WO2023084690A1

WO2023084690A1 - Information processing device, information processing method, and program

Info

Publication number: WO2023084690A1
Application number: PCT/JP2021/041541
Authority: WO
Inventors: 英孝宮▲崎▼; 昌彦金子
Original assignee: 日本未来科学研究所合同会社
Priority date: 2021-11-11
Filing date: 2021-11-11
Publication date: 2023-05-19

Abstract

The purpose of the present invention is to calculate and present an indicator of ambient air quality in real time on the basis of a plurality of measurement items.　An ambient air monitoring device 10 is provided with a processing unit configured to: acquire ambient air information, which is a plurality of types of measurement data regarding properties and components of ambient air, together with measurement location information, which is information indicating the location where the ambient air information was measured; store a correlation between the acquired ambient air information and an ambient air indicator, which is information indicating the quality of the ambient air; acquire the correlation from a correlation storage unit and apply the correlation to the ambient air information to calculate the ambient air indicator; and output the calculated ambient air indicator in a prescribed format.

Description

Information processing device, information processing method and program

The present invention relates to an information processing device, an information processing method, and a program.

With infectious diseases becoming a global social problem, there is growing interest in the quality of the air in the environment where people breathe on a daily basis. Regarding air quality, for example, Japanese laws and regulations (Industrial Safety and Health Law, Office Sanitation Standard Regulations (Air Conditioning Equipment)) stipulate the amount of airborne dust, carbon monoxide, carbon dioxide, formaldehyde, room temperature (temperature), and relative humidity. Standard values to be complied with for each item are stipulated, and it is required to periodically measure and check whether the standard values are exceeded.

In this regard, for example, Patent Document 1 discloses signal communication between a carbon dioxide sensor that detects an instantaneous value of the carbon dioxide concentration in the air in the indoor environment of a building, a control unit, and the carbon dioxide sensor and the control unit. A method is proposed for controlling the air quality in the indoor environment of a building by means of a system comprising a communication unit and a storage unit.

Japanese Patent Application Laid-Open No. 2021-117999

However, Patent Document 1 only deals with carbon dioxide in the indoor environment, and does not mention measuring or controlling other measurement items that affect air quality. In addition, even if all stipulated items are regularly checked against the standard values, there is a high level of concern about the existence of pathogens such as viruses that cause infectious diseases in the air in the environment. However, there is a problem that the information that can be an important index for human infection prevention behavior is not provided at all.

One of the objects of the present invention is to provide an information processing device, an information processing method, and a program capable of calculating and presenting in real time an index indicating environmental air quality based on a plurality of measurement items.

An information processing apparatus according to one aspect of the present invention provides environmental air information, which is a plurality of types of measurement data relating to properties and components of environmental air, together with measurement position information, which is information indicating the location where the environmental air information was measured. acquire, hold a correlation between the acquired environmental air information and an environmental air index that is information indicating the quality of the environmental air, acquire the correlation from the correlation holding unit, and store the environmental air A processing unit configured to calculate the ambient air index by applying the correlation to the information and to output the calculated ambient air index in a predetermined format.

According to the present invention, an index indicating environmental air quality can be calculated and presented in real time based on multiple measurement items.

1 is a system configuration diagram illustrating the configuration of an environmental air monitoring system according to one embodiment of the present invention; FIG. 1 is a block diagram illustrating the configuration of hardware and functional blocks of a sensor device according to an embodiment of the present invention; FIG. 1 is a block diagram illustrating the configuration of hardware and functional blocks of an environmental air monitoring device according to an embodiment of the present invention; FIG. 2 is a block diagram illustrating the configuration of hardware and functional blocks of a terminal device according to one embodiment of the present invention; FIG. 4 is a flowchart illustrating the flow of environmental air index calculation processing of the environmental air monitoring device in one embodiment of the present invention. FIG. 4 is a diagram showing a configuration example of inference data in one embodiment of the present invention; FIG. 4 is a diagram showing an example of a management screen of the environmental air monitoring device according to one embodiment of the present invention; FIG. 4 is a diagram showing an example of a management screen of the environmental air monitoring device according to one embodiment of the present invention; FIG. 4 is a diagram showing an output display example of the environmental air monitoring device in one embodiment of the present invention; FIG. 4 is a diagram showing another output display example of the environmental air monitoring device in one embodiment of the present invention; FIG. 4 is a block diagram illustrating the configuration of hardware and functional blocks of an environmental air monitoring device according to another embodiment of the present invention; 9 is a flow chart illustrating the flow of learning processing of the environmental air monitoring device in another embodiment of the present invention; 9 is a flowchart illustrating the flow of environmental air index calculation processing of the environmental air monitoring device in another embodiment of the present invention;

