INDOOR AIR QUALITY MONITORING SYSTEM

FIELD

Embodiments herein relate to indoor air quality monitoring systems and related methods.

BACKGROUND

Indoor air quality in manufacturing plants and other industrial settings can be a concern due to a variety of factors, including emissions from machinery and equipment, particulates which are generated during some processes, and the use of chemicals, solvents, and the like. Poor indoor air quality can lead to health problems such as respiratory issues, headaches, and fatigue. In addition, poor indoor air quality can also affect productivity and lead to increased absenteeism. Other concerns include the potential risk of fire or explosion due to the presence of flammable or combustible materials, and the potential for the release of hazardous substances into the environment. To address these concerns, it is important to implement effective indoor air quality monitoring and/or management systems.

SUMMARY

Embodiments herein relate to indoor air quality monitoring systems and related methods. In a first aspect, an indoor air quality monitoring system can be included having a control circuit, a memory circuit in electronic communication with the control circuit, and a sensor channel interface in electronic communication with the control circuit. The system can be configured to store a model set of data reflecting information on air quality determining features within a physical indoor environment, receive sensor data regarding air quality at discrete points within the physical indoor environment, and evaluate the sensor data regarding air quality and perform operations to generate one or more outputs relating to air quality within the physical indoor environment.

In a second aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include at least one selected from the group consisting of executing airflow modeling calculations using the model set of data reflecting the air quality determining features and estimating air quality values at discrete geolocation points within the physical indoor environment, evaluating the sensor data regarding air quality to determine whether changes to the air quality determining features or the operating parameters thereof can be needed in a present state or a future state to maintain one or more predetermined air quality standards, and generating one or more recommendations regarding maintaining or enhancing air quality within the physical indoor environment.

In a third aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the predetermined air quality standards include at least one selected from the group consisting of levels of particulates, levels of VOCs, levels of CO₂, levels of CO, levels of NO₂, and levels of SO₂.

In a fourth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the air quality determining features can include at least one selected from the group consisting of airborne contaminant removal devices, air flow generating devices or systems, airborne contaminant generating devices or zones, and air exchange features.

In a fifth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the airborne contaminant removal devices can include dust collectors.

In a sixth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the airborne contaminant removal devices can include VOC removal devices.

In a seventh aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the model set of data can include at least one selected from the group consisting of an air volume of the physical indoor environment and a physical configuration of the indoor environment.

In an eighth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the sensor data regarding air quality can include at least one selected from the group consisting of current levels of particulates, current levels of VOCs, current levels of CO₂, current levels of CO, current levels of SO₂, current levels of NO₂, and current temperature.

In a ninth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can be configured to validate the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality.

In a tenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can be configured to validate the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

In an eleventh aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can be configured to update the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

In a twelfth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can execute airflow modeling calculations using the model set of data reflecting the air quality determining features and estimate air quality values at discrete geolocation points within the physical indoor environment, compare the estimated air quality values at discrete geolocation points against sensor data related to the same discrete geolocation points, and adjust further estimates based on the compared values.

In a thirteenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the control circuit generates a user interface output.

In a fourteenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the user interface output can include at least one selected from the group consisting of graphical objects representing the air quality determining features, values representing air quality measures, and a graphical representation of the physical indoor environment.

In a fifteenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can be configured to track estimated air quality at discrete geolocations within the physical indoor environment over time.

In a sixteenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can be configured to calculate estimated exposure values to airborne contaminants associated with a presence at discrete geolocations or zones within the physical indoor environment longitudinally over time.

In a seventeenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality has worsened unexpectedly.

In an eighteenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality has decreased by an amount exceeding a threshold value over a period of time and issuing a notification regarding the identified one or more discrete geolocations or zones.

In a nineteenth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include identifying a likely source of air contamination based on information regarding one or more discrete geolocations or zones within the physical indoor environment wherein air quality has worsened unexpectedly, the sensor data regarding air quality, and the stored set of model data.

In a twentieth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can further include one or more sensors, wherein the one or more sensors can be in electronic communication with the sensor channel interface.

In a twenty-first aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the system can further include one or more sensors, wherein the one or more sensors can be in wireless electronic communication with other components of the system.

In a twenty-second aspect, a method of monitoring indoor air quality can be included. The method can include storing a model set of data reflecting information on air quality determining features within a physical indoor environment, receiving sensor data regarding air quality at discrete points within the physical indoor environment, and evaluating the sensor data regarding air quality and performing operations to generate one or more outputs relating to air quality within the physical indoor environment.

In a twenty-third aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the method can further include validating the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality.

In a twenty-fourth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the method can further include validating the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

In a twenty-fifth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the method can further include updating the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

In a twenty-sixth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the method can further include tracking estimated air quality at discrete geolocations within the physical indoor environment over time.

In a twenty-seventh aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the method can further include calculating estimated exposure values to airborne contaminants associated with a presence at discrete geolocations or zones within the physical indoor environment longitudinally over time.

In a twenty-eighth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include executing airflow modeling calculations using the model set of data reflecting the air quality determining features and estimating air quality values at discrete geolocation points within the physical indoor environment.

In a twenty-ninth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include generating one or more recommendations regarding maintaining or enhancing air quality within the physical indoor environment.

In a thirtieth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include evaluating the sensor data regarding air quality to determine whether changes to the air quality determining features or the operating parameters thereof can be needed in a present state or a future state to maintain one or more predetermined air quality standards.

In a thirty-first aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the predetermined air quality standards include at least one selected from the group consisting of levels of particulates, levels of VOCs, levels of CO₂, levels of CO, levels of NO₂, and levels of SO₂.

In a thirty-second aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the air quality determining features can include at least one selected from the group consisting of airborne contaminant removal devices, air flow generating devices or systems, airborne contaminant generating devices or zones, and air exchange features.

In a thirty-third aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the airborne contaminant removal devices can include dust collectors.

In a thirty-fourth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the airborne contaminant removal devices can include VOC removal devices.

In a thirty-fifth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the model set of data can include at least one selected from the group consisting of an air volume of the physical indoor environment and a physical configuration of the indoor environment.

In a thirty-sixth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the sensor data regarding air quality can include at least one selected from the group consisting of current levels of particulates, current levels of VOCs, current levels of CO₂, current levels of CO, current levels of SO₂, current levels of NO₂, and current temperature.

In a thirty-seventh aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the method can further include generating a user interface output.

