20030214400 Mizutani et al. Nov 2003 A1
20030233432 Davis et al. Dec 2003 A1
20040001009 Winings et al. Jan 2004 A1
20040064260 Padmanabhan et al. Apr 2004 A1
20040143474 Haeberle et al. Jul 2004 A1
20040153437 Buchan Aug 2004 A1
20040168115 Bauernschmidt et al. Aug 2004 A1
20040233192 Hopper Nov 2004 A1
20040260411 Cannon Dec 2004 A1
20050010460 Mizoguchi et al. Jan 2005 A1
20050119767 Kiwimagi et al. Jun 2005 A1
20050143863 Ruane et al. Jun 2005 A1
20050267900 Ahmed et al. Dec 2005 A1
20060004841 Heikkonen et al. Jan 2006 A1
20060009862 Imhof et al. Jan 2006 A1
20060017547 Buckingham et al. Jan 2006 A1
20060020177 Seo et al. Jan 2006 A1
20060028471 Kincaid et al. Feb 2006 A1
20060029256 Miyoshi et al. Feb 2006 A1
20060058900 Johanson et al. Mar 2006 A1
20060067545 Lewis et al. Mar 2006 A1
20060067546 Lewis et al. Mar 2006 A1
20060077255 Cheng Apr 2006 A1
20060184326 McNally et al. Aug 2006 A1
20060231568 Lynn et al. Oct 2006 A1
20060234621 Desrochers et al. Oct 2006 A1
20060265664 Simons et al. Nov 2006 A1
20060279630 Aggarwal et al. Dec 2006 A1
20070016955 Goldberg et al. Jan 2007 A1
20070055757 Mairs et al. Mar 2007 A1
20070055760 McCoy et al. Mar 2007 A1
20070061046 Mairs et al. Mar 2007 A1
20070067062 Mairs et al. Mar 2007 A1
20070088534 Macarthur et al. Apr 2007 A1
20070090951 Chan et al. Apr 2007 A1
20070091091 Gardiner et al. Apr 2007 A1
20070101433 Louch et al. May 2007 A1
20070114295 Jenkins May 2007 A1
20070120652 Behnke May 2007 A1
20070139208 Kates Jun 2007 A1
20070216682 Navratil et al. Sep 2007 A1
20070219645 Thomas et al. Sep 2007 A1
20070239484 Arond et al. Oct 2007 A1
20070268122 Kow et al. Nov 2007 A1
20080001763 Raja et al. Jan 2008 A1
20080027885 Van Putten et al. Jan 2008 A1
20080036593 Rose-Pehrsson et al. Feb 2008 A1
20080062167 Boggs et al. Mar 2008 A1
20080099045 Glenn et al. May 2008 A1
20080103798 Domenikos et al. May 2008 A1
20080120396 Jayaram et al. May 2008 A1
20080144885 Zucherman et al. Jun 2008 A1
20080183424 Seem Jul 2008 A1
20080194009 Marentis Aug 2008 A1
20080198231 Ozdemir et al. Aug 2008 A1
20080209342 Taylor et al. Aug 2008 A1
20080222565 Taylor et al. Sep 2008 A1
20080224862 Cirker Sep 2008 A1
20080242945 Gugliotti et al. Oct 2008 A1
20080250800 Wetzel Oct 2008 A1
20080279420 Masticola et al. Nov 2008 A1
20080280275 Collopy Nov 2008 A1
20080303658 Melker et al. Dec 2008 A1
20080306985 Murray et al. Dec 2008 A1
20080320552 Kumar et al. Dec 2008 A1
20090001181 Siddaramanna et al. Jan 2009 A1
20090024944 Louch et al. Jan 2009 A1
20090065596 Seem et al. Mar 2009 A1
20090083120 Strichman et al. Mar 2009 A1
20090096791 Abshear et al. Apr 2009 A1
20090125337 Abri May 2009 A1
20090125825 Rye et al. May 2009 A1
20090144023 Seem Jun 2009 A1
20090157744 McConnell Jun 2009 A1
20090160673 Cirker Jun 2009 A1
20090322782 Kimchi et al. Dec 2009 A1
20100048167 Chow et al. Feb 2010 A1
20100058248 Park Mar 2010 A1
20100064001 Daily Mar 2010 A1
20100070089 Harrod et al. Mar 2010 A1
20100073162 Johnson et al. Mar 2010 A1
20100123560 Nix et al. May 2010 A1
20100134296 Hwang Jun 2010 A1
20100156628 Ainsbury et al. Jun 2010 A1