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, the present invention will be described in line with its embodiments with reference to the accompanying drawings.
<First embodiment>
[Overall Configuration of Environmental Air Monitoring System]
First, the overall configuration of an environmental air monitoring system according to one embodiment of the present invention will be described. FIG. 1 is a block diagram illustrating the overall configuration of an environmental air monitoring system 1 according to one embodiment of the invention. The environmental air monitoring system 1 includes an environmental air monitoring device 10 , a sensor device 20 and a terminal device 30 . The environmental air monitoring device 10 and the sensor device 20 and the environmental air monitoring device 10 and the terminal device 30 are communicably connected by a communication network 40 . The communication network 40 includes communication lines such as the Internet, WAN, LAN, and dedicated lines, and is configured to establish connection by wire or wireless communication as appropriate. The environmental air monitoring device 10, which is the information processing device of the present invention, may be configured as a cloud computing system composed of a plurality of computers (nodes) on the communication network 40 instead of an independent computer. In that case, the data processing that realizes the functions of the environmental air monitoring device 10, which will be described later, can be distributed in the cloud. In addition, various parameters and data used for the data processing can be appropriately distributed and stored in storage distributed in the cloud.

The environmental air monitoring device 10 receives a plurality of types of sensor measurement data sent from a plurality of sensor devices 20 connected via a communication network 40, and the sensor devices 20 are installed using predetermined data processing to be described later. Calculate an index for the air quality of the ambient air in a location where In addition, the environmental air monitoring device 10 acquires event information about various events occurring in various places from other databases through the communication network 40, and uses it for calculating the index. Specifically, this event information is, for example, information on the occurrence of infected persons of a specific infectious disease, its scale (the number of infected persons), and the condition of the infected persons, but is not necessarily limited to this.

The sensor device 20 is a device that is installed at a place where the air quality of the environmental air should be evaluated, acquires a predetermined type of sensor measurement data regarding air, and has a function of sending it to the environmental air monitoring device 10 via the communication network 40. be. It may be installed indoors or outdoors, and may be carried by a person such as a delivery man who patrols the city.

The terminal device 30 has a function of receiving output data including various indices created by the environmental air monitoring device 10 based on sensor measurement data of the sensor device 20 and outputting it to a display screen or the like. An application that operates as a client of the environmental air monitoring device 10 may be installed in the terminal device 30 .

Next, configurations of the environmental air monitoring device 10, the sensor device 20, and the terminal device 30 will be described.
[Structure of sensor device 20]
FIG. 2 shows a functional block diagram of a configuration example of the sensor device 20 according to the present embodiment. The sensor device 20 illustrated in FIG. 2 is a sensor device for measuring various data related to air quality, and includes a processor 21, a memory 22, a sensor group 23, a position signal receiver 24, a data IF unit 25, and a communication device. A portion 26 is provided. The processor 21 performs predetermined data processing on various sensor measurement data measured by the sensor group 23 and executes various programs for controlling the overall operation of the sensor device 20 . Processor 21 may be, for example, a CPU.

The memory 22 is a storage device that stores various programs executed by the processor 21 and various data used for executing the programs, and includes hardware such as ROM, RAM, and flash memory.

The sensor group 23 includes sensor devices that measure sensor measurement data that are the basis for the environmental air monitoring apparatus 10 of the present embodiment to calculate various air quality indices. In this embodiment, temperature and humidity sensor 231, carbon dioxide (CO ₂ ) sensor 232, carbon monoxide (CO) sensor 233, ozone (O ₃ ) sensor 234, nitrogen dioxide (NO ₂ ) sensor 235, volatile organic compounds ( VOC) sensor 236 , formaldehyde (CH ₂ O) sensor 237 , and particulate matter (PM) sensor 238 . For the temperature/humidity sensor 231, for example, an analog voltage output sensor module can be used. The _CO2 sensor 232, CO sensor 233, _O3 sensor 234, and _NO2 sensor 235 are devices that measure the _CO2 concentration, CO concentration, _O3 concentration, and _NO2 concentration in the air, respectively. The device may be a semiconductor type or any measurement type device. VOC sensor 236 measures the total amount of VOCs present in the air, for example, by non-dispersive infrared analysis. The CH ₂ O sensor 237 also measures the CH ₂ O concentration in the air in a similar manner, for example. The PM sensor 238 classifies the concentration of particulate matter in the air into PM1.0, PM2.5, and PM10 according to its size, and measures it optically using scattered light, for example. The various sensors used in the sensor group 23 described above are not limited to the devices of the types illustrated, and devices that can be used in this embodiment can be appropriately adopted.

The position signal receiving unit 24 is a processing unit that receives information about the position of the sensor device 20 from the outside, and can be configured as a satellite radio wave receiving module of the global navigation satellite system (GNSS). It is conceivable that the sensor device 20 is installed indoors in many cases. By obtaining altitude information in addition to plane coordinates, it is possible to determine on which floor of a specific building the sensor device 20 is located.

The data IF unit 25 has a function of transmitting sensor measurement data measured by the sensor group 23 and processed by a program stored in the memory 22 to the communication network 40 via the communication unit 26, It is an interface circuit having functions such as receiving various control data to the sensor device 20 .

The communication unit 26 is a communication module that controls the communication function of the sensor device 20 , and has the function of transmitting data from the data IF unit 25 to the communication network 40 and transferring data received from the communication network 40 to the data IF unit 25 . have The communication unit 26 is implemented as hardware such as a mobile communication module, a wireless LAN module such as Wi-Fi, and a Near Field Communication (NFC) module such as Bluetooth (registered trademark).