In a thirty-eighth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the user interface output can include at least one selected from the group consisting of graphical objects representing the air quality determining features, values representing air quality measures, and a graphical representation of the physical indoor environment.

In a thirty-ninth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality can have worsened unexpectedly.

In a fortieth aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality can have decreased by an amount exceeding a threshold value over a period of time and issuing a notification regarding the identified one or more discrete geolocations or zones.

In a forty-first aspect, in addition to one or more of the preceding or following aspects, or in the alternative to some aspects, the operations to generate one or more outputs can include identifying a likely source of air contamination based on information regarding one or more discrete geolocations or zones within the physical indoor environment wherein air quality can have worsened unexpectedly, the sensor data regarding air quality, and the stored set of model data.

This summary is an overview of some of the teachings of the present application and is not intended to be an exclusive or exhaustive treatment of the present subject matter. Further details are found in the detailed description and appended claims. Other aspects will be apparent to persons skilled in the art upon reading and understanding the following detailed description and viewing the drawings that form a part thereof, each of which is not to be taken in a limiting sense. The scope herein is defined by the appended claims and their legal equivalents.

BRIEF DESCRIPTION OF THE FIGURES

Aspects may be more completely understood in connection with the following figures (FIGS.), in which:

FIG. 1 is a schematic view of a monitored building in accordance with various embodiments herein.

FIG. 2 is a flowchart illustrating operations of a method in accordance with various embodiments herein.

FIG. 3 is a schematic view of aspects of a monitored building in accordance with various embodiments herein.

FIG. 4 is a schematic view of aspects of a monitored building in accordance with various embodiments herein.

FIG. 5 is a schematic view of aspects of a monitored building in accordance with various embodiments herein.

FIG. 6 is a schematic view of aspects of a monitored building in accordance with various embodiments herein.

FIG. 7 is a schematic view of aspects of a monitored building in accordance with various embodiments herein.

FIG. 8 is a perspective view of a dust collector in accordance with various embodiments herein.

FIG. 9 is a partial cross-sectional view of a dust collector in accordance with various embodiments herein.

FIG. 10 is a perspective view of a dust collector monitoring device in accordance with various embodiments herein.

FIG. 11 is a schematic view of components of an indoor air quality monitoring system in accordance with various embodiments herein.

FIG. 12 is a block diagram of components of a dust collector monitoring device in accordance with various embodiments herein.

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

DETAILED DESCRIPTION

As referenced above, indoor air quality can be a concern in manufacturing plants as well as other indoor environments. Sensors to detect air quality can be useful in monitoring air quality. However, sensing alone does not allow for the generation of rapid insights regarding possible causes of air quality changes within a plant and/or effective steps for mitigation for the same.

Embodiments herein can include advanced air quality management systems that integrate a model of an environment with real time input from sensing systems to enable the generation of rapid insights into the causes of air quality changes as well as steps that can be taken to mitigate the same. For example, integration of a model of an environment with real time input from sensing systems allows for likely causes of air quality changes to be identified and/or suggested mitigation actions (short term and/or long term) to be generated by the system.

In various embodiments, indoor air quality monitoring systems herein can be configured to store a model set of data reflecting information on air quality determining features within a physical indoor environment. Systems herein can also be configured to receive sensor data regarding air quality at discrete points within the physical indoor environment and then evaluate the same and perform operations to generate one or more outputs relating to air quality within the physical indoor environment.

The air quality determining features represented in the model/model set of data can include various items or systems such as airborne contaminant removal devices, air flow generating devices or systems, airborne contaminant generating devices or zones, air exchange features, and the like. As an example, airborne contaminant removal devices can include, but are not limited to, devices like dust collectors and VOC removal devices. Air flow generating devices or systems can include, but are not limited to, fans, various HVAC components, and the like. Airborne contaminant generating devices or zones can include various types of workstations or zones (welding, grinding, machining, painting, cleaning, or any other manufacturing operation) and material storage devices or zones (such as solvent storage tanks, gas storage tanks, other material storage, and other supplies). Air exchange features can include air exchange devices, windows, doors, and the like.

Systems here can generate many different outputs to aid in managing the indoor air quality of a particular site or building. Generating such outputs can involve various operations. For example, the operations to generate one or more outputs herein can include executing airflow modeling calculations using the model set of data reflecting the air quality determining features and estimating air quality values at discrete geolocation points within the physical indoor environment. Operations can also include evaluating the sensor data regarding air quality to determine whether changes to the air quality determining features or the operating parameters thereof are needed in a present state or a future state to maintain one or more predetermined air quality standards. In some cases, air quality standards may relate to levels of particulates (such as PM2.5—particles that have a diameter less than 2.5 micrometers; PM10—particles that have a diameter of less than 10 micrometer; etc.), levels of various VOCs, levels of CO₂, CO, ozone, NO₂or other nitrogen compounds, SO₂or other sulfur compounds, or other gases). In some embodiments, the predetermined air quality standards may relate to a particular air quality index (AQI) value, such as an AQI value of 100 or another particular value. Additional operations can include generating one or more recommendations regarding maintaining or enhancing air quality within the physical indoor environment. These and other operations the system can perform are described in greater detail below.

Referring now to FIG. 1, a schematic view of a monitored building 100 is shown in accordance with various embodiments herein. In this example, the monitored building 100 includes building walls 102 surrounding a physical indoor environment 130. Various elements can be disposed within the physical indoor environment 130, many of which may impact indoor air quality. In this particular example, the monitored building 100 can include a first workstation 104, a second workstation 106, a third workstation 108, and a fourth workstation 110. Of course, it will be appreciated that any given number of workstations (or zones) can be included, each with a specific location (such as geolocation) within the monitored building 100. The workstations can represent various types of activities that may be conducted within a monitored building 100 that may impact indoor air quality such as welding, grinding, machining, painting, cleaning, or any other manufacturing operation. Such workstation locations may also reflect the likely presence of workers (at least periodically) for exposure tracking purposes herein.

