Information processing device and program

Abstract

To provide a terminal device and program that can easily grasp a mask wearing state in unspecified locations.SOLUTION: A terminal device includes: an imaging unit configured to capture a face image of a user of the terminal device; a control unit configured to determine whether a user currently using the terminal device is a legitimate user based on the face image for user authentication captured by the imaging unit and generate mask wearing state information indicating whether the user is wearing a mask; and a transmission unit configured to transmit the mask wearing state information to a management device when it is determined that the user currently using the terminal device is a legitimate user.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device and a program, and more particularly to a terminal device and a program for grasping whether people are wearing masks. [Background technology]

[0002] Recently, efforts to prevent the spread of infectious diseases such as viruses have been attracting attention. Accordingly, systems that determine whether people are wearing masks have been proposed. For example, Patent Document 1 discloses an entrance management system that uses an image recognition camera installed at a gate, such as an entrance to a building, to acquire facial image data of people and determine whether or not they are wearing a mask based on the facial image data. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2010-128976 Summary of the Invention [Problem to be solved by the invention]

[0004] To prevent the spread of infection, it is necessary to reduce the risk of infection among an unspecified number of people in unspecified locations (wide areas or various regions). To achieve this, it is effective to acquire information on the mask-wearing status of people in unspecified locations and generate and provide information useful for reducing the risk of infection. However, while the technology of Patent Document 1 mentioned above can determine whether individuals in a specific location where a camera is installed are wearing masks, it is difficult to acquire information on the mask-wearing status of people in unspecified locations. In order to acquire information on the mask-wearing status of people in unspecified locations, it becomes necessary to install an increased number of cameras, which increases the complexity and cost of the system.

[0005] The present invention has been made to solve the above-mentioned problems, and provides a terminal device and a program that can easily grasp the mask wearing status in unspecified locations (wide areas or various regions). [Means for solving the problem]

[0006] An information processing device according to one aspect of the present invention includes a collection unit, an index generation unit, and an output unit. The collection unit collects, for each of a plurality of terminal devices, information on the mask wearing status of the user of the terminal device and location information of the terminal device. The mask wearing status information is generated based on a facial image for user authentication captured by the terminal device. The index generation unit generates an index indicating the mask wearing status in a target area based on the collected mask wearing status information and the collected location information. The output unit outputs information related to the index.

[0007] A program according to one aspect of the present invention causes a computer to execute a collection process, an index generation process, and an output process. The collection process is a process of collecting, for each of a plurality of terminal devices, information on the mask wearing status of the user of the terminal device and location information of the terminal device. The mask wearing status is generated based on a facial image for user authentication captured by the terminal device. The index generation process is a process of generating an index indicating the mask wearing status in a target area based on the collected information on the mask wearing status and the collected location information. The output process is a process of outputting information related to the index.

[0008] An information processing device according to one aspect of the present invention includes a collection unit, an identification unit, and a communication unit. The collection unit collects information on a mask-wearing state of a user of a first terminal device and location information of the first terminal device. The mask-wearing state information is generated based on a face image for user authentication captured by the first terminal device. If the mask-wearing state information collected by the collection unit does not satisfy a predetermined standard, the identification unit identifies a terminal device located within a predetermined range based on the first terminal device or a terminal device expected to be within the predetermined range as a second terminal device. The communication unit notifies the second terminal device.

[0009] A program according to one aspect of the present invention causes a computer to execute a collection process, an identification process, and a communication process. The collection process is a process of collecting information on a mask-wearing state of a user of a first terminal device and location information of the first terminal device. The mask-wearing state information is generated based on a face image for user authentication captured by the first terminal device. The identification process is a process of identifying a terminal device located within a predetermined range based on the first terminal device or a terminal device expected to be within the predetermined range as a second terminal device if the mask-wearing state information does not satisfy a predetermined standard. The communication process is a process of notifying the second terminal device. [Effects of the Invention]

[0010] The present invention provides a terminal device and a program that can easily grasp the mask wearing status in unspecified locations. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a schematic configuration diagram of an infection prevention support system according to a first embodiment. [Figure 2] FIG. 2 is a block diagram illustrating an example of a configuration of a terminal device according to the first embodiment. [Figure 3] FIG. 2 is a block diagram illustrating an example of a configuration of a management device according to the first embodiment. [Figure 4] FIG. 10 is a schematic diagram showing the relationship between a mask wearing state and an authentication score. [Figure 5] FIG. 4 is a diagram illustrating an example of a data structure of a mask information table according to the first embodiment. [Figure 6] 10 is a flowchart showing an example of a mask wearing rate calculation process procedure of the management device according to the first embodiment. [Figure 7] FIG. 2 is a diagram for explaining an example of an area according to the first embodiment. [Figure 8] FIG. 2 is a diagram for explaining an example of an area according to the first embodiment. [Figure 9] FIG. 3 is a diagram showing an example of a mask wearing rate map according to the first embodiment. [Figure 10] FIG. 3 is a diagram showing an example of a mask wearing rate map according to the first embodiment. [Figure 11] FIG. 3 is a diagram showing an example of a mask wearing level map according to the first embodiment. [Figure 12] FIG. 4 is a diagram showing an example of mask wearing rate data according to the first embodiment. [Figure 13] FIG. 3 is a diagram showing an example of a display on the terminal device according to the first embodiment. [Figure 14] FIG. 10 is a diagram showing another example of a display on the terminal device according to the first embodiment. [Figure 15] FIG. 10 is a diagram showing another example of a display on the terminal device according to the first embodiment. [Figure 16] FIG. 11 is a diagram illustrating an example of a data structure of a public area table according to the second embodiment. [Figure 17] FIG. 11 is a diagram for explaining the update process of the mask information table of the management device according to the third embodiment. [Figure 18] FIG. 11 is a diagram showing an example of a display on a terminal device according to a fourth embodiment. [Figure 19] FIG. 13 is a diagram showing an example of a mask wearing rate prediction result according to the fifth embodiment. [Figure 20] FIG. 13 is a diagram showing an example of mask wearing rate prediction data according to the fifth embodiment. [Figure 21]FIG. 13 is a diagram showing an example of a display on a terminal device according to a fifth embodiment. [Figure 22] FIG. 13 is a diagram showing an example of a display on a terminal device according to a fifth embodiment. [Figure 23] FIG. 20 is a diagram showing an example of a result of predicting the number of infected people according to the sixth embodiment. [Figure 24] FIG. 20 is a diagram showing an example of a display on a terminal device according to a sixth embodiment. [Figure 25] FIG. 13 is a block diagram illustrating an example of the configuration of a management device according to a seventh embodiment. [Figure 26] FIG. 20 is a diagram illustrating an example of a data structure of a user position information table according to the seventh embodiment. [Figure 27] 13 is a flowchart illustrating an example of an information providing process procedure according to the seventh embodiment. [Figure 28] FIG. 20 is a diagram showing an example of the configuration of a high-risk area map according to the seventh embodiment. [Figure 29] FIG. 20 is a diagram illustrating an example of a data structure of a terminal device list according to the seventh embodiment. [Figure 30] FIG. 13 is a diagram showing an example of a display on a terminal device according to a seventh embodiment. [Figure 31] 13 is a flowchart illustrating an example of an information providing process procedure according to the eighth embodiment. [Figure 32] FIG. 20 is a diagram for explaining an example of a process for predicting intrusion into a high-risk area according to the eighth embodiment. [Figure 33] FIG. 20 is a diagram for explaining an example of a process for predicting intrusion into a high-risk area according to the eighth embodiment. [Figure 34] FIG. 13 is a diagram showing an example of a display on a terminal device according to an eighth embodiment. [Figure 35] FIG. 13 is a diagram showing an example of a display on a terminal device according to a ninth embodiment. [Figure 36] 13 is a flowchart illustrating an example of an information providing process procedure according to the tenth embodiment. [Figure 37] FIG. 20 is a diagram showing an example of the configuration of a user area map according to the tenth embodiment. [Figure 38]FIG. 20 is a diagram showing an example of a display on a terminal device according to a tenth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] The present invention will be described below through embodiments of the invention, but the invention according to the claims is not limited to the following embodiments. Furthermore, not all of the configurations described in the embodiments are necessarily essential means for solving the problems. For clarity of explanation, the following description and drawings have been omitted and simplified as appropriate. Note that the same elements are assigned the same reference numerals in each drawing.

[0013] <Issues of the embodiment> Here, the problem that this embodiment aims to solve will be explained again. Recently, there has been concern worldwide about the spread of infectious diseases such as the new coronavirus. For this reason, it is recommended that people wear masks when going out or when there is a possibility of coming into close contact with others, as a means of preventing the spread of droplets such as saliva that can cause infection. In addition, to prevent the spread of infection, it is recommended that people avoid, as much as possible, facilities and stores where people are unlikely to be wearing masks.

[0014] Although wearing a mask is effective in preventing infection, there is concern that an increase in people going out without wearing a mask will occur during hot weather, such as in the summer. There is also concern that an increase in people going out without a mask will occur even if the number of infected people temporarily decreases or if there is a shortage of masks. At such times, facilities and stores where many people gather without wearing masks pose a higher risk of contracting the virus than other places. Therefore, to prevent infection, when going out, it is advisable to avoid places with a high risk of infection, or to take a detour if there are any high-risk places on the route to your destination.

[0015] However, conventional technology did not have a means to quantitatively identify places where many people without masks were gathered, which increased the risk of unknowingly approaching a place where many people without masks were gathered when going out and contracting the virus.

[0016] For example, the entrance management system described in Patent Document 1 above can obtain information on whether people in specific locations where cameras are installed are wearing masks, and can prevent people not wearing masks from entering a building. However, with the entrance management system described above, it is difficult to easily obtain information on the mask wearing status of an unspecified number of people in unspecified locations (multiple locations or a wide range of locations).

[0017] Here, when the national government, local governments, public transportation agencies, etc. formulate infectious disease countermeasures, there is a need to understand the mask-wearing status of many people. Also, when individuals make plans for going out or traveling, there is a need to understand the mask-wearing status in areas of interest to them. In other words, there is a need for individuals, companies, local governments, the country, etc. to understand the mask-wearing status of people in areas of interest to them and use this information to prevent infection. However, the technology of Patent Document 1 mentioned above cannot meet these needs.

[0018] Furthermore, individual users have a need to know information that will help them take actions to reduce the risk of infection. For example, users have a need to know whether their current location is a high-risk or low-risk location. Knowing such information allows users to take measures such as moving locations, thereby reducing the risk of infection. However, while the aforementioned Patent Document 1 can reduce the risk of infection for people in specific locations, it is difficult to reduce the risk of infection for an unspecified number of people in unspecified locations. In other words, it was not possible to provide users with information to reduce the risk of infection according to the circumstances surrounding each individual user.

[0019] As described above, there is a problem in that it is difficult to obtain information on the mask wearing status of people in unspecified locations and generate and provide information that is useful for reducing the risk of infection. The present disclosure has been made to solve this problem, and embodiments will be described below.

[0020] <Embodiment 1> First, a description will be given of embodiment 1. Fig. 1 is a schematic configuration diagram of an infection prevention support system 1 according to embodiment 1. The infection prevention support system 1 shown in the figure is a computer system for reducing the risk of virus infection for users and preventing the spread of virus infection. The infection prevention support system 1 includes an information processing device (hereinafter referred to as a management device) 10, terminal devices 20-1, 20-2, ..., 20-6, and relay devices 30-1, 30-2, and 30-3. Hereinafter, when the terminal devices 20-1, 20-2, ..., 20-6 are referred to without distinction, they will be simply referred to as terminal devices 20, and when the relay devices 30-1, 30-2, and 30-3 are referred to without distinction, they will be simply referred to as relay devices 30. The number of terminal devices 20 and the number of relay devices 30 are not limited to six and three, respectively.

[0021] The terminal device 20 is a mobile phone terminal such as a smartphone used by a user. However, the terminal device 20 is not limited to this, and may be a tablet terminal, a personal computer, or another terminal device with a communication function. The terminal device 20 communicates with the management device 10 via a communication means available to the terminal device 20, such as a wired local area network (LAN), a wireless LAN, or a mobile phone line such as 4G or 5G. In the first embodiment, the terminal device 20 determines whether the user is wearing a mask from the facial image in response to capturing a "face image for user authentication," and transmits mask wearing state information indicating the determination result and location information of the terminal device 20 to the management device 10. Alternatively, the terminal device 20 transmits a facial image from which the mask wearing state can be determined and location information of the terminal device 20 to the management device 10.