Next, each program stored in the memory 22 of the sensor device 20 will be described. The memory 22 stores functional units such as a sensor control unit 221 , a sensor data processing unit 222 , a position information acquisition unit 223 and a data input/output unit 224 .

The sensor control unit 221 has a function of controlling the sensors included in the sensor group 23 in response to instructions from the environmental air monitoring device 10, such as activation and deactivation of each sensor, requests for sensor status, and the like. The sensor data processing unit 222 executes processing such as correction and calibration of measurement data output from each sensor of the sensor group 23 . The position information acquisition unit 223 determines whether the sensor device 20 exists based on the information regarding the position of the sensor device 20 such as the coordinate information from the GNSS received by the position signal reception unit 24 or the positioning result based on the position of the wireless LAN base station. Information about the position of the object, such as plane coordinates and altitude, is calculated. The data input/output unit 224 has a function of performing data transmission/reception processing between each program and the outside. Note that the configuration of the program that implements the functions of the sensor device 20 is not necessarily limited to that illustrated in FIG.

[Configuration of Environmental Air Monitoring Device 10]
Next, a configuration example of the environmental air monitoring device 10 will be described. FIG. 3 is a functional block diagram showing a configuration example of the environmental air monitoring device 10 of this embodiment. An environmental air monitoring device 10 as an information processing device illustrated in FIG.

The processor 11 is hardware that realizes the overall functions of the environmental air monitoring device 10 by executing each program stored in the memory 12, and can be configured as a CPU, for example.

The memory 12 is composed of storage devices such as RAM, ROM, flash memory, etc., and stores various programs for realizing the functions of the environmental air monitoring device 10 .

The auxiliary storage unit 13 stores inference data 131 used by the programs stored in the memory 12, result data calculated as a result of executing these programs, and the like. The auxiliary storage unit 13 can be configured with a storage device such as a semiconductor drive (SSD) or hard disk drive (HDD). All or part of the programs stored in the memory 12 may be stored in the auxiliary storage unit 13 in advance and read out from the auxiliary storage unit 13 to the memory 12 when the processor 11 executes them.

The input/output unit 14 includes input devices such as a touch panel, keyboard, mouse, and microphone for receiving data input operations to the environmental air monitoring device 10, and output devices such as an appropriate format display and speakers.

The data IF unit 15 is an interface circuit that has a function of transferring sensor measurement data received from the sensor group 23 to each program in the memory 12, a function of sending various control data from each program to the sensor device 20, and the like. The communication unit 16 is a communication module that controls the communication function of the environmental air monitoring device 10 , sends data from the data IF unit 15 to the communication network 40 , and transfers data received from the communication network 40 to the data IF unit 15 . It has the function to The communication unit 16 is implemented as hardware such as a mobile communication module, a network interface card (NIC), or a wireless LAN module.

Next, the functions of the environmental air monitoring device 10 will be explained. The functions of the environmental air monitoring device 10 are realized by the processor 11 executing the inference unit 121, the index calculation unit 122, the output display control unit 123, and the data input/output unit 124, which are programs stored in the memory 12. be. The environmental air monitoring device 10 of the present embodiment combines various sensor measurement data collected from the sensor device 20 and the position information of the sensor device 20, and event information collected from an external database or the like via the communication network 40. Based on this, an index representing the air quality of the ambient air at the location of each sensor device 20 is calculated and output.

The inference unit 121 has a function of receiving sensor measurement data acquired from the sensor devices 20 and position information of the installation location of the sensor device 20 from each sensor device 20 and applying a predetermined rule to execute inference based on the input information. have.

FIG. 6A shows a conceptual model of inference data in this embodiment. In this embodiment, fuzzy inference is used to derive the air quality index from the sensor measurement data. The conceptual model illustrated in FIG. 6A is the membership function applied to this fuzzy reasoning.

In this embodiment, a comprehensive air quality index, which is an index indicating the comprehensive air quality at the measurement target location, is calculated. In addition, in the present embodiment, infection with a pathogenic virus such as the novel coronavirus is assumed as the specific event. As an index that quantitatively indicates the risk of viral infection, the virus presence probability, which is an index that indicates the probability that pathogens, including the new coronavirus, exist in the location (space) being measured, is being measured. An infection risk degree, which is an index representing the degree of virus infection risk in a place (space), is adopted.

As an example, the comprehensive air quality index is based on the building environmental hygiene management standards applied when air conditioning equipment is installed in the Building Management Law, the amount of suspended dust (PM), CO, CO ₂ , CH ₂ Inference data are applied to measured data for O, temperature (room temperature), and relative humidity.

Based on conventional knowledge, it is assumed that the virus presence probability is higher when the CO ₂ concentration is relatively high and therewith the content of fine particles such as PM2.5 is relatively high. It is presumed that when the _CO2 concentration is high, there are more people in the space exhaling, and more PM in the air means more pathogens in the exhalation. This is because it is thought to indicate that virus-sized objects are included.