The monitored building 100 illustrated in FIG. 1 also includes windows 112, entry doors 114, and overhead doors 116. It will be appreciated that opening or closing windows 112, entry doors 114, and overhead doors 116 can affect airflow and, as such, these structures can be taken into account with the model used by the systems herein. The monitored building 100 also includes various sensor units 120. In some embodiments, the sensor units 120 can be associated with a specific zone of interest. The sensor units 120 can collect data and/or generate a signal used by the system herein in monitoring air quality. In some embodiments, the sensor units 120 can directly measure levels of a contaminant of interest, such as levels of particulates, levels of VOCs, and levels of CO, CO₂, levels of SO₂or other sulfur compounds, levels of NO₂or other nitrogen compounds, or other gases, or any of the other contaminants referenced herein. In some embodiments, the sensor units 120 (or at least some sensor units) can measure things like air speed at a particular spatial point, air direction at a particular spatial point, temperature, light, humidity, and the like.

The monitored building 100 can also include various air contaminant removal devices (or contaminant mitigation devices). FIG. 1 illustrates a dust collector 150, however, it will be appreciated that all types of air contaminant removal devices are contemplated herein including, but not limited to, chemical scrubbers, various absorbent systems, and the like. In some embodiments, the dust collector(s) 150 can include a dust collector monitoring device 152. Details of exemplary dust collector monitoring devices are described below. Briefly, however, a dust collector monitoring device 152 herein can include various air quality monitoring sensors therein. In some embodiments, a dust collector monitoring device 152 can receive data from other sensor units 120 in the environment and serve to aggregate the data and/or serve as a gateway for transmitting the same to other components of the system (local or remote) for various processing steps, or to another system entirely.

Referring now to FIG. 2, a flowchart is shown illustrating operations 200 performed in accordance with various embodiments herein. The operations 200 can include an operation of storing 202 a model set of data reflecting information on air quality determining features within a physical indoor environment. The model set of data can include information on air quality determining features within the physical indoor environment. The model set of data can also include information regarding aspects of the particular environment being monitored such as an air volume of the physical indoor environment and a physical configuration of the indoor environment. The operations 200 can also include an operation 200 of receiving 204 sensor data regarding air quality at discrete points within a physical indoor environment. In this manner, the system can integrate real time sensor data with a model of a physical indoor environment. Sensor data can be of various types as described elsewhere herein. For example, the sensor data regarding air quality can include information such as levels of particulates, levels of VOCs, and levels of CO, CO₂, levels of SO₂or other sulfur compounds, levels of NO₂or other nitrogen compounds, or other gases, or any of the other contaminants referenced herein, and current temperature.

The operations 200 performed can also include an operation of evaluating 206 the sensor data regarding air quality and performing operations to generate one or more outputs relating to air quality within a physical indoor environment. In various embodiments, the operations to generate one or more outputs can include at least one including at least one of executing airflow modeling calculations using the model set of data reflecting the air quality determining features and estimating air quality values at discrete geolocation points within the physical indoor environment 130, evaluating the sensor data regarding air quality to determine whether changes to the air quality determining features or the operating parameters thereof are needed in a present state or a future state to maintain one or more predetermined air quality standards (such as threshold levels of one or more contaminants), and generating one or more recommendations regarding maintaining or enhancing air quality within the physical indoor environment 130. Such outputs can be enabled by the integration of the model of the physical indoor environment with the sensor data.

FIGS. 3-7 illustrate aspects of how the system can operate in various air contamination scenarios. Referring specifically to FIG. 3, a schematic view is shown of aspects of a monitored building or site in accordance with various embodiments herein. As before, the monitored building includes building walls 102 surrounding a physical indoor environment 130. The monitored building also includes various pieces of equipment therein such as dust collectors 150, product racks 302, enclosed rooms 304 (such as an office, bathroom, etc.), tooling racks 306, work tables 308, and welding stations 312.

FIG. 3 shows a plurality of air velocity vectors that illustrate the flow of air through the physical indoor environment 130. The air velocity vectors can be part of a model of the physical indoor environment 130. As such, information regarding the air velocity vectors can be a part of the model and/or model data used herein and/or can be generated by the system using the model data herein. In some embodiments, information regarding air velocity vectors can be generated through measurements as a part of a configuration process, can be input into the system by a system user or from another system, or can be estimated using computational fluid dynamics approaches as described further below.

FIG. 3 also shows contaminant levels (in this case, levels of particulates measured in mg/m³) throughout the physical indoor environment 130. In this example, the monitored building generally has high air quality with only a small area having relatively high contaminant concentrations 320.

Two air quality sensors 120 are also shown within the physical indoor environment 130. However, it will be appreciated that any number of air quality sensors 120 can be used and that the system is not limited to using only two. The air quality sensors 120 can produce data about air quality within the physical indoor environment 130 that can be used by the system in combination with the model of the physical indoor environment 130.

It will be appreciated that the physical indoor environment 130 can change in various ways over time. In some cases, the change may be transitory, such as a garage door being opened. However, in other cases the change may be non-transitory, such as new pieces of equipment being added or the space being reconfigured. All of these changes (transitory and non-transitory) can impact air quality and, as such, can be taken into account and/or addressed by systems herein.

Referring now to FIG. 4, a schematic view is shown of aspects of a monitored building or site in accordance with various embodiments herein. As before, the monitored building includes building walls 102 surrounding a physical indoor environment 130 and includes various pieces of equipment therein such as dust collectors 150, product racks 302, enclosed rooms 304, tooling racks 306, worktables 308, and welding stations 312. Two air quality sensor 120 are also within the physical indoor environment 130.

In the example of FIG. 4, a change has occurred adversely impacting air quality. As can be seen in FIG. 4, contaminant levels throughout the physical indoor environment 130 are substantially higher than as illustrated in FIG. 3. Notably, both air quality sensors 120 are reporting contaminant levels above a threshold level of contamination. Threshold values herein can be predetermined or can be dynamically calculated. In some embodiments, thresholds can be input into the system by a system user or received from a different system and can reflect the goals for air quality management within a particular environment. In some embodiments, threshold values can reflect EPA guidelines.

The system can generate a notification or alert regarding the observed air quality change. The notification or alert can include information on the locations or zones within the physical indoor environment 130 that have experienced the adverse air quality change. The system can issue the notification or alert through a user interface of the system, through a data network, to another system or device, or the like. In some embodiments, the notification or alert can be provided to an operator of the manufacturing plant and/or to a monitoring agent, service, or system.