[0022] Typically, terminal devices such as smartphones are configured to lock their user interface (UI), such as a screen, if no operation is performed for a certain period of time to ensure security or reduce battery consumption. The UI is, for example, a screen, and the locked state is also called a screen lock. When a smartphone's UI is locked, the smartphone cannot be operated until the authorized user unlocks the lock state. Recently, in addition to password entry, pattern drawing, and fingerprint authentication, an increasing number of smartphone models are equipped with a facial recognition unlock function. Facial recognition unlocking involves capturing a user's face using a smartphone's built-in camera, and then performing image analysis to determine whether the features of the captured facial image match the features of a facial image of an authorized user pre-registered on the smartphone. If it is determined that the features of the captured facial image match the features pre-registered on the smartphone, the user performing facial authentication is determined to be the authorized user of the smartphone, and the smartphone is unlocked.

[0023] In the first embodiment, focusing on the fact that unlocking by facial authentication is frequently performed on smartphones, the user's mask-wearing state is determined from a facial image captured during facial authentication on the terminal device 20. That is, in the first embodiment, the "face image for user authentication" is a facial image for facial authentication used to unlock the locked state of the UI of the terminal device 20. However, in addition to or instead of this, the "face image for user authentication" may be a facial image used for facial authentication for electronic payment using the terminal device 20 or for other personal identification using the terminal device 20. For example, when facial authentication is performed when starting or stopping the terminal device 20, the mask-wearing state may be determined using a facial image captured for that purpose. That is, processing may be performed using not only a facial image for unlocking the locked state of the terminal device 20, but also a facial image for personal identification on the terminal device 20.

[0024] The relay device 30 is a device for connecting the terminal device 20 to the Internet NW. The relay device 30 may include a router, a base station, a line termination device, or a device of a provider (line carrier).

[0025] The management device 10 is a server computer connected to the Internet NW. Based on data received from each of the multiple terminal devices 20 via the relay device 30, the management device 10 generates an index (wearing status index) indicating the mask wearing status in each region, and generates information for preventing the spread of infection based on the wearing status index.

[0026] 2 is a block diagram showing an example of the configuration of the terminal device 20 according to the first embodiment. The terminal device 20 includes a communication unit 21, a display unit 22, an input unit 23, an audio output unit 24, a position identification unit 25, a face authentication unit 26, an imaging unit 27, a control unit 28, and a storage unit 29. The components are connected to each other via a data bus or the like.

[0027] The communication unit 21 has an internet communication function and transmits and receives data to and from the management device 10 via the relay device 30 and the internet NW. Specifically, the communication unit 21 transmits mask wearing status information calculated by the control unit 28 and location information acquired by the location identification unit 25 to the management device 10. The communication unit 21 also receives information related to mask wearing status indicators for the target area from the management device 10 and causes the display unit 22 or the audio output unit 24 to output the information.

[0028] The display unit 22 is an interface that displays the operation screen and setting information of the terminal device 20, as well as the notification information from the management device .

[0029] The input unit 23 is also called an operation unit, and includes input devices such as various buttons or a touch panel for operating the terminal device 20, and an interface for supplying input signals to the control unit 28. The display unit 22 and the input unit 23 may be integrally configured using a touch panel.

[0030] The audio output unit 24 provides audio notification to the user. The audio output unit 24 is configured by, for example, a speaker or earphones. Although not shown in FIG. 2, the terminal device 20 may also include an audio input unit configured by a microphone or the like. Furthermore, the audio input to the audio input unit may be used as a voice command to control the terminal device 20, or the audio input to the audio input unit may be transmitted via the communication unit 21 to perform a voice call.

[0031] The position specifying unit 25 is configured with a GPS (Global Positioning System) receiver or the like, and acquires the current position information (latitude and longitude) of the terminal device 20.

[0032] The face authentication unit 26 performs image analysis processing on face image data captured by the imaging unit 27 (described later) and calculates an authentication score to be used for face authentication. Then, the face authentication unit 26 determines whether the user currently using the terminal device 20 is an authorized user based on the authentication score.

[0033] In the first embodiment, the face authentication unit 26 executes an unlock process to unlock the UI of the display unit 22, etc. When executing the unlock process, the face authentication unit 26 requests the imaging unit 27 to capture an image. The face authentication unit 26 may also request the imaging unit 27 to capture an image not only for the unlock process but also when performing user authentication for electronic payment, etc. The face authentication unit 26 detects, for example, that some input (operation) has been made to the input unit 23 in the locked state, and starts the unlock process. After requesting the imaging unit 27 to capture an image, the face authentication unit 26 acquires face image data from the imaging unit 27 and generates an authentication score indicating the degree to which the acquired face image data matches data (template) of a previously registered authorized user. The face authentication unit 26 then determines whether the user using the terminal device 20 is an authorized user based on the authentication score.

[0034] When the user performs face authentication, the imaging unit 27 photographs the user's face and generates a face image. In the first embodiment, the imaging unit 27 photographs the user's face and generates a face image in response to the face authentication unit 26 executing the unlock process. The imaging unit 27 may also photograph the user's face and generate a face image not only for the unlock process but also when performing user authentication for electronic payment or the like.

[0035] The control unit 28 controls each component of the terminal device 20. The control unit 28 may be configured with a CPU (Central Processing Unit), and the control unit 28 may execute a program stored in the storage unit 29 to perform each process of the terminal device 20. The control unit 28 generates mask wearing state information based on the authentication score calculated by the face authentication unit 26 or the face image captured by the imaging unit 27. Details of the mask wearing state information generation process will be described later. The face authentication unit 26 may be included in the control unit 28. Alternatively, the control unit 28 and the face authentication unit 26 may be configured integrally.

[0036] The control unit 28 then associates the mask wearing state information with an identifier (terminal identifier) ​​that identifies the terminal device 20 and the location information acquired by the location specifying unit 25, and transmits the associated information to the management device 10 via the communication unit 21. Specifically, each time the lock state is released by facial authentication, the control unit 28 creates mask information including mask wearing state information, location information, and a terminal identifier, and transmits the mask information to the management device 10 via the communication unit 21. Alternatively, the control unit 28 creates mask information including a face image that can determine the mask wearing state, location information, and a terminal identifier, and transmits the mask information to the management device 10 via the communication unit 21. The terminal identifier is an ID for identifying the terminal device 20, and may be, for example, a hash value of a telephone number. Note that an identifier for identifying a user (user identifier) ​​may be used instead of the terminal identifier. The control unit 28 may perform control not to transmit the mask information to the management device 10 when the facial authentication unit 26 determines that the user is not a legitimate user. By performing such control, the management device 10 can obtain highly reliable data that has been confirmed by each terminal device 20 as being from the individual (without mixing in data from other users), thereby improving the reliability of the information generated as a result of processing by the management device 10.

[0037] The storage unit 29 is configured as a storage medium that stores data and programs used for various processes of the terminal device 20.

[0038] For convenience, the following description will be given assuming that face authentication by the face authentication unit 26 is performed as user authentication when the screen of the smartphone is unlocked, but it goes without saying that the present invention is not limited to this.

[0039] 3 is a block diagram showing an example of the configuration of the management device 10 according to the first embodiment. The management device 10 includes a communication unit 11, a timer unit 12, a control unit 13, an output unit 16, and a storage unit 17.

[0040] The communication unit 11 has an internet communication function, and transmits and receives data to and from the terminal device 20 via the internet NW and the relay device 30.

[0041] The timekeeping unit 12 acquires the current time.

[0042] The storage unit 17 is configured by a storage medium that stores data and programs used for various processes of the management device 10. The storage unit 17 stores a mask information table 18 and a map database (map information) 19. The mask information table 18 is a table that stores mask wearing status information of the user of the terminal device 20, and will be described in detail later. The map database 19 also stores location information on structures such as roads, railways, and facilities, as well as location information on city, ward, town, and village boundaries and river areas. The map database 19 may also store area information indicating location information (latitude, longitude, etc.) of one or more predetermined areas (sections). The area information may also be configured not to be stored in the map database 19, but for the control unit 13 or the index generation unit 15 to generate the area information.

[0043] The control unit 13 controls each component of the management device 10. The control unit 13 includes a collection unit 14 and an index generation unit 15. The control unit 13 may be configured with a CPU (Central Processing Unit), and the control unit 13 may execute a program stored in the storage unit 17 to perform each process of the management device 10.

[0044] The collection unit 14 collects, for each of the multiple terminal devices 20, mask wearing state information of the user of that terminal device 20 and location information of that terminal device 20, and records the collected information in a mask information table 18 in the storage unit 17. More specifically, when the collection unit 14 receives mask information including mask wearing state information, location information, and a terminal identifier from the terminal device 20 via the communication unit 11, the collection unit 14 obtains the current time (reception date and time) from the clock unit 12. The collection unit 14 then associates the reception date and time with the mask wearing state information, location information, and terminal identifier, and records the association results in the mask information table 18 in the storage unit 17. Of course, the control unit 13 and the collection unit 14 may be configured integrally.

[0045] The index generating unit 15 generates a mask wearing status index for a target area based on the mask wearing status information and location information collected in the mask information table 18. The target area is an area for which the mask wearing status index is calculated. The wearing status index may indicate the mask wearing rate or the ratio for each wearing level. Of course, the control unit 13 and the index generating unit 15 may be configured integrally.

[0046] The indicator generation unit 15 also maps the wearing status indicator for each area based on the location information in the mask information table 18. This enables the management device 10 to notify the user of areas where many people gather without wearing a mask, i.e., areas with a high risk of infection. This process is based on the knowledge that since the terminal device 20, such as a smartphone, is always at the user's fingertips and is frequently unlocked, it is easy to detect the user's mask wearing status in real time.

[0047] The output unit 16 outputs information related to the wearing status indicator of the target area. For example, the output unit 16 may be a display unit or an audio output unit that outputs information related to the wearing status indicator. The output unit 16 may transmit the information related to the wearing status indicator of the target area to the terminal device 20 or an external device (not shown) connected to the Internet NW via the communication unit 11. In this case, the communication unit 11 may be configured as a part of the output unit 16.

[0048] In the present embodiment 1, the control unit 28 of the terminal device 20 or the control unit 13 of the management device 10 generates mask wearing status information using one of the following methods 1 to 4. Methods 1 and 2 are methods in which the control unit 28 of the terminal device 20 generates mask wearing status information. Methods 3 and 4 are methods in which the control unit 13 of the management device 10 generates mask wearing status information.

[0049] (Method 1: A method of determining directly in the terminal device 20) When the imaging unit 27 captures a face image for user authentication, the control unit 28 of the terminal device 20 acquires face image data from the imaging unit 27, performs mask recognition processing on the face image data, and generates mask-wearing state information. The mask recognition processing may use a known technique disclosed in, for example, Japanese Patent Application Laid-Open No. 2011-118588. Of course, other image recognition techniques may also be used to generate mask-wearing state information from face image data.

[0050] Here, the mask wearing status information (information on the mask wearing status) will be described in detail. The most basic mask wearing status information is the determination result of whether or not a mask is being worn. This is sometimes called first mask wearing status information. The first mask wearing status information may be a binary value of "Yes: 1" indicating that a mask is being worn and "No: 0" indicating that a mask is not being worn, or may be a numerical value (e.g., "80%)" indicating the possibility (probability) of wearing a mask. The mask wearing status information may be expressed as a wearing score that quantifies the state of wearing a mask. For example, if a mask is being worn, the wearing score may be "100," and if a mask is not being worn, the wearing score may be "0." Furthermore, if the possibility (probability) of wearing a mask is 80%, the wearing score may be "80."

[0051] The mask wearing status information may also be a determination result of a wearing level (degree of wearing) that categorizes the wearing state, such as whether the mask is worn completely or partially. Mask wearing status information including information on the mask wearing level may also be referred to as second mask wearing status information. The second mask wearing status information may be a numerical value indicating the wearing level, which indicates the degree of completeness or incompleteness of wearing. The wearing levels may be classified, for example, into "a complete state in which the mask completely covers the nose and mouth (Level 1)," "an incomplete state in which the mask covers the mouth but not the nose (Level 2)," "a practical state in which the mask is not worn, where the mask is over the ears but under the chin and does not cover the mouth and nose (Level 3)," and "a formal state in which no mask is detected in the facial image (not wearing or carrying) (Level 4)." The wearing level may also be expressed numerically as a wearing score. For example, the wearing score for level 1 may be set to "100," the wearing score for level 2 to "70," the wearing score for level 3 to "30," and the wearing score for level 4 to "0." Of course, the number of wearing levels is not limited to four, and there may be more or fewer than this.