Based on conventional knowledge, the degree of infection risk is set to be high when both the CO ₂ concentration and PM content are relatively high under conditions where the relative humidity in the space to be measured is relatively high or low. . In addition, the risk of infection is set so that the higher the VOC concentration, the higher the risk of infection, since it is believed that the respiratory irritation caused by VOCs increases the risk of infection.

The membership function for fuzzy inference illustrated in FIG. 6 is set based on the above-described conventional knowledge. That is, among the sensor measurement data, the temperature and humidity for which preferred numerical ranges are defined are set so as to form a trapezoid with the preferred numerical ranges as upper sides. In addition, the lower the CO concentration, the CO ₂ concentration, the PM content, the CH ₂ O concentration, and the VOC concentration, the better the measurement data, so they are set linearly with a constant slope. As for the ozone concentration, it is generally considered that the lower the concentration, the better.

Note that the shape of the membership function applied to fuzzy inference shown in FIG. 6 is an example in this embodiment, and tuning such as changing the shape as appropriate according to each index obtained can be performed. For example, in a restaurant or the like that always handles fire indoors, it is conceivable to modify the membership function relating to the CO ₂ concentration.

Based on the inference result of the inference unit 121, the sensor measurement data received from each sensor device 20, and the location information, the index calculation unit 122 calculates the air quality of the environmental air in the location where each sensor device 20 is installed. Calculate the overall air quality index, which is an index for comprehensive evaluation, the virus presence probability at the location where the sensor is installed, and the degree of infection risk. The comprehensive air quality index is calculated as a numerical value in the range of 0 to 9.9, and the higher the numerical value, the poorer the air quality. The virus presence probability and the degree of infection risk are each represented by a numerical value between 0% and 100%. A specific index calculation method may be specified through normalization of each sensor measurement data, adjustment of a membership function, and the like.

The output display control unit 123 has a function of generating output display data using sensor measurement data, position information, and various index data calculated by the index calculation unit 122 .

The data input/output unit 124 has an interface function for inputting data such as sensor measurement data and position information used by the inference unit 121 and the index calculation unit 122, and outputting output screen data generated by the output display control unit 123. have

[Configuration of terminal device 30]
Next, a configuration example of the terminal device 30 will be described. FIG. 4 is a block diagram showing a configuration example of the terminal device 30 according to this embodiment. The terminal device 30 receives and displays various sensor measurement data, index data, etc. from the environmental air monitoring device 10 while communicating with the environmental air monitoring device 10 via the communication network 40, and also displays the data to the environmental air monitoring device 10. It is a terminal device that transmits a request for data update or the like. The terminal device 30 can be configured by, for example, a smart phone, a tablet terminal, or a personal computer having a communication function.

A terminal device 30 illustrated in FIG.

The processor 31 is hardware that realizes the overall functions of the terminal device 30 by executing each program stored in the memory 32, and can be configured as a CPU, for example.

The memory 32 is composed of storage devices such as RAM, ROM, and flash memory, and stores various programs for realizing the functions of the terminal device 30 . The auxiliary storage unit 33 stores data used by the programs stored in the memory 32, result data calculated as a result of executing the programs, and the like.

The auxiliary storage unit 33 can be composed of a storage device such as a semiconductor drive (SSD). All or part of the programs stored in the memory 32 may be stored in the auxiliary storage unit 33 in advance and read out from the auxiliary storage unit 33 to the memory 32 when the processor 11 executes them.

The input/output unit 34 includes input devices such as a touch panel, keyboard, mouse, and microphone for receiving data input operations to the terminal device 30, and output devices such as an appropriate format display and speakers.

The data IF section 35 is an interface circuit having a function of transferring data received from the environmental air monitoring device 10 to each program in the memory 32, a function of sending various control data from each program, and the like.

The communication unit 36 is a communication module that controls the communication function of the terminal device 30 , transmits data from the data IF unit 35 to the communication network 40 , and transfers data received from the communication network 40 to the data IF unit 35 . have a function. The communication unit 36 includes hardware such as a mobile communication module, a wireless LAN module, and an NFC module.

Next, each program stored in the memory 32 of the terminal device 30 will be described. The memory 32 includes an application 321 that causes the terminal device 30 to function as a client of the environmental air monitoring device 10 and a data input/output unit 322 . Note that the memory 32 may store other programs (not shown). Also, browser software installed in the terminal device 30 may be used as a client of the environmental air monitoring device 10 without using the application 321 .

The application 321 includes a communication control unit 3211, a request transmission unit 3212, and a screen display control unit 3213. The communication control unit 3211 provides a function of performing data transmission/reception processing between the application 321 and the environmental air monitoring device 10 . The request transmission unit 3212 provides a function of requesting transmission of various data from the application 321 to the environmental air monitoring device 10 . The screen display control unit 3213 provides a data output function to an output device such as a display of the input/output unit 34 based on the output screen data and the like received from the environmental air monitoring device 10 .

The data input/output unit 322 is an interface unit that provides data input/output processing functions to the application 321 .