The system can also record information regarding the timing of the observed change (such as when the contaminant value first crossed the threshold value, whether it is substantially constant or is periodic, and how long the contamination state has persisted). In this case, the increase in contaminant amounts has stayed substantially constant since initially occurring. Timing information regarding contaminants (alone or in combination with other information about contaminants as discussed herein) can be cross-referenced with information from the model of the indoor environment and allow the system to provide additional insights as to possible causes of the contamination as well as recommended mitigation actions. As one example, if a higher level of contamination is detected in a particular area of the indoor environment, then the model can be used by the system to predict how long it may take for contamination levels to return to a normal or baseline value assuming the contamination was caused by a one-off or otherwise transitory event. However, if the contamination values do not return to normal or baseline in the predicted time frame, then this can be taken as an indication of a chronic (non-transitory) event (such as may result from a change having been made to the indoor environment necessitating additional contaminant removal capacity) and a notice regarding the same can be provided by the system.

In this example, two new pieces of equipment 402 were added generating additional air contamination and they were responsible for the adverse change to air quality. Because the system herein can be configured to provide notice of the adverse change in air quality as well as timing information regarding the same, an operator or manager associated with the physical environment can quickly deduce that the adverse change coincided with the addition of the two piece of equipment 402 and therefore determine that they are the cause.

In some scenarios, physical changes made in the monitored environment 130 are input into the system by a system user and/or received by the system from a separate system or device. In various embodiments, the system can cross-reference observed air quality changes with physical changes that have been made to identify that the physical changes are the likely the cause of the adverse air quality change and can include identification of the same in a notification or alert.

In some embodiments, the system can also provide suggestions that are uniquely enabled by the integration of sensor data with the model of the indoor environment. In some embodiments, the system can provide suggestions regarding improving the air quality including, but not limited to, providing recommendations regarding additional contaminant removal equipment, changes to contaminant removal equipment and/or contamination generating systems/devices, location of contaminant removal equipment and/or contamination generating systems/devices, and the like based on the sensor data indicating current air contamination as well as information from the air flow model.

Referring now to FIG. 5, a schematic view is shown of aspects of a monitored building or site in accordance with various embodiments herein. FIG. 5 is generally similar to FIG. 4 but illustrates the effects of a suggested solution to the air contamination issue shown in FIG. 4. In this case, the system can be configured to provide a recommended solution in the form of adding an additional collector 502 in a specific location within physical indoor environment 130 to optimize its effects on air quality. The recommendation can be provided in the form of a notification or alert. In some embodiments, the recommendation can be provided through a user interface, such as those described herein. As can be seen from the air quality information in FIG. 5, the additional collector 502 is effective to return air quality back to desirable levels.

In some cases, a circumstance such as a gas leak can adversely impact air quality. In this scenario, the system herein can detect a change in air quality using sensor data and provide information, based on the model, as to a likely location of the issue and/or a likely source of the issue. Referring now to FIG. 6, a schematic view is shown of aspects of a monitored building or site in accordance with various embodiments herein. As before, the monitored building includes building walls 102 surrounding a physical indoor environment 130 and includes various pieces of equipment therein such as dust collectors 150, product racks 302, enclosed rooms 304, tooling racks 306, work tables 308, welding stations 312, two air quality sensor 120, two additional pieces of equipment 402, and the additional collector 502 from the previous example.

In this example, the system detects that air quality has worsened within a particular area 602 (or zone) of the physical indoor environment 130. Based on the model used by the system, the system predicts the likely source area 604 of the contamination to be upstream from where sensor(s) have detected the air contamination. The system can also cross-reference the source area 604 with location information of equipment to determine what equipment is in the source area 604. Information regarding the nature of the contamination (particulates, gases, etc.) as sensed with sensors herein can also be cross-referenced with information regarding what type of contamination the equipment within the source area 604 can generate. On this basis, in this example, the system is configured to identify that a leak has likely occurred with a propane tank 606 within the source area 604.

As before, the system can provide a notification or alert regarding the observed air quality, the source area 604, and/or the equipment within the source area 604 that may be causing the air contamination. Appropriate action can then be taken to mitigate the air contamination. In various embodiments, appropriate action can be recommended by the system to mitigate the air contamination. In some embodiments, such action can be taken by (e.g., recommendations can be executed by) personnel within the physical location, such as by fixing the leak to the propane tank 606. In other embodiments, action can be taken by the system itself to mitigate the air contamination such as by initiating opening of windows or doors (or actually opening them by sending a signal to a door or window actuator), or by sending control signals to various pieces of contaminant removal equipment that might be present in the physical environment (such as to cause them to start, increase their removal of contaminants, change their operational parameters, etc.).

Referring now to FIG. 7, a schematic view is shown of aspects of a monitored building or site in accordance with various embodiments herein. FIG. 7 is generally similar to FIG. 6. However, in FIG. 7 the propane tank 606 leak has now been stopped and the air quality has returned to a normal or baseline level.

Many different types of contaminant removal devices are contemplated herein and can be used by the system when modeling a physical environment and evaluating air contamination within the same. Referring now to FIG. 8, a perspective view of an exemplary dust collector 150 is shown in accordance with various embodiments herein. However, it will be appreciated that a dust collector is merely one example of a contaminant removal device. In this example, the dust collector 150 includes a dust collector monitoring device 152. The dust collector monitoring device 152 can include sensors to generate data used with monitoring systems herein. For example, the dust collector monitoring device 152 can include sensors to measure air contaminant levels.

In this example, the dust collector 150 depicted in FIG. 8 includes an upper wall panel 816, and two pairs of opposite side wall panels 817 (one of which is depicted in FIG. 8). It will be appreciated, however, that the dust collector 150 can take on many different shapes and configurations. In this example, the dust collector 150 includes a dirty air conduit 811 for receiving dirty or contaminated air (i.e., air with particulate matter therein) into the dust collector 150. A clean air conduit 813 can be provided for venting clean or filtered air from the dust collector 150. The dust collector 150 includes access openings 812 for multiple filter elements. In use, each of the access openings 812 is sealed by a cover such that dirty air entering the dust collector 150 does not escape through the access openings 812. The dust collector 150 may also include a hopper 818 to collect particulate matter separated from the dirty air stream as described herein.

In some embodiments, the dust collector 150 can include a fan 832 to provide movement of air through the dust collector 150. However, in other embodiments, air can be pulled through the system with a fan or other equipment that is not part of the dust collector 150. Air movement as caused by the dust collector 150 can be included within the models used by systems herein. The dust collector 150 can include a control box 840, which can include a control circuit for the filtration system.