[0052] The second mask wearing state information may also be a numerical value indicating the probability (likelihood) of each wearing level. For example, when using the four types of wearing levels described above, information such as "20% probability of level 1, 70% probability of level 2, 10% probability of level 3, and 0% probability of level 4" may be assigned to a certain face image. In other words, information associating the wearing level with the probability may be used as the second wearing state information.

[0053] The control unit 28 may also include information such as "wearing a face shield in addition to a mask," "wearing a face shield but not a mask," or "wearing a mouth shield but not a mask" in the mask wearing status information. In other words, information about droplet prevention equipment other than a mask may be included in the mask wearing status information. Mask wearing status information including information about droplet prevention equipment other than a mask may also be referred to as third mask wearing status information. The third mask wearing status information may also be quantified as a wearing score. For example, the wearing score may be "100" for "wearing a face shield in addition to a mask," "80" for "wearing a mask but not a face shield," "40" for "not wearing a mask but wearing a face shield," "10" for "not wearing a mask but wearing a mouth shield," and "0" for "not wearing a mask, face shield, or mouth shield."

[0054] The control unit 28 may also determine the mask material and shape through image recognition and include the results in the mask wearing status information. Mask wearing status information including information about the mask material and shape may also be referred to as fourth mask wearing status information. The fourth mask wearing status information may include only information about the mask material, only information about the mask shape (size), or both. For example, the control unit 28 may generate information such as "cloth mask: small size," "urethane mask: medium size," "nonwoven mask: large size," and "medical mask: large size" and include it in the mask wearing status information. The fourth mask wearing status information may also be quantified as a wearing score. For example, the wearing score for "medical mask: large size" may be "100," the wearing score for "nonwoven mask: large size" may be "80," the wearing score for "urethane mask: medium size" may be "60," and the wearing score for "cloth mask: small size" may be "50." In other words, the larger the mask size and the more effective the material in preventing droplets, the higher the wearing score should be.

[0055] Then, the control unit 28 of the terminal device 20 generates mask information including the mask wearing status information, the location information of the terminal device 20, and the terminal identifier, and transmits the mask information to the management device 10 via the communication unit 21. The mask wearing status information may be a character string or a wearing score (numerical value).

[0056] (Method 2: Indirect determination in terminal device 20) Generally, in the image analysis process for facial authentication, multiple parameters are extracted from a facial image, and the matching rate with registered information is calculated as an authentication score. For example, the larger the authentication score calculated by the facial authentication unit 26, the higher the possibility (probability) that the user is the actual user (authorized user). If the authentication score is equal to or greater than a first predetermined value (for example, "70" if the maximum authentication score is "100"), the facial authentication unit 26 determines that the user is an authorized user and releases the locked state of the terminal device 20. On the other hand, if the authentication score is less than the first predetermined value, the facial authentication unit 26 determines that the user is not an authorized user and does not release the locked state of the terminal device 20.

[0057] Furthermore, even if the user performing face authentication is an authorized user of the terminal device 20 and the authentication score calculated by the image analysis process is equal to or greater than the first predetermined value, the authentication score may fluctuate depending on the shooting conditions. For example, when more of the face is hidden due to wearing a mask, the authentication score tends to decrease. Figure 4 is a schematic diagram showing the relationship between the mask wearing condition and the authentication score.

[0058] 4(a) shows a face image of a user not wearing a mask (not carrying one) (Level 4). Generally, a user is not wearing a mask during initial registration (initial setup) for face authentication, so the face authentication unit 26 calculates a high authentication score for the case of FIG. 4(a) ("96" in this figure).

[0059] 4(b) shows a face image in an incomplete state (level 2) where the mask covers the mouth but not the nose. In this case, the face authentication unit 26 calculates an authentication score that is lower than level 4 ("80" in this figure).

[0060] 4(c) shows a face image in a complete state (level 1) where the nose and mouth are completely covered by a mask. In this case, the face authentication unit 26 calculates an authentication score that is lower than that of level 2 ("72" in this figure).

[0061] In this way, the authentication score varies depending on the state of wearing of the mask. Therefore, in method 2, the control unit 28 of the terminal device 20 determines whether or not a mask is being worn and the mask wearing level according to the authentication score calculated by the face authentication unit 26. Specifically, when the authentication score is equal to or greater than a first predetermined value and less than a second predetermined value, the control unit 28 determines that the authorized user is wearing a mask at level 1. Here, the second predetermined value is greater (higher) than the first predetermined value. Furthermore, when the authentication score is equal to or greater than a second predetermined value and less than a third predetermined value, the face authentication unit 26 determines that the authorized user is wearing a mask at level 2. Here, the third predetermined value is greater (higher) than the second predetermined value. Furthermore, when the authentication score is equal to or greater than the third predetermined value, the face authentication unit 26 determines that the authorized user is not wearing a mask (level 3 or level 4). Furthermore, the control unit 28 may generate a wearing score according to the wearing level, as described above. Furthermore, the control unit 28 may generate the wearing score by performing a predetermined calculation on the authentication score. For example, the wearing score may be calculated so that the higher the authentication score, the lower the value.

[0062] When performing initial registration for facial recognition, the user may register two types of facial images: a facial image with a mask on (a wearing template) and a facial image without a mask on (a non-wearing template). For example, the display unit 22 may display a message such as, "First, take a picture of your face with a mask on. Then, take a picture with the mask off," prompting the user to register both a facial image with a mask on and a facial image without a mask on. In this case, when performing facial recognition, the facial authentication unit 26 may determine whether the captured facial image is closer to the wearing template or the non-wearing template in addition to determining whether the user is a legitimate user. If the captured facial image is closer to the wearing template, the facial authentication unit 26 may determine that the user is wearing a mask, and if it is closer to the non-wearing template, the facial authentication unit 26 may determine that the user is not wearing a mask. The facial authentication unit 26 may estimate the level of mask wear based on the degree of match with the wearing template and the degree of match with the non-wearing template. Furthermore, in addition to the two types of templates for wearing and not wearing, three or more types of templates may be used, such as a "fully-wearing (Level 1) template that completely covers the nose and mouth," a "partially-wearing (Level 2) template that leaves the nose exposed but covers the mouth," and a "not-wearing template."Facial images wearing droplet prevention equipment other than masks may also be registered as wearing templates.

[0063] In this way, in Method 2, the control unit 28 of the terminal device 20 generates mask wearing state information according to the authentication score calculated by the face authentication unit 26 and the degree of match with the wearing template. Then, the control unit 28 generates mask information including the mask wearing state information, location information of the terminal device 20, and a terminal identifier, and transmits the mask information to the management device 10 via the communication unit 21.

[0064] The control unit 28 of the terminal device 20 may transmit the date and time when face authentication was performed (the date and time when the mask wearing state information was generated, also called the measurement date and time) to the management device 10. Then, the collection unit 14 of the control unit 13 of the management device 10 may record the measurement date and time in the mask information table 18 instead of the reception date and time.

[0065] Methods 1 and 2 provide high privacy protection because they prevent the management device 10 from directly holding the user's face image, which is private information. In other words, they have the advantage of reducing the psychological burden on the user regarding privacy protection. However, instead of methods 1 and 2, the management device 10 may be configured to generate mask-wearing status information. In this case, the terminal device 20 transmits the user's face image or authentication score, i.e., data that can determine the user's mask-wearing status, to the management device 10 in response to capturing a face image for user authentication. The following methods 3 and 4 are methods in which the control unit 13 of the management device 10 generates mask-wearing status information.

[0066] (Method 3: Direct determination in management device 10) In response to capturing a face image for user authentication, the terminal device 20 transmits face image data to the management device 10 as data for determining a mask wearing state. More specifically, the control unit 28 of the terminal device 20 acquires the face image data from the face authentication unit 26, generates mask information including the face image data, location information of the terminal device 20, and a terminal identifier, and transmits the mask information to the management device 10 via the communication unit 21. The collection unit 14 of the control unit 13 of the management device 10 determines the user's mask wearing state from the face image data included in the mask information received from the terminal device 20 in a manner similar to Method 1, and generates mask wearing state information. For example, the collection unit 14 generates a mask wearing score based on the face image data. In other words, the collection unit 14 functions as a detection unit that detects the mask wearing state of the user of the terminal device 20 based on the face image data. The collection unit 14 also functions as a generation unit (wearing state information generation unit) that generates information on the mask wearing state of the user of the terminal device 20 based on the collected face image data. The collection unit 14 then records the generated mask wearing state information, the location information of the terminal device 20, and the terminal identifier in the mask information table 18 of the storage unit 17.

[0067] (Method 4: Indirect determination in the management device) The terminal device 20 transmits the authentication score described in Method 2 to the management device 10 as data that can determine the mask wearing state. Specifically, the control unit 28 of the terminal device 20 acquires the authentication score from the face authentication unit 26, generates mask information including the authentication score, location information of the terminal device 20, and a terminal identifier, and transmits the mask information to the management device 10 via the communication unit 21. Note that the terminal device 20 may not transmit the authentication score if the authentication score is less than a first predetermined value, that is, if the user using the terminal device 20 has not been authenticated as a legitimate user.

[0068] Then, the collection unit 14 of the control unit 13 of the management device 10 determines the mask wearing state of the user based on the authentication score in the same manner as in Method 2, and generates mask wearing state information. For example, a wearing score is generated based on the authentication score. The collection unit 14 records the generated mask wearing state information, location information of the terminal device 20, and a terminal identifier in the mask information table 18 of the storage unit 17. Note that the collection unit 14 may perform control not to record the authentication score in the mask information table 18 if the authentication score is less than a first predetermined value.

[0069] In methods 3 and 4, the control unit 28 of the terminal device 20 may also transmit the date and time when facial authentication was performed (measurement date and time) to the management device 10. The collection unit 14 of the control unit 13 of the management device 10 may then record the measurement date and time in the mask information table 18 instead of the reception date and time. Like methods 1 and 2, method 4 provides high privacy protection because the management device 10 does not directly hold the user's facial image, which is private information. Meanwhile, method 3 has the advantage of easily utilizing the latest image recognition technology and image recognition technology that requires a large amount of calculations, since image recognition processing is performed by the management device 10. Furthermore, method 3 has the advantage of enabling processing such as comparing multiple users' facial images to determine their mask wearing status, thereby enabling more accurate determination of the mask wearing status. Thus, in any of methods 1 to 4, the mask wearing status information is generated based on a facial image for user authentication captured by the terminal device 20 and is recorded in the mask information table 18 of the management device 10. However, in methods 1 and 3, mask wearing status information can also be generated using facial images captured for purposes other than user authentication.

[0070] 5 is a diagram showing an example of the data structure of the mask information table 18 according to embodiment 1. In the mask information table 18 shown in this figure, the reception date and time, the wearing score as mask wearing status information, the location information, and the terminal identifier are recorded.

[0071] The reception date and time is recorded as the date and time when the management device 10 received the mask information from the terminal device 20. Note that the reception date and time record "2020 / 9 / 10 10:33:21" indicates "September 10, 2020, 10:33:21."

[0072] As described above, the mask wearing score is a numerical value representing the determination result indicating the user's mask wearing status, and is expressed as a number between "0" and "100," for example. The larger the number, the higher the possibility (probability) that the user is wearing a mask, or the higher the level of mask wearing (completeness of wearing). On the other hand, the smaller the number, the higher the possibility that the user is not wearing a mask, or the lower the level of mask wearing (completeness of wearing). Note that in this figure, an example is shown in which the mask wearing score is stored as mask wearing status information, but as described above, the mask wearing status information does not have to be a numerical value and may be a character string or a symbol. For example, two logical values, "Yes (wearing)" and "No (not wearing)," may be stored in the mask information table 18. As the location information and terminal identifier, the location information (latitude, longitude) and terminal identifier included in the mask information received from the terminal device 20 are recorded.

[0073] When the collection unit 14 of the control unit 13 of the management device 10 receives mask information from a terminal device 20, the collection unit 14 adds a new record (a new row) to the mask information table 18. If the number of records exceeds a predetermined number (e.g., 100 million), the collection unit 14 deletes records in order starting with the oldest received date and time. Furthermore, when the capacity of the mask information table 18 exceeds a predetermined value (e.g., 1 PB), the collection unit 14 may delete records in order starting with the oldest received date and time. Alternatively, the collection unit 14 may delete records whose received date and time exceed a predetermined time (e.g., six months) compared with the current time. Furthermore, when the collection unit 14 receives mask information from a terminal device 20 while mask information for the same terminal device 20 is already recorded in the mask information table 18, the collection unit 14 may overwrite the record (existing record) for that terminal device 20 or add a new record. That is, the collection unit 14 may record only the latest mask information for each terminal device 20 in the mask information table 18, or may record multiple pieces of mask information received from the same terminal device 20 in chronological order. When overwriting an existing record, the collection unit 14 may perform the following process. First, when the collection unit 14 receives mask information from the terminal device 20, it references the terminal identifier in the mask information and determines whether or not a record with a matching terminal identifier exists in the mask information table 18. If a matching terminal identifier exists, the collection unit 14 overwrites the record corresponding to that terminal identifier with the received mask information. If a record with a matching terminal identifier does not exist in the mask information table, the collection unit 14 adds a new record to the mask information table. Note that, for the sake of explanation, the mask information table 18 is shown in descending order of reception date and time in this figure.