[Inference based on sensor measurement data and calculation process of various indicators]
Next, the process of inference and calculation of various indexes based on sensor measurement data by the environmental air monitoring device 10 of this embodiment will be described. FIG. 5 shows a flow chart illustrating the process of calculating the inference and various indices. The data processing illustrated in FIG. 5 is data processing executed by the inference unit 121 and the index calculation unit 122 of the environmental air monitoring device 10, and is executed, for example, when the environmental air monitoring device 10 is started and at predetermined time intervals thereafter. can be made

When the processing flow for inference and calculation of various indices is started, first, in step S500, the inference unit 121 acquires sensor measurement data and position information from the sensor device 20 via the data input/output unit 124. These data can be temporarily stored in the auxiliary storage unit 13 .

In step S510, the inference unit 121 acquires the membership function as the inference data 131 from the auxiliary storage unit 13.

In step S520, the inference unit 121 applies a membership function as inference data to the acquired sensor measurement data and position information to perform fuzzy inference. Then, the index calculator 122 calculates the overall air quality index, the virus existence probability, and the infection risk degree from the fuzzy inference results.

In step S530, the index calculation unit 122 stores each calculated index in the auxiliary storage unit 13.

Based on the inference based on the above sensor measurement data and the calculation processing flow of various indices, the newly acquired sensor measurement data and the position information of the sensor device 20 are used to calculate the overall air quality index, virus presence probability, and infection risk degree related to the environmental air. It can be calculated, and it will be possible to objectively know the environmental air quality and the risk of infection with pathogenic viruses in the target location.

[Output display of various data]
Next, the form of data output including various indices calculated by the environmental air monitoring device 10 will be described.

FIG. 7A shows an example of a management screen output and displayed on the display device that constitutes the input/output unit of the environmental air monitoring apparatus 10. As shown in FIG. As shown in FIG. 7A, in the upper half of this management screen, the installation location and identification ID of the sensor device 20, the overall air quality index calculated from the measurement data at the corresponding installation location, and the infection risk are displayed in a table format. temperature, and virus presence probability, temperature (°C), humidity (RH%), CO concentration (ppm), _CO2 concentration (ppm), _O3 concentration (ppm), and PM2.5 content measured at the installation location Amounts (μg) are indicated. Further, a detail button is provided for each installation location, and by operating this button, detailed information about the corresponding installation location is displayed in the lower half of FIG. 7A. In the example of FIG. 7A, this detailed information includes a map of the vicinity of the installation location, the address and organization of the installation location, warning messages recorded for the installation location, notes about the warning message, temperature at the installation location, CO ₂ Concentration, including graphs showing changes in _O3 concentration over time. In this way, according to the management screen illustrated in FIG. 7A , it is possible to list the indicators and main measurement values regarding the air quality of the location where the sensor device 20 is installed, and the state requiring attention regarding the air quality. You can immediately determine where you are. Further, by operating the detail button, it is possible to obtain detailed information about a specific location, for example, a location determined to require attention regarding air quality, which can be used to find the cause and countermeasures for problems related to air quality.
FIG. 7B shows an example of another form of management screen output and displayed on the display device that constitutes the input/output unit of the environmental air monitoring apparatus 10 . As shown in FIG. 7B, in the upper half of this management screen, the installation location and identification ID (device ID) of the sensor device 20, the overall air quality index calculated from the measurement data at the corresponding installation location, the infection risk and the virus presence probability are displayed. A 3D map of the surroundings of the installation location is also displayed in the upper half so that the installation location of the sensor device 20 can be visually grasped. In addition, a switch is provided for turning on/off the power of the sensor device 20 and the number of revolutions of the electric fan from this management screen, and it is configured so that the change can be reflected by operating the action button.
In the lower half of the management screen illustrated in FIG. 7B, the temperature (° C.), humidity (RH%), _CO2 concentration (ppm), and PM2.5 content (μg) measured at the installation location are In the form of a round analog display meter, it is displayed with digital readings. Around the memory of each meter, an area display indicating the legal reference value corresponding to each measurement item is provided. For example, for _CO2 , up to 800 ppm is a safe area (e.g. blue band display), 800-1000 ppm is a caution area (e.g. yellow band display), and over 1000 ppm is a warning area (e.g. red band display). By displaying, it is possible to immediately understand what state the displayed measured value means. In addition, below each meter, the effect of the measurement item on air quality is described in text, and the standard values under related laws and regulations are also shown, so those who view the management screen can easily understand each measurement item and air quality. You can learn about the relationship with and the legal allowable range. In addition, in the management screen example of FIG. 7B, measurement items other than the four items illustrated can be displayed in the same form. In addition, for each measurement item, by operating the "graph" button, the circular meter display can be switched to a graph display showing changes in measured values over time. In this way, according to the management screen illustrated in FIG. 7B , it is possible to view the air quality indicators and main measurement values of the location where the sensor device 20 is installed substantially in real time. Locations requiring attention can be immediately determined.
It should be noted that the management screen examples of FIGS. 7A and 7B can be freely changed in terms of display items and display format based on the required specifications of the system. Templates for display items and display formats may be prepared in advance so that they can be changed at any timing.