The dust collector monitoring device 152 can be connected to a first fluid conduit 852, a second fluid conduit 854, and third fluid conduit 856. The fluid conduits can provide fluid communication between various parts of the filtration system (such as the dirty/upstream side, the clean/downstream side, a compressed air supply, etc.) and sensors/transducers that can be within or otherwise associated with the dust collector monitoring device 152. The first fluid conduit 852 can be connected to an existing fluid conduit 862 of the air filtration system that provides fluid communication with an area of fluid flow that is upstream from the filtration element(s). In some embodiments, the first fluid conduit 852 can be connected to the existing fluid conduit 862 using a junction 866 (such as a T-junction, splice junction, or other connecting structure). The second fluid conduit 854 can be connected to an existing fluid conduit 864 of the air filtration system that provides fluid communication with an area of fluid flow that is upstream from the filtration element(s). In some embodiments, the second fluid conduit 854 can be connected to the existing fluid conduit 864 using a junction 868 (such as a T-junction, splice junction, or other similar connecting structure).

Referring now to FIG. 9, a partial cross-sectional view of a dust collector 150 is shown in accordance with various embodiments herein. The interior of the dust collector 150 includes a tube sheet 922 that separates the interior of the housing into a clean air chamber 924 and a dirty air chamber 926. The dust collector 150 includes a clean air conduit 813 through which clean air exits from the clean air chamber 924 during operation of the dust collector 150.

The depicted dust collector 150 includes pulse collectors 930 and filter elements 940 in the dirty air chamber 926 (dirty side or upstream side). The pulse collectors 930 are attached to the tube sheet 922 over an aperture in the tube sheet 922 (not seen in FIG. 9) such that a pulse of air from the pulse generators 950 passing through the pulse collector 930 enters an interior volume of the filter elements 940. Air can be provided to the pulse generators 950 from a compressed air manifold 948, which itself can receive compressed air from an air compressor or central source of plant compressed air.

Referring now to FIG. 10, a perspective view of a dust collector monitoring device 152 is shown in accordance with various embodiments herein. The dust collector monitoring device 152 can include a first receptacle 1002 or fitting to receive a tube or other conduit as part of the first fluid conduit 852. The dust collector monitoring device 152 can also include a second receptacle 1004 or fitting to receive a tube or other conduit as part of the second fluid conduit 854. Although not shown in this figure, it will be appreciated that the dust collector monitoring device 152 can also include a third receptacle or fitting to receive a tube or other conduit as part of the third fluid conduit 856. In addition, various embodiments herein can include greater or lesser numbers of receptacle and/or fluid conduits.

In various embodiments, the dust collector monitoring device 152 can be mounted on a surface of the dust collector 150 such as an external surface thereof. For example, in some embodiments, the dust collector monitoring device 152 can be mounted on a side wall panel 817. However, the dust collector monitoring device 152 can also be mounted in other locations including on top or bottom walls as well as inside the filtration system 800 and also mounted off the filtration system 800 (such as on a separate panel that is physically separated from other components of the system). The monitoring device can be mounted using various hardware including, but not limited to, using fasteners, adhesives, magnets, and the like. In a particular embodiment, an adhesive layer 1006 is used to mount the housing of the dust collector monitoring device 152, which can be, for example, a pressure sensitive adhesive (PSA).

Systems herein can include various components including some that may be within a physical environment being monitored and some that may be located remotely. Referring now to FIG. 11, a schematic view of components of an exemplary indoor air quality monitoring system 1100 is shown in accordance with various embodiments herein. A work environment 1102 (such as a monitored building) includes dust collector(s) 150 (or other contaminant removal devices) that may also include a dust collector monitoring device 152. The work environment 1102 can represent various types of facilities including, but not limited to, a manufacturing facility, a food or grain processing facility, a shipping or distribution center, or the like.

In some embodiments, wireless signals from the dust collector monitoring device 152 can be exchanged with a wireless communication tower 1120 (or antenna array), which could be a cellular tower or other wireless communication tower. Similarly, signals from other sensors (such as air quality sensor 120) can be exchanged with a wireless communication tower 1120. The wireless communication tower 1120 can be connected to a data network 1122, such as the Internet or another type of public or private data network, packet-switched or otherwise.

The data network can provide for one-way or two-way communication with other components that are external to the work environment 1102. For example, a server 1124 (real or virtual) or other processing device that may be in a specific location or in the cloud can receive electronic signals containing data from one or more components such as the dust collector monitoring device 152 and/or air quality sensors 120. The server 1124 can interface with a database 1126 (real or virtual) to store data. In some embodiments, the server 1124 (or a device that is part of the server system) can interface with a user device 1128, which can allow a user to query data stored in the database 1126. The server 1124 and/or the database 1126 can be at a distinct physical location or can be in the cloud.

In various embodiments, the indoor air quality monitoring system 1100 can be configured to store a model set of data reflecting information on air quality determining features within a physical indoor environment 130. The model set of data can be stored within the cloud, such as on the server 1124 and/or in the database 1126. However, in some embodiments, the model set of data can also be stored on a device in or near the work environment 1102.

It will be appreciated that operations as described herein can be executed by a single device or execution can be distributed across different devices.

In some embodiments, the dust collector monitoring device 152 can serve as a signal communication gateway for sensing devices (such as air quality sensor 120) within the work environment. For example, air quality sensors 120 can send a signal to the dust collector monitoring device 152, which in turn may process the signals and/or send information regarding the signals onto a data communication network for transmission to a remote location. While FIG. 11 shows wireless communication to wireless communication tower 1120, it will be appreciated that communication with a data communication network can also be provided through a repeater device, router, or similar device located at the work site.

Referring now to FIG. 12, a block diagram of components of a dust collector monitoring device 152 is shown in accordance with various embodiments herein. It will be appreciated that a greater or lesser number of components can be included with various embodiments and that this schematic diagram is merely illustrative. In addition, some or all of the components described with respect to FIG. 12 can be integrated with or distributed across other devices or components of the system herein. The monitoring device 152 can include a housing 1202 and a control circuit 1204.

The control circuit 1204 can include various electronic components including, but not limited to, a microprocessor, a microcontroller, a FPGA (field programmable gate array) chip, an application specific integrated circuit (ASIC), or the like.

In various embodiments, the monitoring device 152 can include a first pressure sensor 1206 (as used herein, reference to a pressure sensor shall include a pressure transducer unless the context dictates otherwise) and a first fluid conduit 852 including an internal portion 1208 and an external portion 1210. The first fluid conduit can be in fluid communication with the dirty air chamber 926.