20100156630 Ainsbury Jun 2010 A1
20100188228 Hyland Jul 2010 A1
20100223198 Noureldin et al. Sep 2010 A1
20100249955 Sitton Sep 2010 A1
20100286937 Hedley et al. Nov 2010 A1
20100318200 Foslien et al. Dec 2010 A1
20100324962 Nesler et al. Dec 2010 A1
20110010654 Raymond et al. Jan 2011 A1
20110057799 Taneff Mar 2011 A1
20110077779 Fuller et al. Mar 2011 A1
20110083094 Laycock et al. Apr 2011 A1
20110087988 Ray et al. Apr 2011 A1
20110112854 Koch et al. May 2011 A1
20110126111 Gill et al. May 2011 A1
20110154426 Doser et al. Jun 2011 A1
20110161124 Lappinga et al. Jun 2011 A1
20110169646 Raichman Jul 2011 A1
20110184563 Foslien et al. Jul 2011 A1
20110202467 Hilber et al. Aug 2011 A1
20110273298 Snodgrass et al. Nov 2011 A1
20110291841 Hollock et al. Dec 2011 A1
20110298301 Wong et al. Dec 2011 A1
20110316703 Butler et al. Dec 2011 A1
20110320054 Brzezowski Dec 2011 A1
20120022700 Drees et al. Jan 2012 A1
20120039503 Chen et al. Feb 2012 A1
20120062382 Taneff Mar 2012 A1
20120075464 Derenne et al. Mar 2012 A1
20120109988 Li et al. May 2012 A1
20120112883 Wallace May 2012 A1
20120131217 Delorme et al. May 2012 A1
20120158185 El-Mankabady et al. Jun 2012 A1
20120216243 Gill et al. Aug 2012 A1
20120224057 Gill et al. Sep 2012 A1
20120259466 Ray et al. Oct 2012 A1
20120262472 Garr et al. Oct 2012 A1
20120272146 D'Souza et al. Oct 2012 A1
20120291068 Khushoo et al. Nov 2012 A1
20120303652 Tseng Nov 2012 A1
20120310418 Harrod et al. Dec 2012 A1
20130055132 Foslien Feb 2013 A1
20130060794 Puttabasappa et al. Mar 2013 A1
20130082842 Balazs et al. Apr 2013 A1
20130085609 Barker Apr 2013 A1
20130086152 Hersche et al. Apr 2013 A1
20130091631 Hayes et al. Apr 2013 A1
20130110295 Zheng et al. May 2013 A1
20130135468 Kim et al. May 2013 A1
20130169681 Rasane et al. Jul 2013 A1
20130184880 McMahon Jul 2013 A1
20130187775 Marsden et al. Jul 2013 A1
20130204570 Mendelson et al. Aug 2013 A1
20130229276 Hunter Sep 2013 A1
20130268293 Knudson et al. Oct 2013 A1
20130289774 Day et al. Oct 2013 A1
20130309154 Call et al. Nov 2013 A1
20140032157 Khiani Jan 2014 A1
20140040998 Yi-Chang Feb 2014 A1
20140046490 Foslien et al. Feb 2014 A1
20140046722 Rosenbloom et al. Feb 2014 A1
20140058539 Park Feb 2014 A1
20140167917 Wallace et al. Jun 2014 A2
20140207291 Golden et al. Jul 2014 A1
20140292518 Wildman et al. Oct 2014 A1
20140307076 Deutsch Oct 2014 A1
20140309757 Le Sant et al. Oct 2014 A1
20140316582 Berg-Sonne et al. Oct 2014 A1
20140320289 Raichman Oct 2014 A1
20140342724 Hill et al. Nov 2014 A1
20150025329 Amarasingham Jan 2015 A1
20150032264 Emmons et al. Jan 2015 A1
20150056909 Chien Feb 2015 A1
20150070174 Douglas Mar 2015 A1
20150077258 Nelson et al. Mar 2015 A1
20150113462 Chen et al. Apr 2015 A1
20150153918 Chen et al. Jun 2015 A1
20150161874 Thyroff et al. Jun 2015 A1
20150167995 Fadell et al. Jun 2015 A1
20150168949 Hua et al. Jun 2015 A1
20150194043 Dunn et al. Jul 2015 A1
20150198707 Al-Alusi Jul 2015 A1
20150212717 Nair et al. Jul 2015 A1
20150213222 Amarasingham Jul 2015 A1
20150213379 Nair et al. Jul 2015 A1