[0074] Next, a calculation process will be described with reference to FIG. 6 when the control unit 13 of the management device 10 calculates a mask wearing rate as a wearing status index. FIG. 6 is a flowchart showing an example of a procedure for the mask wearing rate calculation process of the management device 10 according to the first embodiment. The mask wearing rate calculation process is a process of calculating, for each area, the mask wearing rate of users of terminal devices 20 present in that area by referring to the mask information table 18 and the map database 19 in the storage unit 17 of the management device 10. The control unit 13 of the management device 10 executes the mask wearing rate calculation process at predetermined intervals (for example, 10 minutes). The mask wearing rate calculation process is also sometimes called a "mask wearing status index calculation process," a "wearing status index calculation process," or an "infection risk index calculation process."

[0075] First, in S100, the index generating unit 15 of the control unit 13 of the management device 10 acquires the current time CT from the clocking unit 12. Thereafter, the index generating unit 15 advances the process to S110.

[0076] In S110, the index generating unit 15 refers to the mask information table 18 in the storage unit 17, and extracts a record Rt whose reception time is within a predetermined period DT (e.g., 15 minutes) from the current time CT from the records recorded in the mask information table 18. In other words, the record Rt is relatively new mask information received by the management device 10. The index generating unit 15 proceeds to S120.

[0077] In S120, the index generation unit 15 selects area Z, which is a target area for calculating the mask wearing rate. Specifically, the index generation unit 15 selects one unprocessed area from n (one or more) areas included in the map database 19, and sets this as area Z. The number of areas may be one or more, but the following description will be given taking the case where there are multiple areas as an example.

[0078] 7 and 8 are diagrams for explaining an example of an area according to the first embodiment. FIG. 7 shows an example of area division when map information is meshed. This figure shows an example in which a plurality of rectangular areas obtained by dividing a region into predetermined latitude and longitude ranges are recorded in the area information of the map database 19. Alternatively, for example, the index generation unit 15 may divide a region into predetermined latitude and longitude ranges and generate a plurality of rectangular areas. For example, if the index generation unit 15 selects area Z shaded with diagonal lines, the range of latitudes Nb to Nc and longitudes Ea to Eb becomes the area (section) for which the mask wearing rate is calculated. Note that each area is not limited to a rectangle and may have any shape.

[0079] FIG. 8 shows an example in which areas are divided by facility. This figure shows an example in which the area information in the map database 19 records areas for each facility, such as a store. For example, if the index generation unit 15 selects the shaded area Z, the range of latitude Nc to Nd and longitude Ec to Ed becomes the target section for calculating the mask wearing rate. Note that while FIG. 8 shows an example in which the facility area is specified as a rectangular area, the area may have any shape. For example, the area information in the map database 19 may record location information indicating the actual shape of each facility. For example, the index generation unit 15 may generate an area as a circular area within a predetermined distance from the center coordinates based on location information (center coordinates) indicating the center of the facility included in the map database 19. When generating an area as a circular area, the area may be defined based on the latitude and longitude of the center of the facility and the radius from the center of the facility, or the diameter of the entire facility. Each area may have a different shape. Returning to FIG. 6, the explanation will continue. In S120, the index generating unit 15 selects an area Z for which the mask wearing rate is to be calculated, and then advances the process to S130.

[0080] In S130, the index generation unit 15 extracts records Ra (record set Ra) whose location information is included in the section of the area Z selected in S120 from the records Rt extracted in S110. Typically, the records Ra include mask information for multiple terminal devices 20 (multiple users). Thereafter, the index generation unit 15 advances the process to S140.

[0081] In S140, the index generation unit 15 extracts records Rm (record set Rm) whose wearing scores are equal to or greater than a predetermined threshold from the records Ra extracted in S130. This threshold may be set to, for example, "50," but is not limited to this value. The administrator of the management device 10 or the user of the terminal device 20 may be able to set the predetermined threshold as desired. Records Rm whose wearing scores are equal to or greater than the predetermined threshold are records that are estimated to indicate that the user is wearing a mask during face authentication. The index generation unit 15 then proceeds to S150.

[0082] In S150, the index generation unit 15 calculates the mask wearing rate P. The mask wearing rate P [percentage] is calculated by formula (1) where Ta is the number of records Ra extracted in S130 and Tm is the number of records Rm extracted in S140. That is, the mask wearing rate P is the ratio of the number of mask information (data) whose wearing score is equal to or greater than a predetermined threshold to the number of mask information (data) in area Z.

number

[0083] Alternatively, the index generating unit 15 may calculate the mask wearing rate P according to equation (2).

number

[0084] In S160, the index generation unit 15 determines whether or not the mask wearing rate P has been calculated for all areas. If the mask wearing rate P has not been calculated for all areas (if there are unprocessed areas) (S160: NO), the index generation unit 15 returns the process to S120 and selects the area for which the mask wearing rate P has not been calculated (unprocessed area) as area Z. On the other hand, if the mask wearing rate has been calculated for all areas (S160: YES), the index generation unit 15 ends the process.

[0085] In the above description, the mask wearing rate P for all areas registered in the map database 19 is calculated sequentially. However, this is not limiting. For example, the administrator of the management device 10 may select one or more areas, and the index generation unit 15 may sequentially calculate the mask wearing rate P for each selected area. Furthermore, the management device 10 may select one or more areas for each terminal device 20 and sequentially calculate the mask wearing rate P for each selected area. In this case, the management device 10 may select one or more areas to be calculated for each terminal device 20 based on the current location information of the terminal device 20. However, instead of this, the management device 10 may select one or more areas to be calculated for each terminal device 20 based on future location information predicted based on the current location information. For example, the management device 10 may acquire time-series data on the location information of the terminal device 20 or information on the movement speed and movement direction of the terminal device 20, and based on this, predict the location information of the terminal device 20 in the future (a predetermined time after the present), and select the areas to be calculated using the predicted location information. Alternatively, the user of the terminal device 20 may specify a location (for example, the location of the terminal device 20 at a future time), and the management device 10 may acquire the specified location information and use the location information to select an area to be calculated. Note that when multiple areas are selected, the index generation unit 15 may integrate the selected areas (treating them as one area) and calculate the mask wearing rate for the integrated area.

[0086] After executing the mask wearing rate calculation process, the index generation unit 15 of the control unit 13 of the management device 10 creates a mask wearing rate map for each area. Then, the control unit 13 of the management device 10 transmits data of the mask wearing rate map to the terminal device 20 via the communication unit 21, and displays it on the display unit 22. The control unit 13 of the management device 10 may also transmit data of the mask wearing rate map (e.g., image data) to a server of another system (not shown) or the like.

[0087] 9 and 10 are diagrams illustrating an example of a mask wearing rate map according to the first embodiment. FIG. 9 is a mask wearing rate map in which map information is meshed, and FIG. 10 shows a mask wearing rate map for each facility. The index generating unit 15 may create a mask wearing rate map so that the display format of an area or facility changes depending on the mask wearing rate. For example, the mask wearing rate map may be created so that areas where the mask wearing rate is less than a first predetermined value are displayed in red, areas where the mask wearing rate is equal to or greater than the first predetermined value and is less than a second predetermined value greater than the first predetermined value are displayed in yellow, and areas where the mask wearing rate is equal to or greater than the second predetermined value are displayed in blue. Of course, the present invention is not limited to changing the display color, and the number of types of display format is not limited to three. For example, the display pattern (fill pattern) or text of an area or facility may be changed depending on the mask wearing rate. For example, the display format may be set to attract the user's attention by adding a predetermined icon to the names of areas or facilities in areas with low mask wearing rates or by displaying the names of the areas or facilities in a larger font. Conversely, the display format may be set to highlight areas and facilities with a high mask wearing rate. Also, in FIG. 10, the number of records Ra for each facility (each area) may be displayed in addition to the mask wearing rate. That is, the number of terminal devices 20 and the number of users (number of people) present at each facility may be displayed in addition to the mask wearing rate. The number of people per unit area (population density) of each facility may also be displayed. Displaying the number of people and population density at each facility in this way allows users to more accurately assess the risk of infection. For example, if there are two facilities with a mask wearing rate of "50%," the facility with the lower number of people and population density can be determined to have a lower risk of infection.

[0088] The index generating unit 15 of the control unit 13 of the management device 10 may calculate a percentage for each wearing level instead of the mask wearing rate as the wearing status index. In this case, the index generating unit 15 creates a mask wearing level map showing data on the wearing level percentage for each area. For example, the wearing status index may be generated as "Level 1: 50%, Level 2: 30%, Level 3: 15%, Level 4: 5%" for Area 1, and "Level 1: 10%, Level 2: 40%, Level 3: 20%, Level 4: 30%" for Area 2.

[0089] FIG. 11 is a diagram illustrating an example of a mask wearing level map according to the first embodiment. This diagram shows data on the wearing level ratio for each facility. Since the above-described wearing levels 1 to 4 cover all mask wearing states, the sum of the levels 1 to 4 ratios in each facility (each area) is 100%. In the example shown in FIG. 11, the sum of the levels 1 and 2 ratios in each facility matches the mask wearing rate in FIG. 10. In this way, the mask wearing rate may be calculated based on the ratio of a predetermined wearing level. Furthermore, instead of the ratio for each wearing level, the number of people or the number of terminal devices 20 for each wearing level may be displayed corresponding to each facility (each area). Furthermore, the number of people per unit area (population density) may be displayed for each wearing level. By displaying the number of people and population density for each wearing level in this way, the user can more accurately assess the risk of infection.

[0090] In the above explanation, the index generating unit 15 of the control unit 13 of the management device 10 creates a mask wearing rate map and transmits data of the mask wearing rate map to the terminal device 20, but the mask wearing rate map may be generated in the terminal device 20. In this case, the index generating unit 15 of the control unit 13 executes the mask wearing rate calculation process, then creates mask wearing rate data for each area, and distributes it to the terminal device 20 via the communication unit 21.

[0091] 12 is a diagram showing an example of mask wearing rate data according to the first embodiment. In this diagram, latitude and longitude indicating the range of an area and the mask wearing rate in that area are described, but other elements such as facility names may be added. Also, in this diagram, data in XML format is shown as an example of mask wearing rate data, but of course, the data is not limited to this and may be described in other formats.

[0092] When the control unit 28 of the terminal device 20 receives mask wear rate data from the management device 10 via the communication unit 21, it stores the mask wear rate data in the storage unit 29. The control unit 28 of the terminal device 20 generates a mask wear rate map based on the mask wear rate data and displays it on the display unit 22. Similarly to the mask wear rate map created by the management device 10 described above, the control unit 28 of the terminal device 20 may change the display format of areas and facilities depending on the mask wear rate. The control unit 28 may designate areas with a mask wear rate below a predetermined value (e.g., 60%) as areas with a high risk of virus infection (high-risk areas) and display the mask wear rate map on the display unit 22 in a different display format from other areas. For example, the terminal device 20 may display areas with a mask wear rate below a predetermined value in red and areas with a mask wear rate equal to or higher than the predetermined value in a normal color other than red. This allows the user to easily identify areas with a low mask wear rate and reduce the risk of virus infection. The control unit 28 of the terminal device 20 may create a mask wear rate map using three or more display formats depending on the mask wear rate. For example, the mask wearing rate map may be created so that areas where the mask wearing rate is less than a first predetermined value are displayed in red, areas where the mask wearing rate is equal to or greater than the first predetermined value and less than a second predetermined value greater than the first predetermined value are displayed in yellow, and areas where the mask wearing rate is equal to or greater than the second predetermined value are displayed in blue. Furthermore, the terminal device 20 is not limited to changing the display color according to the mask wearing rate, and may also change the display pattern (fill pattern) or font.