In various embodiments, the monitoring device 152 can include a second pressure sensor 1214 and a second fluid conduit 854 including an internal portion 1216 and an external portion 1218. The second fluid conduit can be in fluid communication with the clean air chamber 924.

In various embodiments, the monitoring device 152 can include a third pressure sensor 1222 and a third fluid conduit 856 including an internal portion 1224 and an external portion 1226. The third fluid conduit can be in fluid communication with the compressed air manifold 948. As such, the third fluid conduit can be in fluid communication with a compressed gas supply.

Pressure sensors herein can be of various types. Pressure sensors can include, but are not limited to, strain gauge type pressure sensors, capacitive type pressure sensors, piezoelectric type pressure sensors, and the like. In some embodiments, pressure sensors herein can be MEMS-based pressure sensors.

The processing power of the control circuit 1204 and components thereof can be sufficient to perform various operations described herein and various data processing/signal processing operations including, but not limited to averaging, time-averaging, statistical analysis, normalizing, aggregating, sorting, deleting, traversing, transforming, condensing (such as eliminating selected data and/or converting the data to a less granular form), compressing (such as using a compression algorithm), merging, inserting, time-stamping, filtering, discarding outliers, calculating trends and trendlines (linear, logarithmic, polynomial, power, exponential, moving average, etc.), predicting filter element EOL (end of life), identifying an EOL condition, predicting performance, predicting costs associated with replacing filter elements vs. not-replacing filter elements, executing computational fluid dynamics calculations, calculating air velocity vectors, performing “what-if” calculations to test the predicted effects of possible air contamination mitigation solutions (such as adding and/or moving air contaminant removal equipment), and the like.

In some embodiments, the monitoring device 152 can include additional sensors, such as air contamination sensor(s) 1230 to detect air contamination in or around the monitoring device 152. For example, the monitoring device 152 can include a particulate sensor, a gas sensor, or the like. Exemplary sensors are described in greater detail below.

In various embodiments, the monitoring device 152 can include a power supply circuit 1232. In some embodiments, the power supply circuit 1232 can include various components including, but not limited to, a battery 1234, a capacitor, a power-receiver such as a wireless power receiver, a transformer, a rectifier, and the like.

In various embodiments the monitoring device 152 can include an output device 1236. The output device 1236 can include various components for visual and/or audio output including, but not limited to, lights (such as LED lights), a display screen, a speaker, and the like. In some embodiments, the output device can be used to provide notifications or alerts to a system user such as current system status, an indication of a problem, a required user intervention, a proper time to perform a maintenance action, or the like.

In various embodiments, the control circuit 1204 generates a user interface output. In some embodiments, the output device 1236 can include a display screen upon which a user interface herein can be displayed. In other embodiments, the control circuit 1204 generates a user interface output that can be transmitted for display on another device, such as a mobile computing device, a stationary computing device, or the like. In various embodiments, the user interface output can include at least one including at least one of graphical objects representing the air quality determining features, values representing air quality measures, and a graphical representation of the physical indoor environment. Real time measurements from sensors can also be displayed graphically on the user interface. In some embodiments, such measurements can be overlayed onto a representation of the physical environment being monitored such that the location in the representation of the physical environment matches the actual location of sensors within the actual physical environment. Notification and/or alerts generated by the system herein can also be displayed graphically on the user interface.

In various embodiments the monitoring device 152 can include memory 1238 and/or a memory controller. The memory can include various types of memory components including dynamic RAM (D-RAM), read only memory (ROM), static RAM (S-RAM), disk storage, flash memory, EEPROM, battery-backed RAM such as S-RAM or D-RAM and any other type of digital data storage component. In some embodiments, the electronic circuit or electronic component includes volatile memory. In some embodiments, the electronic circuit or electronic component includes non-volatile memory. In some embodiments, the electronic circuit or electronic component can include transistors interconnected to provide positive feedback operating as latches or flip flops, providing for circuits that have two or more metastable states, and remain in one of these states until changed by an external input. Data storage can be based on such flip-flop containing circuits. Data storage can also be based on the storage of charge in a capacitor or on other principles. In some embodiments, the non-volatile memory 1238 can be integrated with the control circuit 1204.

In various embodiments the monitoring device 152 can include a clock circuit 1240. In some embodiments, the clock circuit 1240 can be integrated with the control circuit 1204. While not shown in FIG. 12, it will be appreciated that various embodiments herein can include a data/communication bus to provide for the transportation of data between components. In some embodiments, an analog signal interface can be included. In some embodiments, a digital signal interface can be included.

In various embodiment the monitoring device 152 can include a communications circuit 1242. In various embodiments, the communications circuit can include components such as an antenna 1244, amplifiers, filters, digital to analog and/or analog to digital converters, and the like.

In various embodiments, monitoring devices 152 herein are designed so that they can operate using only a battery for power and not deplete the battery for a long period of time such as weeks, months, or even years. As such, in various embodiments operations of the monitoring device 152 can be optimized to conserve energy consumption. However, in other embodiments, monitoring devices 152 herein can operate on a standard AC current source.

Model Calculations, Validation, and Updates

The air-mass flow distribution inside of a structure is caused by pressure differences as evoked by wind, thermal buoyancy, ventilation systems (typically including fans), and the like, or a combination of those. Inner airflow pathways (such as airflow ducts), openings in a building shell, and the like also influence air flow.

A model set of data can be used to generate a digital representation of air flow within a particular indoor environment (an airflow model). In various embodiments, the digital representation can include a plurality of vectors indicating both air velocities and directions. The model set of data can include the physical assumptions needed for modeling.

In some embodiments, aspects of computational fluid dynamics (CFD) can be applied by the system in generating a model of airflow using the model set of data. Computational fluid dynamics is a simulation technique that can used to model both spatial and temporal field solutions of fluid pressure, temperature and velocity. Computation fluid dynamics can include applying flow equations and/or algorithms based on principles of conservation laws (conversation of mass, conservation of linear momentum, conservation of energy), continuum conservation laws, Navier-Stokes equations (compressible and incompressible), Euler equations, Boussinesq equations, Reynolds-average Navier-Stokes equations, and the like. In some embodiments, CFD modeling/analysis can be performed using software packages such as ANSYS, OpenFOAM, PIPESIM, SimScale, COMSOL, Autodesk CFD, SU2, FLOW-3D, Altair HyperWorks, SimulationX, and the like. In some embodiments, such software and/or portions of such software such as open source portions can be integrated with systems herein. In some embodiments, the system can model the dispersion of contaminants within the indoor environment by applying the Eulerian concept to create a Eulerian contaminant dispersion model. Alternatively, a Lagrangian model can be applied to model the dispersion of contaminants within the indoor environment. Other approaches that can be applied herein include Gaussian dispersion models.