20150216369 Hamilton et al. Aug 2015 A1
20150253748 Brun et al. Sep 2015 A1
20150281287 Gill et al. Oct 2015 A1
20160061476 Schultz et al. Mar 2016 A1
20160061477 Schultz et al. Mar 2016 A1
20160061794 Schultz et al. Mar 2016 A1
20160061795 Schultz et al. Mar 2016 A1
20160063833 Schultz et al. Mar 2016 A1
20160066067 Schultz et al. Mar 2016 A1
20160116181 Aultman Apr 2016 A1
20160139067 Grace May 2016 A1
20160223215 Buda et al. Aug 2016 A1
20160253897 Wildman et al. Sep 2016 A1
20160255516 Hill et al. Sep 2016 A1
20160298864 Ekolind et al. Oct 2016 A1
20160306934 Sperry et al. Oct 2016 A1
20160314683 Felch et al. Oct 2016 A1
20160328948 Ferniany Nov 2016 A1
20160335731 Hall Nov 2016 A1
20160367925 Blackley Dec 2016 A1
20170024986 Austin Jan 2017 A1
20170193792 Bermudez Rodriguez et al. Jul 2017 A1
20170256155 Sengstaken, Jr. Sep 2017 A1
20170280949 Wildman et al. Oct 2017 A1
20170294106 Thyroff Oct 2017 A1
20170365024 Koch et al. Dec 2017 A1
20180016773 Chandler et al. Jan 2018 A1
20180151054 Pi May 2018 A1
20180218591 Easter Aug 2018 A1
20180259927 Przybylski et al. Sep 2018 A1
20180293038 Meruva et al. Oct 2018 A1
20180301014 Worral et al. Oct 2018 A1
20180313695 Shim et al. Nov 2018 A1
20180365957 Wright et al. Dec 2018 A1
20190051138 Easter Feb 2019 A1
20190139395 Rogachev et al. May 2019 A1
20190209719 Andersen et al. Jul 2019 A1
20200009280 Kupa et al. Jan 2020 A1
20200074836 Kolavennu et al. Mar 2020 A1
20200090089 Aston Mar 2020 A1
20200146557 Cheung et al. May 2020 A1
20200200420 Nayak et al. Jun 2020 A1
20200348038 Risbeck et al. Nov 2020 A1
20210010701 Nesler et al. Jan 2021 A1
20210011443 Mcnamara et al. Jan 2021 A1
20210011444 Risbeck et al. Jan 2021 A1
20210364181 Risbeck et al. Nov 2021 A1
20210373519 Risbeck et al. Dec 2021 A1
20220011731 Risbeck et al. Jan 2022 A1
20220113045 Gamroth et al. Apr 2022 A1
20220137580 Burroughs et al. May 2022 A1
Foreign Referenced Citations (45)
Number Date Country
2387100 Nov 2003 CA
2538139 Mar 2005 CA
2600529 Sep 2006 CA
103110410 May 2013 CN
103970977 Aug 2014 CN
105116848 Dec 2015 CN
108961714 Dec 2018 CN
110009245 Jul 2019 CN
110084928 Aug 2019 CN
110827457 Feb 2020 CN
1669912 Jun 2006 EP
2310981 Apr 2011 EP
07-085166 Mar 1995 JP
11-024735 Jan 1999 JP
11-317936 Nov 1999 JP
2001-356813 Dec 2001 JP
2005-242531 Sep 2005 JP
2005-311563 Nov 2005 JP
10-1172747 Aug 2012 KR
10-1445367 Oct 2014 KR
10-1499081 Mar 2015 KR
9621264 Jul 1996 WO
2004029518 Apr 2004 WO
2005022457 Mar 2005 WO
2005045715 May 2005 WO
2006099337 Sep 2006 WO
2008152433 Dec 2008 WO
2008157755 Dec 2008 WO
2009012319 Jan 2009 WO
2009079648 Jun 2009 WO
2010004514 Jan 2010 WO
2010106474 Sep 2010 WO
2011025085 Mar 2011 WO
2011043732 Apr 2011 WO
2011057173 May 2011 WO
2011123743 Oct 2011 WO
2013062725 May 2013 WO
2013178819 Dec 2013 WO
2014009291 Jan 2014 WO
2014098861 Jun 2014 WO
2014135517 Sep 2014 WO
2016123536 Aug 2016 WO
2017057274 Apr 2017 WO
2019046580 Mar 2019 WO
2020024553 Feb 2020 WO
Non-Patent Literature Citations (148)
Entry
“4.0 Today's Activities, The Home Dashboard,” CRBM info@hand website, 46 pages, prior to Apr. 25, 2013.