[0093] FIG. 13 is a diagram illustrating an example of a display on the terminal device 20 according to the first embodiment. This diagram illustrates an example of a screen configuration for notifying the user of the terminal device 20 that areas where the mask wearing rate is below a predetermined value are virus infection risk areas (high-risk areas) when a mask wearing rate map is displayed on the display unit 22 of the terminal device 20. In the example illustrated in this diagram, "Store A," "Store B," and "Station C" are indicated as high-risk areas by bold-line frames (rectangles). For example, if the predetermined value is "60%," in the example of FIG. 10, the mask wearing rates of "Store A," "Store B," and "Station C" are less than "60%," and therefore these facilities are extracted as high-risk areas. On the other hand, "Store D" is not in a high-risk area and is therefore indicated by a thin-line frame (rectangle). Of course, high-risk areas may be represented not only by line thickness but also by other display modes, such as by changing the display color.

[0094] 14 is a diagram showing another example of a display on the terminal device 20 according to the first embodiment. This diagram shows an example of the configuration of a screen (warning screen) that is displayed on the display unit 22 when the control unit 28 of the terminal device 20 acquires location information from the location identification unit 25 at predetermined intervals (for example, 10 seconds) and the mask wearing rate at the location where the user of the terminal device 20 is currently located is less than a predetermined value. In this case, the index generation unit 15 of the control unit 13 of the management device 10 may acquire the current location information of the terminal device 20 and, based on the information, determine the area Z for calculating the mask wearing rate P.

[0095] 13 and 14 on the display unit 22 of the terminal device 20, the audio output unit 24 may notify the user of the virus infection risk area as audio information. For example, the audio output unit 24 may output a warning sound (alert sound) or a warning message by voice synthesis.

[0096] 15 is a diagram showing another example of a display on the terminal device 20 according to the first embodiment. This diagram shows an example of the configuration of a screen (warning screen) that is displayed when the control unit 28 of the terminal device 20 acquires location information from the location identification unit 25 at predetermined intervals (for example, 10 seconds) and an area where the mask wearing rate is below a predetermined value is found in the direction in which the user of the terminal device 20 is moving. In this case, the index generation unit 15 of the control unit 13 of the management device 10 may acquire time-series data of the location information of the terminal device 20 or direction information included in the location information of the terminal device 20, and may determine the area Z for calculating the mask wearing rate P based on the acquired data.

[0097] As described above, according to the first embodiment, the management device 10 can easily obtain information about the mask wearing status of people in unspecified locations (wide or multiple regions) by effectively utilizing existing infrastructure such as smartphones and the Internet. Therefore, the management device 10 can easily and quantitatively calculate a mask wearing status index for each area. That is, without using a complex and expensive system as the infection prevention support system 1, an index showing the mask wearing status of an unspecified number of people in a wide area (multiple regions) can be easily and quantitatively calculated. Furthermore, by providing related information based on the wearing status index to the terminal device 20, the management device 10 can issue real-time infection prevention alerts to users in areas with a high risk of infection. This reduces the likelihood that users will approach high-risk areas, reducing the risk of virus infection for users and ultimately preventing the spread of infection.

[0098] Furthermore, since the user only needs to perform the normal operations for facial recognition and no special operations are required, the burden on the user is extremely low. Furthermore, when using facial recognition to unlock the UI, users generally perform facial recognition frequently to unlock the UI, so the user's mask-wearing information can be obtained frequently and in a natural way.

[0099] In the first embodiment, the management device 10 is configured to transmit the mask wearing rate map or mask wearing rate data created by the management device 10 to the terminal device 20. However, instead of this, the management device 10 may be configured to combine map information with areas with a high risk of infection and transmit it to the terminal device 20. In other words, the management device 10 may omit transmitting information about areas with a low risk of infection (areas with a high mask wearing rate) to the terminal device 20. Furthermore, the mask wearing rate data created by the management device 10 may be transmitted to a server of another system (not shown), and the mask wearing rate data may be used in that system.

[0100] <Modification of the First Embodiment> In the mask wearing rate calculation process of the first embodiment, in S110 of FIG. 6, the index generation unit 15 extracts records Rt from the mask information recorded in the mask information table 18, the records Rt having a reception time within a predetermined period of time compared to the current time CT. However, if multiple pieces of mask information for the same terminal device 20 are chronologically recorded in the mask information table 18 and a user of the same terminal device 20 unlocks the device multiple times using facial authentication within a short period of time, multiple pieces of mask information for the user of the same terminal device 20 may be extracted as records Rt. For example, the first and tenth records in FIG. 5 are mask information for a user with the terminal identifier "UE001," and a record containing these records is extracted as records Rt. In such a case, the mask wearing status of a particular user is more strongly reflected in the mask wearing rate, resulting in a decrease in the accuracy and reliability of the mask wearing rate. For example, if a user who unlocks using facial recognition multiple times in a short period of time is wearing a mask, the number of records Rm extracted in step S140 will be large, and as a result, when the mask wearing rate P is calculated in S150, the calculated mask wearing rate P may be higher than the actual rate. Conversely, if a user who unlocks using facial recognition multiple times in a short period of time is not wearing a mask, the calculated mask wearing rate P may be lower than the actual rate.

[0101] In this modification, when extracting records Rt in S110 of the flowchart in FIG. 6, the index generation unit 15 extracts only the record with the most recent reception date and time as record Rt for records with duplicate terminal identifiers. That is, the index generation unit 15 extracts the most recent record for one terminal device 20. This improves the calculation accuracy of the mask wearing rate P. When formula (1) is used in this modification, the mask wearing rate P is determined as the ratio of the number of terminal devices 20 whose wearing scores are equal to or greater than a predetermined threshold to the number of terminal devices 20 included in area Z (target area, predetermined area). In other words, the terminal devices 20 included in area Z may be considered target terminals, and the ratio of terminal devices 20 among the target terminals whose wearing scores are equal to or greater than a predetermined threshold may be determined as the mask wearing rate P. When formula (2) is used in this modification, the average value of the wearing scores of the terminal devices 20 included in area Z is determined as the mask wearing rate P. As described above, the mask wearing rate P may be calculated as a representative value rather than an average value. As with the mask wearing rate P, this modification improves the calculation accuracy of the rate for each wearing level. The index generation unit 15 may extract one record from one user using a user identifier that identifies the user instead of a terminal identifier. For example, when one user uses multiple terminal devices 20, one latest data for each user may be extracted from multiple data obtained by performing face authentication on the multiple terminal devices 20, and the mask wearing rate P may be calculated using the extracted data. That is, the ratio of the number of users whose wearing score is equal to or greater than a predetermined threshold to the number of users present in area Z may be taken as the mask wearing rate. In other words, users present in area Z may be considered as target users, and the ratio of target users whose wearing score is equal to or greater than a predetermined threshold may be taken as the mask wearing rate. Furthermore, a representative value of the wearing scores of users present in area Z may be taken as the mask wearing rate.

[0102] <Embodiment 2> Next, a second embodiment, which is a variation of the first embodiment, will be described. Because people often remove their masks in private spaces (private areas) such as private residences, mask wearing status indexes tend to be calculated as low in areas with many residential areas. Therefore, in the second embodiment, the mask wearing status information used in the calculation process for the mask wearing status index for area Z excludes the mask wearing status information of terminal devices 20 located in private spaces. Specifically, in the second embodiment, the control unit 13 of the management device 10 calculates the mask wearing status index for area Z using the mask wearing status information of only terminal devices 20 located in locations previously defined as public areas. In this case, the storage unit 17 of the management device 10 may store a public area table that defines the location information of public areas, and the control unit 13 may use the public area table to determine whether the terminal device 20 is located in a public area.

[0103] FIG. 16 is a diagram illustrating an example of the data structure of a public area table according to the second embodiment. For example, as illustrated in this figure, the public area table associates the names of facilities defined as public areas with the location information of the facilities. The location information in this figure defines the area (range) of the facility as a rectangle (rectangle) and indicates the location information (latitude, longitude) of the diagonal vertices of the rectangle. For example, the first row in FIG. 16 indicates that the facility name is "Department Store 1" and the area (range) of "Department Store 1" is a rectangle defined by two diagonal vertices, vertex 1 "(N011, E011)" and vertex 2 "(N012, E012)." Of course, FIG. 16 is merely an example, and the public area may be defined in any shape, not just a rectangle. Furthermore, the facility names and the number of facilities recorded in the public area table may be set arbitrarily, not limited to the example illustrated in FIG. 16. Furthermore, the public area table may associate the types of facilities defined as public areas (facility types) with the location information of facilities corresponding to those types. In this case, facility names such as "Department Store 1" and "Department Store 2" in FIG. 16 are unified into a facility type such as "Department Store." Alternatively, facility types such as "Store" or "Large-scale Retail Store" may be used. Furthermore, the facility names and facility types may be omitted from the public area table. In this case, only location information indicating the range of the public area is stored in the public area table. The public area table may be generated from a map database. Furthermore, the control unit 13 may acquire the public area table from an external server or the like as necessary. In this case, it is also possible to omit storing the public area table in the memory unit 17.

[0104] Next, the mask wearing rate calculation process procedure in this embodiment will be described. In this embodiment, in S110A (not shown), which corresponds to S110 in Fig. 6, the collection unit 14 extracts, from the records recorded in the mask information table 18, records Rt' whose reception time is within a predetermined period DT from the current time CT and whose location information of the terminal device 20 is included in the location information in the public area table. Specifically, record Rt' is extracted from records whose reception time satisfies the above-mentioned condition and whose location information in the mask information table 18 (location information of the terminal device 20) is included in the range specified by the location information in the public area table.

[0105] 6, the index generating unit 15 may extract, from the records Rt extracted in S110, records Ra' whose location information of the terminal device 20 is included in the section of the area Z selected in S120 and is included in the location information of the public area table. That is, S110A and S130 may be executed in combination, or S110 and S130A may be executed in combination. The other processes are the same as those in the first embodiment.

[0106] As described above, according to the second embodiment, the control unit 13 of the management device 10 calculates the mask wearing status index by taking into account the mask wearing status of users of only the terminal devices 20 located in public areas, thereby improving the accuracy of the mask wearing status index.

[0107] <Embodiment 3> Next, a third embodiment, which is a modification of the first embodiment, will be described. The third embodiment is characterized in that the control unit 13 of the management device 10 not only acquires mask information from the terminal device 20 but also frequently acquires location information of the terminal device 20 from the terminal device 20. In the first embodiment, the location of the terminal device 20 is identified using the location information included in the mask information. Therefore, when the terminal device 20 is moving and face authentication is not performed on the terminal device 20 for a long period of time, there is a problem that a discrepancy (deviation) occurs between the actual location of the terminal device 20 and the location information in the mask information table 18. In the third embodiment, a process is performed to solve this problem. In this embodiment, the terminal device 20 not only transmits mask information to the management device 10, but also transmits location information of the terminal device 20 to the management device 10 at a predetermined timing (for example, at a predetermined cycle) regardless of whether face authentication has been performed. At this time, the terminal device 20 associates a terminal identifier with the location information and transmits them. Alternatively, the terminal device 20 may associate a terminal identifier with the location information and the measurement date and time when the location information was measured and transmit them. The frequency with which the terminal device 20 transmits the location information is set higher than the frequency with which it transmits the mask information. For example, the terminal device 20 may transmit the location information every 10 seconds. The terminal device 20 may also detect that its own location information has changed and transmit the location information to the management device 10 in that case. In other words, the terminal device 20 may perform control such that it transmits the location information of its own device when the location information of its own device has changed, and does not transmit the location information of its own device when the location information of its own device has not changed.

[0108] When the control unit 13 of the management device 10 receives the location information of the terminal device 20 via the communication unit 11, it stores the information in the storage unit 17. In the following description, the received location information is stored in the mask information table 18, but this is not limiting. For example, the reception date and time (or measurement date and time), the terminal identifier, and the location information may be stored in another table in the storage unit 17 in association with each other. As described above, the management device 10 acquires the location information of the terminal device 20, for example, at predetermined intervals, even during the period from when it receives mask information from the same terminal device 20 until it receives the next mask information. The control unit 13 of the management device 10 updates the mask information table 18, assuming that the user's mask-wearing state remains unchanged, until it receives the next mask information.

[0109] FIG. 17 is a diagram for explaining the update process of the mask information table 18 of the management device 10 according to the third embodiment. This diagram illustrates a situation in which the management device 10 receives the latest location information "N100, E100" from the terminal device 20 with the terminal identifier "UE002" at "2020 / 9 / 10 10:38:19." At this time, the data received by the management device 10 from the terminal device 20 is location information, not mask information, and therefore does not include mask wearing status information. In response to obtaining the latest location information, the control unit 13 of the management device 10 adds a new record (first record) for the terminal device 20 with the terminal identifier "UE002." The control unit 13 registers "N100, E100" as the location information of the newly added record. The control unit 13 extracts the most recent record (the 12th record) with the terminal identifier "UE002" as the wearing score, and registers the wearing score of the most recent record ("41" in this example) as the wearing score of the new record (the first record). That is, the control unit 13 adds a record that associates new location information acquired from the terminal device 20, the terminal identifier, and the most recently acquired wearing score of the user of the terminal device 20, and updates the mask information table 18. In this embodiment, the wearing status index calculation process is performed using the mask information table 18 in which location information is updated frequently. Note that in this embodiment, since many records with the same terminal identifier exist in the mask information table 18, it is desirable to perform the wearing status index calculation process using the method of the modification of the first embodiment. Of course, the modification of the first embodiment, the second embodiment, and the third embodiment may be combined and executed.