FIG. 8 shows an output screen display example of the terminal device 30. FIG. In response to the request from the terminal device 30, the output display control section 123 of the environmental air monitoring device 10 generates output screen data and transmits it to the terminal device 30 that made the request.

On the output screen, the position information corresponding to the displayed measurement data (in the example of FIG. 8, “1F, Z Building, Y Town, X Ward”), the total spatial index, which is the calculated environmental air index, the degree of infection risk, and Temperature, _CO2 concentration, humidity, CO concentration, _NO2 concentration, _O3 concentration, PM2.5 content, VOC concentration as aerosol, sensor measurement data are displayed. The bottom graph shows the measurement history of _CO2 concentration over the last 24 hours. A text display field is provided near the center of the screen, and is configured to display an alert when the measured value exceeds a predetermined threshold value (for example, the legal allowable upper limit value). The example of FIG. 8 indicates that the CO ₂ concentration at the measurement point is at a level that requires ventilation. These display items are only examples, and other items may be displayed in place of or in addition to any of these items, or the number of display items may be reduced.

9 shows another display example of the output screen of the terminal device 30. FIG. FIG. 9 displays a map on the screen of the terminal device 30, and shows, on the map, the state of the environmental air at each point as seen from the environmental air index in 3D graphics. For example, in the example of FIG. 9, the environmental air condition is displayed in three levels of "GOOD", "FAIR", and "POOR". By tapping or mouse over each icon, the information of the point (for example, store name, building name, altitude (number of floors) of the measurement place, etc.) is displayed.

According to the output screen example described above, it is possible to know in detail the state of the environmental air in the location where the specific sensor device 20 is located, and to report the degree of risk of infectious disease infection in that location on an easy-to-understand scale. can. In addition, it is possible to inform intuitively which places are safe and secure in terms of environmental air on the map. In addition, since altitude information can be included in the location, even in a large-scale building such as a high-rise building, detailed locations including the floor on which the location is located can be presented.

<Second embodiment>
Next, an environmental air monitoring system 1 according to a second embodiment of the invention will be described. The configuration of the environmental air monitoring system 1 of this embodiment is similar to that of the first embodiment illustrated in FIG. The aspect of the index calculation processing regarding various environmental airs differs from that of the first embodiment. The configuration of the present embodiment will be described below with respect to the configuration different from that of the first embodiment.

[Configuration of Environmental Air Monitoring Device 10]
FIG. 10 is a functional block diagram illustrating a configuration example of the environmental air monitoring device 10 of this embodiment. The basic configuration of the environmental air monitoring device 10 illustrated in FIG. 10 is the same as that of the first embodiment illustrated in FIG. However, the program of the learning unit 121A is stored in the memory 12, and the learning data 131A used by the learning unit 121A and the trained model 132 generated by the learning unit 121A are stored in the auxiliary storage unit 13. Points are different.

In the environmental air monitoring device 10 of the present embodiment, the memory 12 stores the program of the learning unit 121A, and learning is performed using the learning data 131A, which is teacher data stored in the auxiliary storage unit 13.

The learning data 131A includes event information acquired from the outside via the communication unit 16 . In this embodiment, this event information is the occurrence of a cluster due to infection with a specific pathogenic virus. Event information is based on a combination of the location and date of occurrence of this cluster. In the learning data 131A, temperature, CO ₂ concentration, humidity, CO concentration, NO ₂ concentration, which are sensor measurement data at the relevant date and time of the sensor device 20 installed at the corresponding location, are associated with the information regarding the occurrence of the cluster. , O ₃ concentration, PM content, VOC concentration, and position information of the sensor device 20 are held. Furthermore, the total air quality index, the degree of infection risk, and the virus existence probability calculated using those measurement data are also associated. In this way, the learning data 131A is a combination of the date and time of occurrence of the cluster, the location, the corresponding sensor measurement data, and the calculated index value. Thereby, the relationship between cluster generation, sensor measurement data, and each index value is learned. In addition, it is assumed that information on the occurrence of clusters as event information will be obtained from materials published by the competent authorities.

The memory 12 stores the program of the learning unit 121A, and uses the learning data 131A to learn and learn the relationship between the set of sensor measurement data, position information, the presence or absence of cluster occurrence, and the number of infected people in the occurrence cluster. A finished model 132 is generated and stored in the auxiliary storage unit 13 .

The index calculation unit 122 is an index for comprehensively evaluating the air quality of the ambient air in the location where each sensor device 20 is installed based on the sensor measurement data received from each sensor device 20 and the position information. Calculate the overall air quality index. Also, the index calculation unit 122 calculates the infection risk level and the virus existence probability using the learned model 132 based on the sensor measurement data and the position information.

[Learning process]
Next, the learning process by the environmental air monitoring device 10 of this embodiment will be described. FIG. 11 shows a flowchart illustrating the learning process. The data processing illustrated in FIG. 11 is processing for generating the learned model 132 that is used when the index calculator 122 of the environmental air monitoring device 10 calculates an index related to environmental air. , and at predetermined time intervals thereafter.