Such digital representations of airflow and/or contaminant dispersion can be used and/or generated by systems herein in various operations. For example, in various embodiments the system executes airflow modeling calculations using the model set of data reflecting the air quality determining features and estimates air quality values at discrete geolocation points within the physical indoor environment. Further operations can also be executed as described elsewhere herein such as determining whether changes to the air quality determining features or the operating parameters thereof are needed in a present state or a future state to maintain one or more predetermined air quality standards and generating one or more recommendations regarding maintaining or enhancing air quality within the physical indoor environment.

In various embodiments, the system can be configured to validate the model set of data and/or the model itself by evaluating sensor data regarding air quality in comparison with expected measures of air quality. By way of example, if the model indicates that air contamination is expected to travel (based on air velocity vectors or another aspect of the model) from a first zone including a sensor to a second zone including another sensor, but the second zone never senses air contamination consistent with what would be expected to be observed based on what was sensed in the first zone, then this can indicate that the model is at least partially invalid. Conversely, if what is sensed at the second zone is consistent with that observed in the first zone, then this can serve as validation of the model within the particular physical environment. As such, systems herein can be configured to validate the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

If the model is deemed to likely be invalid, then the system can update the model set of data and/or the model itself in order to account for the empirical observations made with the sensors. For example, the air velocity vectors can be changed (in terms of velocity and/or direction) in order to account for the empirical observations of the sensors. Further, the model set of data itself can be changed or updated, such as to reflect the presence of a new element in the environment that impacts airflow and/or air contamination. Thus, the system is configured to update the model set of data and/or the model itself by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

Similarly, in some cases, in addition to or instead of adjusting the model, the system can compare the estimated air quality values at discrete geolocation points against sensor data related to the same discrete geolocation points and adjusts further estimates based on the compared values.

Exposure Tracking

In some scenarios, the significance of exposure to air contaminants can relate to the accumulated exposure over time wherein the intensity of exposure and the total amount of time being exposed to the same both impact potential exposure effects. Systems herein can track estimated air quality at discrete geolocations within a physical indoor environment over time in order to determine exposure values relating to the intensity of exposure as well as the accumulated exposure. For example, the system can be configured to calculate estimated exposure values to airborne contaminants associated discrete geolocations or zones within the physical indoor environment longitudinally over time.

In various embodiments systems herein can calculate an Air Quality Index (AQI) value. For each pollutant an AQI value of 100 generally corresponds to an ambient air concentration that equals the level of the short-term U.S. ambient air quality standard for protection of public health. AQI values at or below 100 are generally thought of as satisfactory. When AQI values are above 100, air quality is unhealthy. The U.S. EPA establishes an AQI for five major air pollutants regulated by the Clean Air Act (ground-level ozone, particulates (including PM2.5 and PM10), CO, SO₂, and NO₂. For example, an AQI of 100 for ozone corresponds to approximately 0.070 ppm over an 8-hour period. An AQI of 100 for particulate matter corresponds to approximately 35.4 μg/m³PM2.5 over a 24-hour period or 154 μg/m³PM10 over a 24-hour period. An AQI of 100 for CO corresponds to approximately 9.4 ppm over an 8-hour period. An AQI of 100 for SO₂corresponds to approximately 75 ppb over a 1-hour period. An AQI of 100 for NO²corresponds to approximately 100 ppb over a 1-hour period.

AQI can be calculated and/or approximated using the following formula:

$I_{p} = \frac{I_{Hi} - I_{Lo}}{{BP}_{HI} - {BP}_{Lo}} (C_{p} - {BP}_{Lo}) + I_{Lo}$

Wherein Ip=the index for pollutant p; Cp=the truncated concentration of pollutant p; BP_HI=the concentration breakpoint that is greater than or equal to Cp; BP_LO=the concentration breakpoint that is less than or equal to Cp; I_HI=the AQI value corresponding to BP_HI; I_LO=the AQI value corresponding to BP_LO.

Change Tracking and Alerting

Changes in air contamination values can be particularly significant for plant operators as it may indicate an acute circumstance that requires a rapid response for mitigation. For example, a gas or fuel leak may occur very suddenly and result in rapid adverse changes in air quality. As such, the kinetics of an air quality change can be characterized by systems herein and provided with notifications or alerts herein. In addition, the system can evaluate the kinetics of an air quality change when determining a likely source of air contamination.

In some embodiments, operations to generate one or more outputs herein can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality has worsened unexpectedly, such as exceeded a threshold value for airborne contaminants. In some embodiments, the system can accept an input (such as from a system user or another system) so that a change in air quality is expected, in which case notifications or alerts regarding the change can be turned off temporarily.

In some embodiments, operations to generate one or more outputs herein can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality has decreased by an amount exceeding a threshold value over a period of time and issuing a notification regarding the identified one or more discrete geolocations or zones.

Knowledge of the particular location or zone can be important in identifying a likely source of the air contamination. In some embodiments, the operations to generate one or more outputs herein can include identifying a likely source of air contamination based on information regarding one or more discrete geolocations or zones within the physical indoor environment wherein air quality has worsened unexpectedly, the sensor data regarding air quality, and the stored set of model data. In some embodiments, the system can store information regarding the location and type of elements within the monitored environment. In this manner, spatial information regarding air contaminants can be cross-referenced with a listing of elements (pieces of equipment, etc.) in the environment to determine which elements are in spatially relevant location and therefore could be a source of the air contamination.

Sensors

Various sensors can be used with systems herein. In some embodiments, the system itself can include one or more sensors. In some embodiments the system can be configured to receive data from one or more sensors. In various embodiments, one or more sensors can be in electronic communication with a sensor channel interface (physical or software based) of the system. In various embodiments, one or more sensors can be in wireless electronic communication with other components of the system.