[0110] According to this embodiment, even if the terminal device 20 moves after transmitting the mask information, the management device 10 can reflect the latest location information of the terminal device 20 in the mask wearing status index. This allows the mask wearing status index for a specified area to be calculated with higher accuracy. This allows the user of the terminal device 20 to be provided with information for preventing virus infection with higher accuracy.

[0111] If the control unit 13 does not receive mask information from the same terminal device 20 after a predetermined time has elapsed, the control unit 13 may stop the process of adding a new record for that terminal device 20. This is because if a long time has elapsed, it is highly likely that the user's mask wearing state has changed.

[0112] In this embodiment, the terminal device 20 included in the target area is identified using the current location information of the terminal device 20, but this is not limited to this. For example, the management device 10 may acquire time-series data on the location information of the terminal device 20 or information on the movement speed and movement direction of the terminal device 20, and based on this, predict the location information of the terminal device 20 in the future (a predetermined time after the present), and identify the terminal device 20 included in the target area using the predicted location information. Also, for example, the user of the terminal device 20 may specify the location of the terminal device 20 at a future time, the management device 10 may acquire the specified location information, and use the location information to identify the terminal device 20 included in the target area. For example, the user of the terminal device 20 may specify on a map the location where the user plans to be located "30 minutes from now," and the management device 10 may acquire the location information and perform processing.

[0113] <Embodiment 4> Next, a description will be given of a fourth embodiment, which is a modification of the first embodiment. The fourth embodiment is characterized in that the management device 10 generates route information for guiding the user to the destination while avoiding areas with a high risk of infection.

[0114] For example, when a user specifies a destination via the input unit 23 of the terminal device 20, the control unit 28 of the terminal device 20 transmits the departure point information and the destination information to the management device 10 via the communication unit 21. The departure point information may be the current location of the terminal device 20 or the departure point specified by the user.

[0115] The index generation unit 15 of the control unit 13 of the management device 10 determines an area for which an index is to be calculated based on the received departure point information and destination information, and calculates a wearing status index for that area. Next, the index generation unit 15 generates route guidance information that indicates a route from the departure point to the destination based on the departure point information, destination information, map information, and the wearing status index for the area. The communication unit 11 of the management device 10 then transmits the generated route guidance information to the terminal device 20, and causes the display unit 22 of the terminal device 20 to display the route guidance information.

[0116] Below, a specific process for generating route guidance information will be described in the case where the mask wearing rate is calculated as the wearing status index, but the process is not limited to this.

[0117] First, the index generating unit 15 of the control unit 13 of the management device 10 searches for a route from the current location of the terminal device 20 or a starting point designated by the user to the destination. At this time, the index generating unit 15 refers to the map database (map information) 19 stored in the storage unit 17 and the mask wearing rate map data, and searches for a route to the destination that avoids dangerous areas.

[0118] The index generation unit 15 may also generate multiple (N) routes (route candidates) from the departure point to the destination, calculate an index S for each route according to the following formula (3), and select the route with the smallest index S as the optimal route.

[0119]

number

[0120] 18 is a diagram showing an example of a display on the terminal device 20 according to the fourth embodiment. In this diagram, the destination is indicated by a diagonally shaded circle, and the optimal route to the destination with a low risk of virus infection is indicated by a dotted line. Note that the process of deriving a route by preferentially selecting points with a high rate of mask wearing described above may be performed by the control unit 28 of the terminal device 20 instead of the control unit 13 of the management device 10.

[0121] When the display unit 22 of the terminal device 20 displays the screen shown in this figure, the audio output unit 24 may notify the user of the virus infection risk area as audio information. For example, the audio output unit 24 may provide audio guidance on the optimal route. Also, for example, the audio output unit 24 may notify the user of information on the virus infection risk area by audio.

[0122] As described above, according to the fourth embodiment, the user can avoid passing through areas with a high risk of infection, thereby further reducing the risk of infection for the user. In other words, information regarding user behavior that leads to preventing virus infection can be conveyed to the user of the terminal device 20 in an easy-to-understand manner. Note that in this embodiment, map information is used to generate route guidance information, but this is not limited to this. For example, in an environment where the user can pass through any position, such as when the user is passing through a large square, route guidance information can also be generated without using map information including road information.

[0123] <Embodiment 5> Next, a fifth embodiment, which is a modification of the first embodiment, will be described. In the first to fourth embodiments, the control unit 13 of the management device 10 calculates a mask wearing status index for each area in real time based on the most recent mask information of the user of the terminal device 20, and notifies the user of areas with a high infection risk. In the fifth embodiment, the index generation unit 15 of the control unit 13 of the management device 10 aggregates past, i.e., mask wearing status information collected up to the present time, and predicts future, i.e., future, wearing status indexes from the present time onward, using the aggregated information. Specifically, the index generation unit 15 calculates wearing status indexes by area and by day, for example, from one month ago to the present, based on the past mask wearing status information. Next, the index generation unit 15 calculates future wearing status indexes by area and by day, based on the past wearing status indexes by area and by day. This makes it possible to predict days and areas with a low wearing status index, i.e., high infection risk. The communication unit 11 or the output unit 16 of the management device 10 then outputs information related to the predicted index. Of course, the present invention is not limited to predicting the wearing status index on a daily basis. For example, the wearing status index may be predicted by time of day, by day of the week, or by a combination of day of the week and time of day (day of the week and time of day).

[0124] In the following, the prediction process of the wearing status index will be described using an example in which the mask wearing rate is calculated as the wearing status index, but this is not limiting. For example, the rate for each wearing level in each area may be predicted.

[0125] In the fifth embodiment, the index generating unit 15 of the control unit 13 of the management device 10 sets a reference date and time AT for calculating the mask wearing rate in S100B (not shown), which corresponds to S100 in FIG. 6 of the first embodiment. Then, the index generating unit 15 proceeds to S110B (not shown), which corresponds to S110. In S110B, the index generating unit 15 extracts, as records Rt, records whose reception time is after the reference date and time AT and is included in a period from the reference date and time AT until a predetermined period DT (e.g., 24 hours) has elapsed. Note that in the fifth embodiment, when the collecting unit 14 records mask information received from the same terminal device 20 in the mask information table 18, it does not overwrite the existing record but adds a new record and records it. In other words, the mask information table 18 records not only the latest mask information but also past mask information. Then, the index generating unit 15 proceeds to S120.

[0126] For example, when calculating the mask wearing rate for the date "2020 / 8 / 20," the index generation unit 15 sets the reference date and time AT to "2020 / 8 / 20 00:00:00" in S100B. Next, in S110B, the index generation unit 15 uses "24 hours" as the predetermined period DT, extracts mask information from "2020 / 8 / 20 00:00:00" to "2020 / 8 / 20 23:59:59" as record Rt, and calculates the mask wearing rate for the date "2020 / 8 / 20" in a later step. For example, in S100B, the index generation unit 15 can calculate the mask wearing rate for each day for the past month by repeating the processing of the flowchart shown in FIG. 6 while shifting the reference date and time AT by one day each month over the past month and setting it to midnight every day. The index generating unit 15 calculates the past mask wearing rate, and then predicts the mask wearing rate from now on based on the data of the past daily mask wearing rate.

[0127] For example, the index generation unit 15 calculates the mask wearing rate M[t] in a specified area at a future time t based on the mask wearing rates M[t-1], M[t-2], M[t-3], etc. in the specified area at past times t-1, t-2, t-3, etc., according to the following equation (4).

[0128]

number

[0129] Furthermore, the index generating unit 15 may predict the mask wearing rate using information on the day of the week and temperature in addition to the past mask wearing rate. For example, the index generating unit 15 may predict the mask wearing rate according to the following formula (5).

[0130]

number

[0131] Furthermore, the index generation unit 15 may predict (calculate) the future mask wearing rate based on data such as time of day, weather, population density, local events, etc. The control unit 13 transmits the predicted data and past data of the mask wearing rate thus generated to the terminal device 20 via the communication unit 11.

[0132] FIG. 19 is a diagram illustrating a mask-wearing rate prediction result according to the fifth embodiment. The terminal device 20 may display the graph shown in FIG. 19 on the display unit 22 based on the mask-wearing rate prediction data received from the management device 10. This graph illustrates a prediction of the mask-wearing rate from now on based on the past mask-wearing rate in a certain area. In this diagram, the current date is "September 10, 2020." The solid bars indicate the past mask-wearing rate, while the diagonally shaded bars indicate the predicted mask-wearing rate. In this example, the mask-wearing rate in the area decreases toward the weekend, so the mask-wearing rate is predicted to decrease on weekends after "September 10, 2020." Local event information may also be displayed on this graph. For example, if a movie theater in the target area holds an appreciation day on the 20th of each month, or if a shopping mall offers bonus points on days ending in the number 3, such event information may be superimposed on the graph. In other words, event information regarding potential increases or decreases in the number of people in the target area or changes in customer demographics may be displayed. This allows the administrator of the management device 10 or the user of the terminal device 20 to easily understand the relationship between changes in the mask wearing rate and the day of the week, date, and event information.

[0133] The index generation unit 15 of the control unit 13 of the management device 10 predicts the future mask wearing rate for each area for which the past mask wearing rate has been calculated, and then compiles these data to create mask wearing rate prediction data. The mask wearing rate prediction data is data that predicts the mask wearing rate for each area from the present onwards. The index generation unit 15 distributes the mask wearing rate prediction data created in this example to the terminal device 20 via the communication unit 11.

[0134] FIG. 20 is a diagram showing an example of mask wearing rate prediction data distributed from the management device 10 to the terminal device 20. In the example shown in this figure, the latitude and longitude of each area, and the mask wearing rate in that area are described for each day from the present (today) onwards. Of course, the mask wearing rate prediction data may also include data on past mask wearing rates. Also, as in the first embodiment, this figure shows an example of mask wearing rate prediction data described in XML format, but of course this is not limited to this and other formats may also be used for description.

[0135] When the control unit 28 of the terminal device 20 receives mask wearing rate prediction data from the management device 10 via the communication unit 21, the control unit 28 records the mask wearing rate prediction data in the storage unit 29. The control unit 28 of the terminal device 20 creates a mask wearing rate prediction map based on the mask wearing rate prediction data and displays it on the display unit 22. As in the first embodiment, the control unit 28 may change the display format of the mask wearing rate prediction map depending on the mask wearing rate. For example, the lower the predicted mask wearing rate, the more noticeable the display format may be set. Furthermore, the control unit 28 may designate areas in the mask wearing rate prediction map where the mask wearing rate is below a predetermined value (e.g., 60%) as areas with a high risk of virus infection (high-risk areas), and display information about the high-risk areas on the display unit 22.

[0136] 21 is a diagram showing an example of a display on the terminal device 20 according to the fifth embodiment. This diagram shows an example of the configuration of a screen for notifying the user of the terminal device 20 when a scheduler (schedule management application) of the terminal device 20 or the like determines that the mask wearing rate on the date and location where the user plans to travel is below a predetermined value. When the screen shown in this diagram is displayed on the display unit 22 of the terminal device 20, the audio output unit 24 may notify the user of the virus infection risk area as audio information.

[0137] Furthermore, when a user of the terminal device 20 searches for stores, the management device 10 may notify the user of the terminal device 20 of days with a high infection risk (days with a low mask wearing rate) based on the predicted mask wearing rate of each searched store. An example of the screen configuration of the terminal device 20 in this case is shown in FIG. 22. FIG. 22 is a diagram showing an example of a display on the terminal device 20 according to the fifth embodiment. As shown in this figure, for example, the display unit 22 of the terminal device 20 displays predicted information on the infection risk for each day of the week for the searched facilities or stores. This figure shows an example in which the infection risk for each store for that week is displayed at the beginning of the week (Monday). Days of the week or stores with a high mask wearing rate are displayed as "safe," and days of the week or stores with a low mask wearing rate are displayed as "risky." Of course, predicted information on the infection risk may also be displayed by time of day or by day of the week and time of day. Furthermore, information based on past mask wearing rates (actual measurements) may be displayed in addition to information based on predicted mask wearing rates. For example, the infection risk for each store by day of the week may be displayed based on the mask wearing rate for each day of the past four weeks. For example, the mask wearing rate for each day over the past four weeks and the average rate for each day of the week can be calculated, and the infection risk for each store for each day of the week can be displayed based on the average mask wearing rate for each day of the week.