When the learning process flow starts, first, in step S1000, the learning unit 121A acquires the learning data 131A stored in the auxiliary storage unit 13 via the data input/output unit 124.

In step S1010, the learning unit 121A generates a trained model 132 using the acquired learning data 131A. The learning unit 121A can typically be a deep learning engine having two or more hidden layers, but is not limited to this. In the present embodiment, the input to the learning unit 121A is a combination of the date and time of occurrence of the cluster, the location, the corresponding sensor measurement data, and the calculated index value, which constitute the learning data 131A.

In step S1020, the learning unit 121A stores the generated trained model 132 in the auxiliary storage unit 13.

According to the learning processing flow described above, the risk of infection with a specific pathogenic virus infection and the extent to which the virus is expected to exist in the environmental air are calculated from the newly acquired sensor measurement data and the position information of the sensor device 20. be able to

[Calculation of ambient air index]
Next, calculation processing of the ambient air index value based on the generated learned model 132 will be described. FIG. 12 is a flow chart illustrating the processing flow for calculating the ambient air index by the ambient air monitoring device 10 of this embodiment. The environmental air index is calculated by the index calculator 122 of the environmental air monitoring device 10 . The calculation timing can be, for example, when the environmental air monitoring device 10 is started and after every predetermined time. Alternatively, the time when it is determined that there is a change in the sensor measurement data or the position information acquired from the sensor device 20 may be used as the calculation timing.

When the index calculation unit 122 starts processing, first, sensor measurement data and position information are acquired from each sensor device 20 in step S1100.

In step S<b>1110 , the index calculation unit 122 acquires the learned model 132 stored in the auxiliary storage unit 13 via the data input/output unit 124 .

In step S1120, the index calculation unit 122 applies the learned model 132 to the acquired sensor measurement data and position information to calculate the environmental air index value.

In step S1130, the index calculation unit 122 outputs the calculated environmental air index value and ends the process.

According to the environmental air index calculation process described above, based on the sensor measurement data acquired from a specific sensor device 20, it is possible to calculate and output the index related to the environmental air at the location where the sensor device 20 is located.

The correlation between the sensor measurement data and the environmental air index value is a membership function representing the relationship between the sensor measurement data and the environmental air index value, and the membership function is applied to the obtained sensor measurement data to generate a fuzzy The ambient air index value may be calculated by performing inference.
In this way, a statistically appropriate environmental air index value can be calculated by fuzzy inference.

Collecting event information, which is information including the place where a predetermined event occurred and the content of the event, and measuring the place and date and time of the event occurrence related to the event information and measurement data of each sensor corresponding to the place and date and time A trained model is generated by learning big data obtained by associating a value with an environmental air index value corresponding to the measured value, and the measured value of each newly acquired sensor measurement data is used as the learned model By inputting into the model, the environmental air index value at the corresponding position may be calculated.
In this way, it is possible to accurately calculate the environmental air index value by retrieving cluster generation information from information sources on the Internet, etc., and learning the correlation between the sensor measurement data and the big data including the environmental air index value. can.

The sensor measurement data includes measurement data of at least one of temperature, humidity, CO ₂ , CO, O ₃ , NO ₂ , VOC, CH ₂ O, and PM, and the event information is a cluster for a predetermined infectious disease. Occurrence information, a correlation between the measured data and the cluster occurrence information may be derived to calculate the probability of cluster occurrence at the location where the new sensor measurement data is obtained.
In this way, cluster occurrence probabilities can be calculated and presented based on past data.

The ambient air index value and the measured value of measured data, including at least one of the sensor measured data, may be output and displayed, wherein the measured value of the sensor measured data is substantially displayed in the form of an analog indicating meter. may be output and displayed in real time.
In this way, the ambient air index value at each measurement location can be intuitively grasped almost in real time.

The environmental air index value or a phrase indicating the condition of the environmental air represented by the environmental air index value, and the measurement location of the measurement data used as the basis for the calculation of the environmental air index, are displayed in association with each other on a map, including altitude information. You can do it.
By doing so, it is possible to identify a detailed location including the number of floors in the building and know the state of the environmental air at that location.

According to the environmental air monitoring device 10 according to the present embodiment described above, it is possible to calculate and present an index indicating the quality of the environmental air in real time based on a plurality of measurement items.

The series of processes described above can be executed by hardware or by software. In other words, the functional configurations of FIGS. 2-4 and 10 are merely examples and are not particularly limited. That is, it suffices if the environmental air monitoring device 10 is provided with a function capable of executing the series of processes described above as a whole. is not limited to the example of Also, one functional block may be composed of hardware alone, software alone, or a combination thereof. The functional configuration in this embodiment is realized by a processor that executes arithmetic processing, and processors that can be used in this embodiment are composed of various single processing units such as single processors, multiprocessors, and multicore processors. In addition to these, it also includes combinations of these various processing devices and processing circuits such as ASICs (Application Specific Integrated Circuits) and FPGAs (Field-Programmable Gate Arrays).