“America's Largest Managed Security Services Provider Launches Comprehensive, Integrated Covid-19 Safety Program for Office Buildings and Suites,” KastleSafeSpaces, 5 pages, May 11, 2020.
“An Overview of NiagraAX: A comprehensive software platform designed to create smart device applications,” Tridium, Inc., 2005.
“ASHRAE Dashboard Research Project,” 29 pages, Aug. 28, 2008.
“Attune Advisory Services,” press release, Honeywell International Inc., Mar. 20, 2012.
“BACnet Protocol Implementation Conformance Statement” for enteliWEB, Delta Controls, Jul. 17, 2013.
“Biometric Door Reader With Body Temperature Detection,” Kintronics, 9 pages, accessed May 21, 2020.
“Body Surface Temperature Screening with Alarm Function TVS-2001S/TVS-500IS,” Nippon Avionics Co., 3 pages, accessed May 21, 2020.
“BriefCam announces video analytics innovation for contact tracing, physical distancing, occupancy management and face mask detection,” BriefCam Ltd, 11 pages, Jun. 5, 2020.
“Building Automation Software Solutions,” Iconics, 2011.
“Contact Tracing Now Available on Identiv's Hirsch Velocity Access Control Platform,” IDENTIX, 5 pages, May 21, 2020.
“Creston Special Report: How Intelligent building management solutions are reducing operational costs,” Creston, 2012.
“Data analytics and smart buildings increase comfort and energy efficiency”, https://www.microsoft.com/itshowcase/Article/Content/845/Data-analytics-and-smart-buildings-increase-comfort-and-energy-efficiency, Dec. 19, 2016, 8 pages.
“Energy Manager User Guide,” Release 3.2, Honeywell, 180 pages, 2008.
“Facial Attendace System With Temperature Screening Now in India,” IANS, 5 pages, Mar. 19, 2020.
“FebriEye-AI Based Thermal Temperature Screening System,” vehant, 1 page, 2020.
“Free Facilities Dashboards,” eSight Energy Website, 2 pages, prior to Apr. 25, 2013.
“Fuzzy Logic Toolbox 2.1, Design and Stimulate Fuzzy Logic Systems,” The MathWorks, 2 pages, May 2004.
“How Smarter AI-Powered Cameras Can Mitigate the Spread of Wuhan Novel,” AnyConnect, 22 pages, 2020.
“How to fight COVID-19 with machine learning,” DataRevenue, 20 pages, accessed May 25, 2020.
“INNCONTROL 5,” Honeywell, 2 pages, Aug. 8, 2018.
“Intelligent Building Management Systems in Miami,” Advanced Control Corp., Mar. 7, 2013.
“IP Door Access Control,” KINTRONICS, 21 pages, 2014.
“Junk Charts, Recycling Chartjunk as junk art,” 3 pages, Oct. 2, 2006.
“Kogniz AI Health Response Platform,” Kogniz, 9 pages, accessed May 21, 2020.
“Machine Learning Could Check If You're Social Distancing Properly at Work,” MIT Technology Review, 7 pages, Apr. 17, 2020.
“Model Predictive Control Toolbox 2, Develop Internal Model-Based Controllers for Constrained Multivariable Processes,” The MathWorks, 4 pages, Mar. 2005.
“NEC launches dual face biometric and fever detection system for access control,” Biometric Update, 4 pages, May 8, 2020.
“NiagraAX Product Model Overview,” Tridium, Inc., 2005.
“Phoenix Controls Portal,” Phoenix Controls, Inc., 2013.