[0138] Although the fifth embodiment describes a process for predicting the mask wearing rate from the present onward on a daily basis based on past mask wearing rates, the time range for prediction is not limited to this. For example, the index generation unit 15 of the control unit 13 of the management device 10 may calculate the past mask wearing rate every hour. In this case, the index generation unit 15 may specify the reference date and time AT for calculating the mask wearing rate in one-hour increments in S100B and set the predetermined period DT to one hour in S110B. This makes it possible to calculate the mask wearing rate on an hourly basis. By predicting the mask wearing rate on an hourly basis, it is possible to predict time periods with low mask wearing rates. Of course, one-hour increments are merely an example, and the mask wearing rate may be predicted in any time interval, such as 30 minutes. Furthermore, the mask wearing rate may be predicted for each combination of day of the week and time period. For example, the mask wearing rate may be calculated for each day of the week and time period, such as "Friday 6:00 PM to 7:00 PM" or "Friday 7:00 PM to 8:00 PM."

[0139] As described above, according to the fifth embodiment, the management device 10 can predict the wearing status index from the present onwards (future) by calculating the wearing status index for each predetermined period from past mask wearing status information. By predicting the wearing status index from the present onwards, it becomes possible to notify the user of the terminal device 20 in advance of areas with a high risk of infection. This makes it possible to reduce the risk of the user of the terminal device 20 being infected with a virus.

[0140] In the fifth embodiment, the management device 10 transmits the mask wearing rate prediction data to the terminal device 20, and the terminal device 20 notifies the user of areas predicted to have a high infection risk. However, instead of this, the management device 10 may also transmit past mask wearing rates to the terminal device 20 and display them as a graph on the display unit 22 of the terminal device 20. In other words, the management device 10 may omit future mask wearing rate data and transmit only past mask wearing rate data. Furthermore, the management device 10 may transmit the mask wearing rate prediction data to a server of another system (not shown), and the mask wearing rate prediction data may be used in that system. Furthermore, the management device 10 may create a mask wearing rate prediction map and distribute it to the terminal device 20 or another device.

[0141] <Embodiment 6> Next, a sixth embodiment, which is a variation of the fifth embodiment, will be described. In the fifth embodiment, the index generating unit 15 of the control unit 13 of the management device 10 calculated a daily mask wearing status index from past mask wearing status information and predicted the current and future mask wearing status indexes. In the sixth embodiment, the index generating unit 15 predicts the future virus infection status based on the daily mask wearing status index calculated from the past mask wearing status information. Then, the communication unit 11 or the output unit 16 of the management device 10 outputs information related to the predicted number of virus infections.

[0142] Below, an example will be described in which the mask wearing rate is calculated as the wearing status index, but this is not limiting. As in the fifth embodiment, the index generation unit 15 calculates the daily mask wearing rate from past mask wearing status information. Then, the index generation unit 15 predicts the future virus infection situation, for example, the number of virus infected people, based on the past mask wearing rate. The index generation unit 15 may also predict the future number of infected people based on the past number of virus infected people in addition to the past mask wearing rate.

[0143] As mentioned above, the number of infected people by region is announced daily by the national government, local governments, etc. Therefore, first, the collection unit 14 of the control unit 13 of the management device 10 acquires the history of the number of infected people by day from an external server device.

[0144] The index generation unit 15 then calculates the daily wearing status index described in embodiment 5, and predicts the future number of virus infections based on the daily number of infected people obtained from an external server device and the daily wearing status index.

[0145] Specifically, the index generation unit 15 uses the mask wearing rates M[t-1], M[t-2], etc. at past times t-1, t-2 in a specified area and the number of infected people Q[t-1], Q[t-2], etc. to predict the number of infected people Q[t] in the area at a future time t according to the following equation (6).

[0146]

number

[0147] That is, the index generation unit 15 creates a statistical model with the past mask wearing rate and the past number of infected people as independent variables and the future number of infected people as dependent variables, and optimizes parameters (coefficients) using data on the past mask wearing rate and the past number of infected people. The index generation unit 15 may use only the past mask wearing rate as an independent variable, without using the past number of infected people. In this case, acquisition of past data on the number of infected people can be omitted. The index generation unit 15 may also add population density, temperature, the level (status) of warnings (alerts) issued by the national or local government, etc., to the independent variables. The control unit 13 transmits the thus generated predicted information on the number of infected people to the terminal device 20 via the communication unit 11. At this time, predicted data (and past data) on the mask wearing rate may be transmitted from the management device 10 to the terminal device 20, as described in the fifth embodiment.

[0148] FIG. 23 is a diagram illustrating an example of a result of predicting the number of infected people according to the sixth embodiment. The terminal device 20 may display the graph shown in FIG. 23 on the display unit 22 based on the mask wear rate prediction data received from the management device 10. This graph shows the mask wear rate and the number of infected people for each date in a certain region. In this graph, the bar graph indicates the mask wear rate, and the line graph indicates the number of infected people. As in FIG. 19, the current date in this graph is "September 10, 2020," the solid bars indicate the past mask wear rate, and the diagonal bars indicate the predicted mask wear rate. Furthermore, the black circles (●) on the line graph indicate the past number of infected people, and the white circles (○) indicate the predicted number of infected people in the future. The management device 10 may transmit the graph shown in this graph or data capable of drawing the graph shown in this graph to the terminal device 20. In this region, the mask wear rate decreased daily from late August to around September 1, 2020, partly due to the relatively low number of infected people in late August. The number of infected people is expected to increase sharply approximately two weeks later, around September 14, 2020. The graph in this figure shows a rapid increase in the predicted number of infected people in the area, allowing users of the terminal device 20 (ordinary people) to determine the need to ensure they wear masks and refrain from going out. Local government officials can also determine the need to encourage mask wearing, improve medical facilities, and request shorter hours for restaurants. Observing this graph also allows them to determine the likelihood that the increase in the number of infected people is due to a decline in mask wearing rates. Note that the graph in Figure 23 may omit the future mask wearing rate and future number of infected people and instead display the past mask wearing rate and past number of infected people. Even with this display, the relationship between mask wearing rates and the number of infected people can be easily understood. In particular, the administrator (operator) of the management device 10 can use this graph to understand the relationship between mask wearing rates and the number of infected people and incorporate this knowledge into the statistical model of Equation (6). In other words, by creating a graph that clearly shows past mask wearing rates and past numbers of infected people, it becomes possible to build a more accurate statistical model, thereby improving the accuracy of predicting the number of infected people.Furthermore, a graph that allows users of the terminal device 20 to easily understand the relationship between the past mask wearing rate and the number of infected people is also useful.

[0149] Furthermore, when it is predicted that the number of infected people in a given area will increase in the future, the control unit 13 of the management device 10 may distribute alert information to the terminal devices 20 present in the given area.

[0150] 24 is a diagram showing an example of a display on the terminal device 20 according to embodiment 6. When the control unit 28 of the terminal device 20 receives alert information from the management device 10, the control unit 28 causes the display unit 22 to display the screen shown in this figure.

[0151] Furthermore, the control unit 28 of the terminal device 20 may display alert information tailored to the user's behavioral tendencies or schedule in cooperation with the user's behavioral history and data from the schedule management app. For example, if a high number of infected people is predicted at the date, time, and location registered in the schedule management app, the control unit 28 of the terminal device 20 may cause the display unit 22 to display alert information. Furthermore, the control unit 28 may estimate locations and dates and times that the user is likely to visit in the future based on the user's past behavioral history, and if a high number of infected people is predicted at those dates, times, and locations, the control unit 28 may cause the display unit 22 to display alert information. Furthermore, the control unit 28 may control the schedule management app to suggest to the user that they change their behavior plan (date, time, and location).

[0152] The control unit 13 of the management device 10 may transmit information about the predicted number of infected people to devices (not shown) of medical institutions in the area, thereby prompting the medical institutions to quickly take preventive measures such as increasing the number of beds and staff.

[0153] As described above, according to the sixth embodiment, the management device 10 can predict the future number of infected people based on the past mask wearing status information for each region (area). Furthermore, by predicting the trend in the number of infected people from the transition of the mask wearing status index, the management device 10 can alert the user of the terminal device 20. This makes it possible to reduce the possibility that the user of the terminal device 20 will be infected with a virus.

[0154] <Embodiment 7> Next, a seventh embodiment will be described. In the first to sixth embodiments, the management device 10 generates a mask wearing status index for a wide or multi-regional area and generates information for preventing the spread of infection based on the mask wearing status index. In contrast, in the seventh embodiment, the management device provides information for reducing the risk of infection to each user in a wide or multi-regional area according to the user's surroundings. More specifically, when there is another person not wearing a mask near each user, the management device notifies each user of information urging caution (attention alert information).

[0155] The infection prevention support system 1 according to the seventh embodiment has the same configuration as that shown in Fig. 1, but includes a management device 100 instead of the management device 10. The management device 100 is a server computer connected to the Internet NW. Based on data received from each of the multiple terminal devices 20 via the relay device 30, the management device 100 identifies an area near a terminal device 20 whose mask wearing status information does not meet a predetermined standard as a high-risk area, and notifies the other terminal devices 20 located within the high-risk area.

[0156] The terminal device 20 according to the seventh embodiment has the same configuration as that shown in FIG. 2 described in the first embodiment. However, some of the terminal devices 20 included in the infection prevention support system 1 may omit the facial authentication unit 26 and the imaging unit 27. That is, all of the terminal devices 20 included in the infection prevention support system 1 may have the same configuration as that shown in FIG. 2, or some of the terminal devices 20 may have the same configuration as that shown in FIG. 2, with the remaining terminal devices 20 omitting the facial authentication unit 26 and the imaging unit 27. If a terminal device 20 omits the facial authentication unit 26 and the imaging unit 27, the terminal device 20 does not transmit mask information, but transmits user location information including location information and a terminal identifier to the management device 100 at a predetermined timing. On the other hand, a terminal device 20 having the same configuration as that shown in FIG. 2 transmits mask information including mask wearing status information, location information, and a terminal identifier to the management device 100. 2 may transmit mask information (information including mask wearing status information) at a first timing and transmit user position information (position information without mask wearing status information) at a second timing, as in embodiment 3. For example, the frequency of the second timing may be increased (the cycle may be shortened) compared to the first timing.

[0157] 25 is a block diagram showing an example of the configuration of the management device 100 according to the seventh embodiment. The management device 100 includes a communication unit 110, a timer unit 120, a control unit 130, and a storage unit 170.

[0158] The communication unit 110 corresponds to the above-mentioned communication unit 11. The clock unit 120 corresponds to the above-mentioned clock unit 12.

[0159] The control unit 130 controls each component of the management device 100. The control unit 130 may be configured with a CPU, and the control unit 130 may execute a program stored in the storage unit 170 to perform each process of the management device 100. The control unit 130 includes a collection unit 140 and an identification unit 150.

[0160] The collection unit 140 corresponds to the collection unit 14 described above and collects mask wearing state information of the user of the terminal device 20 and location information of the terminal device 20. In the seventh embodiment, like the collection unit 14 described above, the collection unit 140 receives mask information from each terminal device 20 that transmits the mask information, and records the mask wearing state information of the user and the location information of the terminal device 20 included therein in the mask information table 180 of the storage unit 170. As described above, the mask wearing state information is generated based on a face image for user authentication captured by the terminal device 20. The collection unit 140 also receives user location information from the terminal device 20 via the communication unit 110. As described above, the terminal device 20 transmits user location information without mask wearing state information, but the collection unit 140 collects this location information. When the collection unit 140 receives user location information, it acquires the current time (reception date and time) from the clock unit 120 and records the reception date and time, location information, and a terminal identifier in the user location information table 190. Basically, the location information transmitted by the terminal device 20 is the location information of the terminal device 20, and therefore the user location information table 190 is also called a terminal location information table. However, for example, if the user is wearing a wearable device such as a smartwatch, the terminal device 20 may transmit the location information of the wearable device. In this case, even if the terminal device 20 and the user are slightly separated from each other, the terminal device 20 notifies the management device 100 of the user's exact location. Of course, the control unit 130 and the collection unit 140 may be configured integrally.