When a series of processes is executed by software, the programs that make up the software are installed on a computer or the like from a network or recording medium. The computer may be a computer built into dedicated hardware. The computer may also be a computer capable of executing various functions by installing various programs, such as a general-purpose personal computer.

A recording medium containing such a program is not only constituted by a removable medium such as a USB memory that is distributed separately from the main body of the device in order to provide the program to the user, but is also preinstalled in the main body of the device and stored by the user. It consists of a recording medium, etc. provided to Removable media are composed of, for example, magnetic disks (including floppy disks), optical disks, or magneto-optical disks. Optical discs are composed of, for example, CD-ROMs (Compact Disk-Read Only Memory), DVDs (Digital Versatile Disks), Blu-ray (registered trademark) Discs (Blu-ray Discs), and the like. The magneto-optical disk is composed of an MD (Mini-Disk) or the like. Further, the recording medium provided to the user in a state of being pre-installed in the apparatus main body is composed of, for example, a ROM in which the program is recorded and a storage device such as a hard disk included in the

auxiliary storage units

13 and 33 .

In this specification, the steps of writing a program recorded on a recording medium are not only processes that are performed chronologically in that order, but also processes that are not necessarily chronologically processed, and that are performed in parallel or individually. It also includes the processing to be executed.

Although several embodiments of the present invention have been described above, these embodiments are merely examples and do not limit the technical scope of the present invention. The present invention can take various other embodiments, and it is also possible to combine the configurations of the above-described embodiment and modifications. Furthermore, various modifications such as omissions and substitutions can be made without departing from the gist of the present invention. These embodiments and modifications thereof are included in the scope and gist of the invention described in this specification and the like, and are included in the scope of the invention described in the claims and equivalents thereof.

1 Environmental Air Monitoring System 10 Environmental Air Monitoring Device 20 Sensor Device 30

Terminal Device

11, 21, 31

Processor

12, 22, 32

Memory

13, 33 Auxiliary Storage Section 121 Inference Section 121A Learning Section 122 Index Calculation Section 123 Output Display Control Section 131 Inference data 131A Learning data 132 Trained model

Claims

Acquiring environmental air information, which is a plurality of types of measurement data regarding the properties and components of the environmental air, together with measurement location information, which is information indicating the location where the environmental air information was measured;
holding a correlation between the acquired environmental air information and an environmental air index, which is information indicating the quality of the environmental air;
obtaining the correlation and calculating the ambient air index by applying the correlation to the ambient air information;
An information processing device comprising a processing unit configured to output the calculated ambient air index in a predetermined format.
The correlation is a membership function representing the relationship between the environmental air information and the environmental air index, and the processing unit applies the membership function to the acquired environmental air information to perform fuzzy inference. The information processing apparatus according to claim 1, wherein the ambient air index is calculated by:
The processing unit collects event information, which is information including the location where a predetermined event occurred and the content of the event,
The place and date of occurrence of the event related to the event information, the measured value of each measurement data constituting the environmental air information corresponding to the place and date, and the environmental air index corresponding to the measured value are associated. A trained model is generated by learning big data, and the measured values of each measurement data constituting the newly acquired environmental air information are input to the trained model to obtain an environmental air index at the relevant position. 2. The information processing apparatus according to claim 1, configured to calculate .
The plurality of types of measurement data includes measurement data of at least one of temperature, humidity, CO 2 , CO, O 3 , NO 2 , VOC, CH 2 O, and PM, and the event is a predetermined infectious disease. and the processing unit derives a correlation between the measured data and the cluster occurrence information, and calculates the probability of cluster occurrence at the location where the environmental air information is newly acquired. The information processing apparatus according to claim 3.
The information processing apparatus according to any one of claims 1 to 4, wherein the processing unit outputs and displays a measurement value of measurement data including at least one of the measurement data and the environmental air index. .
The information processing apparatus according to claim 5, wherein the measured values of the measurement data are output and displayed substantially in real time in the form of an analog indicator meter.
The processing unit stores the environmental air index or a phrase indicating the state of the environmental air represented by the environmental air index and the measurement location of the measurement data on which the environmental air index was calculated, including altitude information, on a map. 7. The information processing apparatus according to any one of claims 1 to 6, which is displayed in association with .
The information processing device
Acquiring environmental air information, which is a plurality of types of measurement data regarding the properties and components of the environmental air, together with measurement location information, which is information indicating the location where the environmental air information was measured;
holding a correlation between the acquired environmental air information and an environmental air index, which is information indicating the quality of the environmental air;
obtaining the held correlation and calculating the ambient air index by applying the correlation to the ambient air information;
outputting the calculated ambient air index in a predetermined format;
Information processing methods.
information processing equipment,
A process of acquiring environmental air information, which is a plurality of types of measurement data relating to the properties and components of the environmental air, together with measurement location information, which is information indicating the location where the environmental air information was measured;
a process of holding a correlation between the acquired environmental air information and an environmental air index, which is information indicating the quality of the environmental air;
a process of obtaining the held correlation and calculating the ambient air index by applying the correlation to the ambient air information;
a process of outputting the calculated ambient air index in a predetermined format;
program to run.