“Plan to Re-Open,” EHIGH, 16 pages, accessed Jun. 13, 2020.
“Remote temperature monitoring,” AXIS Communication, 10 p. 2014.
“See the World in a New Way Hikvision Thermal Cameras,” HIKVISION, 12 pages, 2017.
“Statistics Toolbox, for Use with Matlab,” User's Guide Version2, The MathWorks, 408 pages, Jan. 1999.
“The Ohio State University,” BACnet International Journal, vol. 5, p. 4, Jan. 2013.
“Thermal Imaging SmartPhone Can Be used for Temperature Screening of People,” Cat, 3 pages, accessed Jul. 13, 2020.
“Vykon Energy Suite Student Guide,” Tridium Inc., 307 pages, Mar. 3, 2006.
“Web Based Energy Information Systems for Energy Management and Demand Response in Commercial Buildings,” California Energy Commission, 80 pages, Oct. 2003.
“WEBs-AX Web-Enabled Building Solutions,” sales brochure, Honeywell International Inc., Mar. 2009.
Alerton Building Controls, Gallery Prints, 7 pages, Dec. 19, 2013.
Allain, “Trying out the iPhone Infrared Camera: The FLIR One,” Wired, 15 pages, 2014.
Andover Controls World, 4 pages, Spring 1997.
Andover Controls, Network News, vol. 2, No. 2, 8 pages, 1997.
Bell et al., “Early Event Detection-Results from a Prototype Implementation,” AICHE Spring National Meeting, 15 pages, Apr. 2005.
Bobker et al., “Operational Effectiveness in Use of BAS,” Proceedings of the 13th International Conference for Enhanced Building Operations, Oct. 8, 2013.
Bocicor, et al., Wireless Sensor Network based System for the Prevention of Hospital Acquired Infections, Arxiv.org, Cornell University Library, 201 Olin Library Cornell University Ithaca, NY 14853, May 2, 2017, XP080947042.
CADGRAPHICS, “The CADGRAPHICS User's Guide,” 198 pages, 2003.
Carrier Comfort Network CCN Web, “Web Browser User Interface to the Carrier Comfort Network,” 2 pages, 2002.
Carrier Comfort Network CCN Web, Overview and Configuration Manual, 134 pages, Apr. 2006.
Carrier Comfort Network CCN Web, Product Data, 2 pages, Apr. 2006.
Kourti, “Process Analysis and Abnormal Situation Detection: From Theory to Practice,” IEEE Control Systems Magazine, p. 10-25, Oct. 2002.
Lacey, “The Top 10 Software Vendors Connecting Smart Buildings to the Smart Grid,” http://www.greentechmedia.com/articles/read/the-top-10-companies-in-enterprise-smart-grid, Jul. 18, 2013.
Lucid Design Group, Inc., “Building Dashboard,” 2 pages, Printed May 30, 2013.
Mathew, “Action-Oriented Benchmarking, Using CEUS Date to Identify and Prioritize Efficiency Opportunities in California Commercial Buildings,” 26 pages, Jun. 2007.
Morrison et al., “The Early Event Detection Toolkit,” Honeywell Process Solutions, 14 pages, Jan. 2006.
Narang, “WEBARC: Control and Monitoring of Building Systems Over the Web,” 53 pages, May 1999.
Oey et al., “Evaluation of Isolation Compliance Using Real Time Video in Critical Care,” North Shore University Hospital, 1 page, Oct. 9, 2015.
Olken et al., “Object Lessons Learned from a Distributed System for Remote Building Monitoring and Operation,” ACM SIGPLAN Notices, vol. 33, No. 10, pp. 284-295, Oct. 1998.
Open Blue Companion Desktop User Guide, Johnson Controls, 18 pages, 2022.
Open Blue Digital Twin: Designed for Buildings. Infused with AI, Johnson Controls, 17 pages, 2022. Accessed Aug. 29, 2022.
Open Blue Enterprise Manager User Guide, Johnson Controls, 108 pages, Release 4.1.3, 2022, Accessed Aug. 29, 2022.
Open Blue Enterprise Manager User Guide, Johnson Controls, Release 3.1, 72 pages, Jan. 28, 2021.
Open Blue Enterprise Manager User Guide, Johnson Controls, Release 4.0, 78pages, Nov. 29, 2021.