In various embodiments, sensor data regarding air quality generated and/or used by systems herein can include, but is not limited to, of levels of particulates and/or sizes thereof (such as PM2.5 or PM10), levels of VOCs, levels of CO₂, levels of CO, levels of sulfur compounds such as sulfur dioxide, levels of nitrogen compounds such as ammonia, nitric oxide, nitrogen dioxide, levels of various metals and metal compounds, and the like. Sensor data can also include data types useful for calculations to be made by the system including, but not limited to, temperature, pressure, air flow speed, air flow direction, light (such as ambient light), other optical data, acoustic data, and the like.

Sensors herein can be based on various principles including optical sensors based on light scattering or other optical phenomena, electrochemical based sensors, metal oxide sensors, photoionization detector (PID) sensors, and the like. Sensors herein can include both fast-response sensors as well as slow-response sensors. However, it will be appreciated that fast-response sensors offer benefits in terms of being able to provide information as rapidly as possible. Sensors herein can sample at various rates. In some embodiments, sensors herein can have a relatively high sample rate. In other embodiments, such as where conditions are not expected to change rapidly, sensors can have a relatively low sample rate to reduce power consumption and/or limit the amount of data generated.

Methods

Many different methods are contemplated herein, including, but not limited to, methods of making, methods of using, and the like. Aspects of system/device operation described elsewhere herein can be performed as operations of one or more methods in accordance with various embodiments herein.

In various embodiments, operations described herein and method steps can be performed as part of a computer-implemented method executed by one or more processors of one or more computing devices. In various embodiments, operations described herein and method steps can be implemented instructions stored on a non-transitory, computer-readable medium that, when executed by one or more processors, cause a system to execute the operations and/or steps.

In an embodiment, a method of monitoring indoor air quality is included. The method can include storing a model set of data reflecting information on air quality determining features within a physical indoor environment, receiving sensor data regarding air quality at discrete points within the physical indoor environment, and evaluating the sensor data regarding air quality and performing operations to generate one or more outputs relating to air quality within the physical indoor environment.

In an embodiment, the method can further include validating the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality. In an embodiment, the method can further include validating the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

In an embodiment, the method can further include updating the model set of data by evaluating the sensor data regarding air quality in comparison with expected measures of air quality at discrete points within the physical indoor environment.

In an embodiment, the method can further include tracking estimated air quality at discrete geolocations within the physical indoor environment over time. In an embodiment, the method can further include calculating estimated exposure values to airborne contaminants associated with a presence at discrete geolocations or zones within the physical indoor environment longitudinally over time.

In an embodiment, the operations to generate one or more outputs can include executing airflow modeling calculations using the model set of data reflecting the air quality determining features and estimating air quality values at discrete geolocation points within the physical indoor environment.

In an embodiment, the operations to generate one or more outputs can include generating one or more recommendations regarding maintaining or enhancing air quality within the physical indoor environment. In an embodiment, the operations to generate one or more outputs can include evaluating the sensor data regarding air quality to determine whether changes to the air quality determining features or the operating parameters thereof are needed in a present state or a future state to maintain one or more predetermined air quality standards.

In an embodiment of the method, the predetermined air quality standards include at least one selected from the group consisting of levels of particulates, levels of VOCs, levels of CO, levels of CO₂, levels of NO₂, levels of SO₂, or other gases or contaminants.

In an embodiment of the method, the predetermined air quality standards include an air quality index (AQI) value.

In an embodiment, the air quality determining features can include at least one selected from the group consisting of airborne contaminant removal devices, air flow generating devices or systems, airborne contaminant generating devices or zones, and air exchange features. In an embodiment, the airborne contaminant removal devices can include dust collectors. In an embodiment, the airborne contaminant removal devices can include VOC removal devices.

In an embodiment, the model set of data can include at least one selected from the group consisting of an air volume of the physical indoor environment and a physical configuration of the indoor environment.

In an embodiment, the sensor data regarding air quality can include at least one selected from the group consisting of current levels of levels of particulates, levels of VOCs, levels of CO, levels of CO₂, levels of NO₂, levels of SO₂, or other gases or contaminants, and current temperature.

In an embodiment, the method can further include generating a user interface output. In an embodiment, the user interface output can include at least one selected from the group consisting of graphical objects representing the air quality determining features, values representing air quality measures, and a graphical representation of the physical indoor environment.

In an embodiment, the operations to generate one or more outputs can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality has worsened unexpectedly. In an embodiment, the operations to generate one or more outputs can include identifying one or more discrete geolocations or zones within the physical indoor environment wherein air quality has decreased by an amount exceeding a threshold value over a period of time and issuing a notification regarding the identified one or more discrete geolocations or zones.

In an embodiment, the operations to generate one or more outputs can include identifying a likely source of air contamination based on information regarding one or more discrete geolocations or zones within the physical indoor environment wherein air quality has worsened unexpectedly, the sensor data regarding air quality, and the stored set of model data.

It should be noted that, as used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the content clearly dictates otherwise. It should also be noted that the term “or” is generally employed in its sense including “and/or” unless the content clearly dictates otherwise.

It should also be noted that, as used in this specification and the appended claims, the phrase “configured” describes a system, apparatus, or other structure that is constructed or configured to perform a particular task or adopt a particular configuration. The phrase “configured” can be used interchangeably with other similar phrases such as arranged and configured, constructed and arranged, constructed, manufactured and arranged, and the like.

All publications and patent applications in this specification are indicative of the level of ordinary skill in the art to which this invention pertains. All publications and patent applications are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated by reference.

As used herein, the recitation of numerical ranges by endpoints shall include all numbers subsumed within that range (e.g., 2 to 8 includes 2.1, 2.8, 5.3, 7, etc.).

The headings used herein are provided for consistency with suggestions under 37 CFR 1.77 or otherwise to provide organizational cues. These headings shall not be viewed to limit or characterize the invention(s) set out in any claims that may issue from this disclosure. As an example, although the headings refer to a “Field,” such claims should not be limited by the language chosen under this heading to describe the so-called technical field. Further, a description of a technology in the “Background” is not an admission that technology is prior art to any invention(s) in this disclosure. Neither is the “Summary” to be considered as a characterization of the invention(s) set forth in issued claims.

The embodiments described herein are not intended to be exhaustive or to limit the invention to the precise forms disclosed in the following detailed description. Rather, the embodiments are chosen and described so that others skilled in the art can appreciate and understand the principles and practices. As such, aspects have been described with reference to various specific and preferred embodiments and techniques. However, it should be understood that many variations and modifications may be made while remaining within the spirit and scope herein.

INDOOR AIR QUALITY MONITORING SYSTEM

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