Open Blue Enterprise Manager, Optimize Building Porl1olio Performance with Advanced Data Analystics and AI, Johnson Controls, 20 pages, Accessed Aug. 29, 2022.
Open Blue Location Manager User Guide, Johnson Controls, Release 2.4.7, 28 pages, Jul. 20, 2022.
Open Blue Platform, Make Smarter, Faster, More Data-Driven Decisions, Johnson Controls, 15 pages, 2022. Accessed Aug. 29, 2022.
Open Blue, Now, Spaces have Memory and Identity, Johnson Controls, 20 pages, 2022. Accessed Feb. 10, 2022.
Panduit Corp., “Enable a Building Automation with Panduit Enterprise Solutions,” 4 pages, Nov. 2012.
Preuveneers et al., “Intelligent Widgets for Intuitive Interaction and Coordination in Smart Home Environments,” IEEE Eighth International Conference on Intelligent Environments, pp. 157-164, 2012.
Proliphix, Inc., “Proliphix IP Devices: HTTP API,” 28 pages, Jan. 23, 2006.
Proliphix, Inc., Remote Management User Guide, 12 pages, prior to Aug. 27, 2007.
Published Australian Application 2009904740, 28 pages, Application Filed on Sep. 29, 2009.
Punn et al., “Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques,” 10 pages, May 6, 2020.
Quirk, “A Brief History of BIM,” Arch Daily, Dec. 7, 2012.
Rogan et al., “Smart and Final Food Stores: A Case Study in Web Based Energy Information and Collection,” Web Based Energy Information and Control Systems: Case Studies and Application, Chapter 6, p. 59-64, 2005.
Risbeck et al; “Modeling and Multiobjective Optimization of Indoor Airborne Disease Transmission Risk and Associated Energy Consumption for Building HVAC Systems,” Energy and Buildings, vol. 253, 24 pages, 2021.
Samad et al., “Leveraging the Web: A Universal Framework for Building Automation,” Proceedings of the 2007 American Control Conference, Jul. 11, 2007.
Search Report and Written Opinion from related International PCT Application No. PCT/US2018/025189 dated Jul. 17, 2018 (12 pages).
Sharp, “Actius AL3DU 3D LC Display High Performance 3D Visualization,” 2 pages, prior to Mar. 17, 2006.
Shhedi et al., “Traditional and ICT Solutions for Preventing the Hospital Acquired Infection”, 2015 20th International Conference on Control Systems and Computer Science, IEEE, May 27, 2015, pp. 867-873, XP033188038.
Silva et al., “Cough localization for the detection of respiratory diseases in pig houses,” ScienceDirect, 7 pages, May 28, 2008.
Sinha et al., “9 Key attributes of energy dashboards and analytics tools,” https://www.greenbiz.com/blog/2013/08/28/9-key-attributes-energy-dashboards-and=analytics-tools, Aug. 28, 2013.
Sinha et al; “Balance Infection Risk, Sustainability and Comfort with Open Blue,” Johnson Controls, 2 pages, 2021.
Sinopoli, “Dashboards for Buildings,” http://www/automatedbuildings.com/news/dec10/articles/sinopoli/101119034404sinopoli.html, Dec. 2010.
Sinopoli, “Modeling Building Automation and Control Systems,” http://www.automatedbuildings.com/news/jun13/articles/sinopoli/130521122303sinopoli.html, Jun. 2013.
So et al., “Building Automation on the Information Superhighway,” ASHRAE (American Society of Heating Refrigerating, and Air Conditioning) Transactions, vol. 104, Part 2, pp. 176-191, 1998.
So et al., “Building Automation Systems on the Internet,” Facilities vol. 15, No. 5/6, pp. 125-133, May/Jun. 1997.
Talon, “Raptor Controller,” 6 pages, Oct. 2003.
Talon, “Workstation Software,” 4 pages, Nov. 2002.
Trane, “System Programming, Tracer Summit Version 14, BMTW-SVP01D-EN,” 623 pages, 2002.
U.S. Appl. No. 62/739,655, filed Oct. 1, 1018 and entitled “System and Method for Monitoring Compliance With an Optimized Plan in an Operating Room to Reduce Patient Infection”.
Wu et al., “A Web 2.0 Based Scientific Application Framework,” 7 pages, prior to Jul. 24, 2014.
www.geappliances.com/home-energy-manager/about-energy-monitors.htm, “Energy Monitor, Home Energy Monitors, GE Nucleus,” 2 pages, printed Jan. 15, 2013.
www.luciddesigngroup.com/network/apps.php#homepage, “Lucid Design Group-Building Dashboard Network-Apps,” 7 pages, Jan. 15, 2013.
Zito, “What is Tridium Part 1,” http://blog.buildingautomationmonthly.com/what-is-tridium/, May 12, 2013.
Carrier, “i-Vu Powerful and Intuitive Front End for Building Control,” 2 pages, Aug. 2005.
Carrier, “i-Vu Web-Based Integrated Control System,” 3 pages, 2005.
Carrier, Demo Screen Shots, 15 pages, prior to Aug. 27, 2007.
Carrier, i-Vu CCN 4.0, Owner's Guide, 20 pages, Jul. 2007.
Carrier, i-Vu CCN, 7 pages, 2007.
Carter, “Industrial Energy Management Dashboards Require a Toolkit,” Cross Automation, 11 pages, Nov. 4, 2013.
Castelo, “A 3D Interactive Environment for Automated Building Control,” Elsevier, Nov. 8, 2012.
Castle, “7 Software Platforms that Make Building Energy Management Easy,” http://greentechadvocates.com/2012/11/28/7-software-platforms-that-make-building-energy-managment-easy/, Nov. 28, 2012.
Chen, “Rank Revealing QR Factorizations,” Linear Algebra and It's Applications, vol. 88-89, p. 67-82, Apr. 1987.
Circon, “i-Browse Web-Based Monitoring and Control for Facility Management,” 2 pages, prior to Aug. 27, 2007.
Dasgupta, “Your voice may be able to tell you if you have Covid,” Hindustan Times, 4 pages, Apr. 16, 2020.
Donnelly, “Building Energy Management: Using Data as a Tool”, http://www.buildingefficiencyinitiative.org/sites/default/files/legacy/InstituteBE/media/Library/Resources/Existing-Building-Retrofits/Using-Building-Data-as-a-Tool.pdf, Oct. 2012, 9 pages.
e-homecontrols.com, “e-Home Controls Website,” link to actual website no longer works, 1 page, prior to Dec. 19, 2013.
Echelon, “Energy Control Solutions with the i.Lon SmartServer,” 4 p. 2007.
Echelon, “i.Lon 100e3 Internet Server Models 72101R-300, 72101R-308, 72102R-300, 72103-R300 . . . ” 5 pages, copyright 2002-2007.
Echelon, “i.Lon 100e3 Internet Server New Features,” 15 pages, Sep. 2006.
Echelon, “i.Lon SmartServer,” 5 pages, 2007.
EnteliWEB catalog sheet, Delta Controls, Inc., 2012.
EnteliWEB catalog sheet, Delta Controls., 2010.
EnteliWEB product from Delta Controls, web pages retrieved on May 9, 2013 from http://deltacontrols.com/products/facilities-management/supervisory-software et seq. by the Internet Archive at web.archive.org.
Extended European Search Report, EP application No. 20151295.1, pp. 13, May 26, 2020.
Ganguty, “Gurugram-based startup Staqu has modified AI-powered JARVIS to battle coronavirus,” YOURSTORY, 7 pages, Mar. 31, 2020.
Honeywell News Release, “Honeywell's New Sysnet Facilities Integration System for Boiler Plant and Combustion Safety Processes,” 4 pages, Dec. 15, 1995.
Honeywell, “Excel Building Supervisor-Integrated R7044 and FS90 Ver. 2.0,” Operator Manual, 70 pages, Apr. 1995.
Honeywell, “Introduction of the S7350A Honeywell WebPAD Information Appliance,” Home and Building Control Bulletin, 2 pages, Aug. 29, 2000; Picture of WebPad Device with touch screen, 1 Page; and screen shots of WebPad Device, 4 pages.
Honeywell, “Product Guide 2004,” XP-002472407, 127 pages, 2004.
Honeywell, Excel 15B W7760B Building Manager Release 2.02.00, Installation Instructions, 28 pages, Dec. 2004.
Honeywell, The RapidZone Solution, Excel 5000 Open System, Application Guide, 52 pages, Jan. 2004.
http://pueblo.lbl.gov/-olken . . . , “Remote Building Monitoring and Operations Home Page,” 5 pages, prior to Aug. 27, J007.
http://www.ccbac.com, “C&C (/)—Omniboard,” 5 pages, Dec. 19, 2013.
http://www.commercial.carrier.com/commercial/hvac/productdescription . . . , “Carrier: 33CSCCNWEB-01 CCN Web Internet Connection to the Carrier Comfort Network,” 1 page, printed Mar. 11, 2008.
http://www.commercial.carrier.com/commercial/hvac/productdescription . . . , “Carrier: i-Vu CCN,” 1 page, printed Mar. 11, 2008.
http://www.docs.hvacpartners.com/idc/groups/public/documents/techlit/gs-controls-ivuccn.rtf, “Products,” 5 pages, printed Jul. 3, 2007.
http://www.domcontroller.com/en/, “DomController Home Automation Software—Control Anything from Anywhere,” 11 pages, printed Jan. 6, 2015.
http://www.lightstat.com/products/istat.asp, Lightstat Incorporated, “Internet Programmable Communicating Thermostats,” 1 page, printed Mar. 13, 2007.
http://www.novar.com/ems-bas/opus-building-automation-system, “Novar OPUS BAS,” 1 page, prior to Feb. 13, 2013.
http://www.sharpsystems.com/products/pc_notebooks/actiusird/3d/, “Actius RD3D Desktop Replacement Notebook with Industry-Breakthrough 3D Screen,” Sharp, 1 page, printed Jun. 16, 2005.
http://www2.sims.berkeley.edu/courses/is213/s06/projects/lightson;final.html, “Lights on a Wireless Lighting Control System,” 11 pages, printed Mar. 22, 2007.
I-stat, Demo Screen Shots, 9 pages, printed Mar. 13, 2007.
I-stat, The Internet Programmable Thermostat, 2 pages, prior to Aug. 27, 2007.
I.Lon 100e3 Internet Server, 1 page, prior to Aug. 27, 2007.
I.Lon, SmartServer, 2 pages, prior to Aug. 27, 2007.
Instituto Superior Tecnico, “A 3D Interactive Environment for Automated Building Control,” Master's Dissertation, 120 pages, Nov. 2012.
Zito, “What is Tridium Part 2,” http:I/blog.buildingautomalionmonlhly.com/Iridium-part-2/, Sep. 10, 2013.
Ball, “Green Goal of ‘Carbon Neutrality’ Hits Limit,” TheWall Street Journal, 7 pages, Dec. 30, 2008.
Johnson Controls and Microsoft Announce Global Collaboration, Launch Integration between Open Blue Digital Twin and Azure Digital Twins, 7 pages, 2022. Accessed Aug. 29, 2022.
Johnson Controls Develops Industry-first Al Driven Digital Solution to Manage Clean Air, Energy, Sustainability, Comfort and Cost in Buildings, 7 pages, 2022. Accessed Aug. 29, 2022.
Johnson Controls, Network Integration Engine (NIE) 3 pages, Nov. 9, 2007.
Johnson Controls, Network Integration Engine (NIE), Product Bulletin, pp. 1-11, Jan. 30, 2008.
Shhedi, Zaid Ali, et al., “Traditional & ICT Solutions for preventing the Hospital Acquired Infection,” 2015 20th International Conference on Control Systems and Science, IEEE, May 27, 2015, pp. 867-873, XP933188038, DOI: 10.1109/CSCS.2015.125.
Bocicor, I., et al., “Wireless Sensor Network based System for the Prevention of Hospital Acquired Infections,” Arxiv.org, Cornell University Library, 201 Olin Library Cornell University Ithaca, NY 14853, May 2, 2017, XP080947042.
EP Communication pursuant to Article 94(3) EPC, European Patent Office, EP Application No. 20 151 295.1, Mar. 29, 2023 (9 pages).
EP Summons to attend oral proceedings pursuant to Rule 115(1) EPC, European Patent Office, EP Application No. 20 151 295.1, May 22, 2024 (11 pages).
Related Publications (1)
Number Date Country
20240079122 A1 Mar 2024 US
Continuations (2)
Number Date Country
Parent 17196297 Mar 2021 US
Child 18505093 US
Parent 16246437 Jan 2019 US
Child 17196297 US