[0161] When the mask wearing state information received from the terminal device 20 does not satisfy a predetermined criterion, the identification unit 150 identifies a range within a predetermined distance R from the location of the terminal device 20 that transmitted the mask wearing state information as a high-risk area HA. ​​Here, cases where the mask wearing state information does not satisfy the predetermined criterion include cases where the mask wearing score is below a predetermined value or the mask wearing level is below a predetermined level. The identification unit 150 then identifies the terminal device 20 located in the high-risk area HA based on the collected location information of the terminal device 20. Here, a terminal device 20 whose mask wearing state information does not satisfy the predetermined criterion may be referred to as a first terminal device 20, and other terminal devices 20 located within the high-risk area HA may be referred to as a second terminal device 20. The second terminal device 20 may include a terminal device 20 that has not transmitted mask wearing state information (a terminal device 20 that transmitted only user location information). The identification unit 150 then generates alert information indicating that the user is located in the high-risk area HA and notifies the second terminal device 20 of the alert information via the communication unit 110. In other words, the warning information is information that indicates that there is a high possibility of virus infection to other users who are in the vicinity (nearby) of the user of the first terminal device 20. Of course, the control unit 130 and the identification unit 150 may be configured integrally.

[0162] The storage unit 170 is configured with a storage medium that stores data and programs used for various processes of the management device 100. The storage unit 170 stores a mask information table 180 and a user position information table 190. The mask information table 180 corresponds to the above-mentioned mask information table 18. The mask information table 180 may have the same data structure as the mask information table 18.

[0163] The user position information table 190 stores user position information. FIG. 26 is a diagram illustrating an example of the data structure of the user location information table 190 according to the seventh embodiment. The user location information table 190 records, for each terminal device 20, the reception date and time, location information, and a terminal identifier. (A), (B), and (C) of the figure respectively show user location information tables 190-1, 190-2, and 190-3 corresponding to the terminal devices 20 with the terminal identifiers "UE001," "UE002," and "UE003." The reception date and time are recorded as the date and time when the management device 100 received the user location information from the terminal device 20. Note that the notation "2020 / 9 / 10 10:33:20," which is the record of the reception date and time, represents "September 10, 2020, 10:33:20." Note that the figure illustrates an example in which the terminal device 20 transmits user location information to the management device 100 every 10 seconds. The location information and terminal identifier include the location information (latitude, longitude) and terminal identifier included in the user location information received from the terminal device 20. The interval at which the terminal device 20 transmits the user location information is not limited to 10 seconds and may be, for example, 1 second, and is arbitrary. Furthermore, the transmission is not limited to a predetermined cycle. For example, the location information may be transmitted when the user (terminal device 20) has moved a predetermined distance or more since the location information previously transmitted. Furthermore, the management device 100 may store, in the user location information table 190, location information of a terminal device 20 (terminal identifier) ​​that is not stored in the mask information table 180 (see FIG. 5). In other words, the user location information table 190 may store both location information of a terminal device 20 that has acquired mask-wearing state information and location information of a terminal device 20 that has not acquired mask-wearing state information.

[0164] When the collection unit 140 of the control unit 130 of the management device 100 receives user location information from a terminal device 20, it adds a new record to the user location information table 190. If the number of records in each table exceeds a predetermined number, for example, 10,000, the collection unit 140 may delete records in order of reception date and time, starting with the oldest. Alternatively, if the capacity of the user location information table 190 exceeds a predetermined value, for example, 1 TB, the collection unit 140 may delete records in order of reception date and time, starting with the oldest. Alternatively, the collection unit 140 may delete records whose reception date and time exceeds a predetermined time, for example, one month, compared to the current time. Note that, for the sake of explanation, the user location information table 190 is shown in descending order of reception date and time in this figure. Also, for the sake of explanation, the user location information table 190 is configured so that it is divided for each terminal device 20 in this figure, but the user location information of all terminal devices 20 may be recorded in a single user location information table 190.

[0165] FIG. 27 is a flowchart illustrating an example of an information provision process according to the seventh embodiment. The control unit 130 of the management device 100 executes the information provision process at a predetermined timing, for example, every minute. The information provision process is a process of transmitting alert information to users who are near users who are unlikely to be wearing masks. The information provision process is also referred to as a "risk reduction process" or an "infection risk reduction process." Note that, hereinafter, the term "low likelihood of wearing a mask" may include not only not wearing a mask but also having a mask wearing level below a predetermined level. For example, it may include having a mask wearing score below a predetermined value. Furthermore, "users unlikely to be wearing a mask" may also be referred to as "mask-unaware users." However, "mask-unaware users" may include not only users who are not wearing a mask but also users whose mask wearing level is below a predetermined level, for example, by not completely covering their mouth and nose with a mask. In other words, mask-unaware users are users whose mask wearing status information does not meet a predetermined standard.

[0166] First, in S200, the identification unit 150 of the control unit 130 of the management device 100 acquires the current time CT from the clock unit 120. After that, the identification unit 150 advances the process to S210.

[0167] In S210, the identification unit 150 refers to the mask information table 180 in the storage unit 170 and extracts, as record Re, records that satisfy a predetermined condition from the mask information recorded in the mask information table 180. For example, the identification unit 150 extracts, for each terminal identifier, records whose latest mask wearing score is equal to or less than a predetermined value S (threshold value S) as record Re. The predetermined value S may be, for example, "60," but is not limited to this value. Alternatively, the identification unit 150 may select, for each terminal identifier, records whose latest mask wearing score is equal to or less than the predetermined value S and whose latest reception time is within a predetermined period DT1, for example, 5 minutes, from the current time CT as record Re. In other words, record Re is information about users who are unlikely to have worn a mask recently. It can also be said that record Re is information about users who are at a high risk of infecting others. After that, the identification unit 150 proceeds to S220.

[0168] In S220, the identification unit 150 creates a location information list P based on record Re. The location information list P stores the terminal identifier of record Re and the location information of the terminal device 20 in association with each other. Specifically, the identification unit 150 creates the location information list P using one of the following methods. The first method is to enter the location information of record Re directly into the location information list P. Although this method is simple, if time has passed since the data was recorded in the mask information table 180, the location of a user (of the terminal device 20) at high risk of infection may have changed, resulting in an error. The second method is to extract the terminal identifier of record Re, identify the latest location information that matches the terminal identifier in the user location information table 190, and enter the location information into the location information list P. This method can identify the location information of users at high risk of infecting others with higher accuracy. In other words, the location information list P is a list of location information of users who are unlikely to be wearing masks. The number of terminal devices 20 (terminal identifiers) recorded in the location information list P is arbitrary, and may be one or more. Furthermore, if there is no terminal device 20 that matches the extraction condition of record Re in S210, the location information list P becomes empty (NULL). After that, the identifying unit 150 advances the process to S230.

[0169] In S230, the identification unit 150 creates a high-risk area map. FIG. 28 is a diagram showing an example of the configuration of a high-risk area map according to the seventh embodiment. In the high-risk area map, an area at a distance R from the location information recorded in the location information list P, i.e., the location of a user not wearing a mask, is set as a high-risk area HA. ​​The distance R may be set to, for example, 2 meters, but is not limited to this and may be set to 3 meters, 5 meters, or the like. In other words, the distance R may be set at a distance at which there is a risk of transmitting a virus to those around through droplets of saliva, sneezing, or the like. Note that while FIG. 28 shows the high-risk area HA as a circular area with a radius R, it may also be configured as a rectangular area centered on the location information of a user who is unlikely to be wearing a mask.

[0170] The identification unit 150 of the control unit 130 may also set the distance R according to the temperature and humidity of the day. For example, in an environment with low temperature and low humidity, viruses are more likely to activate and droplets are more likely to travel farther, so the identification unit 150 sets the distance R longer. On the other hand, in an environment with high temperature and high humidity, the identification unit 150 sets the distance R shorter. The identification unit 150 may also set the high-risk area HA according to wind direction and wind speed. Specifically, the high-risk area HA may be set wider in the downwind direction, where viruses are more likely to spread. For example, in an area where the wind blows from east to west, the high-risk area HA may be set wider west of the position (reference position) recorded in the position information list P than east of that position (downwind direction). In this case, the high-risk area HA does not have to be circular or rectangular, and may be, for example, an ellipse with its center west of the reference position and longer east-west than north-south. In other words, the high-risk area may have any shape. The high-risk area HA may also be set according to wind speed. For example, if the wind speed satisfies a predetermined condition, the high-risk area HA may be set to be wider than usual. The predetermined condition may be a range of wind speeds that makes it easy for viruses to scatter and to remain in a certain location to a certain extent. In other words, the identification unit 150 may set the high-risk area HA according to weather conditions.

[0171] The identification unit 150 may also set the distance R according to the number of terminal devices 20 per unit area, i.e., the terminal density (hereinafter also referred to as population density). For example, when the population density is high, the distance R is shortened to prevent the amount of warning information (described later) from becoming too large, which may confuse users or cause them to stop paying attention. On the other hand, when the population density is low, the distance R is lengthened because there is less concern that the amount of warning information will become too large. In this way, by changing the range (size and shape) of the high-risk area HA according to the surrounding environment, such as weather conditions and population density, it is possible to appropriately set the area where there is a risk of virus infection. Note that the identification unit 150 may store the information of the high-risk area HA set in S230 in the location information list P, or may store it as other data in the storage unit 170. For example, the identification unit 150 may associate a terminal identifier, location information, and information such as the range of the high-risk area HA with each other and store them in the location information list P.

[0172] The description will continue by returning to Fig. 27. After executing S230, the identification unit 150 advances the process to S240.

[0173] In S240, the identification unit 150 refers to the user position information table 190 in the storage unit 170 and extracts a record that satisfies a predetermined condition as record Rc. For example, the identification unit 150 selects the latest record for each terminal identifier as record Rc. Alternatively, the identification unit 150 selects the latest record for each terminal device 20, whose reception time is within a predetermined period DT2, for example, 1 minute, from the current time CT, as record Rc. Thereafter, the identification unit 150 proceeds to S250.

[0174] In S250, the identification unit 150 refers to the record Rc and the location information list P, and records the terminal identifier of the record whose location information falls within an area set as a high risk area HA in the high risk area map in the terminal device list T, thereby creating the terminal device list T. That is, the terminal device list T records information about users who are present in the vicinity of users who are unlikely to be wearing masks recently.

[0175] FIG. 29 is a diagram showing an example of the data structure of the terminal device list T according to the seventh embodiment. For example, the terminal device list T associates the area identifier of the high-risk area HA with a "first terminal identifier" that is the terminal identifier of the first terminal device 20 that formed the high-risk area HA, the wearing score of the user of the first terminal device, the distance R of the high-risk area HA, and a "second terminal identifier" that is the terminal identifier of another terminal device 20 located within the high-risk area HA. ​​Note that the fields for the first terminal identifier, the wearing score, and the distance R may be omitted. Although not shown in this figure, the terminal device list T may further include location information (latitude, longitude) that defines the shape, size, and area of ​​each high-risk area HA.

[0176] Here, the identification unit 150 identifies a terminal device 20 different from the first terminal device 20 as a second terminal device 20, and records its terminal identifier as a second terminal identifier in the terminal device list T. For example, if the wearing score of terminal device "UE001" is lower than a predetermined standard, a high-risk area "HA001" is formed centered around the position of terminal device "UE001." If terminal devices "UE002" and "UE003" are located in the high-risk area "HA001," the identification unit 150 records terminal devices "UE002" and "UE003" in the terminal device list T. Furthermore, the identification unit 150 may include or exclude terminal devices 20 whose wearing scores are lower than a predetermined standard as targets of the second terminal identifier in the terminal device list T. In the above example, for example, if the wearing score of the terminal device "UE002" is also lower than a predetermined standard, in addition to the high-risk area "HA001," a high-risk area "HA002" is formed centered around the position of the terminal device "UE002." In such a case, the identification unit 150 may include the terminal device "UE002" in the second device identifier for the high-risk area "HA001," or may exclude it. In the example shown in FIG. 29, as can be seen from the fact that the second device identifier for the high-risk area "HA001" includes "UE002," which is the first device identifier for the high-risk area "HA002," the second device identifier includes the terminal device 20 whose wearing score is lower than the predetermined standard. In this way, when the identification unit 150 includes the terminal device "UE002" in the second device identifier, the warning information described below is also notified to "UE002," which has a low wearing score.

[0177] Users with low mask wearing scores are at high risk of infecting other users with a virus, and at the same time, are at high risk of themselves becoming infected with a virus. Therefore, from the perspective of preventing the spread of virus infection, particularly in the short term, it is desirable to assign the second terminal identifier to users (terminal devices 20) with low mask wearing scores and users whose mask wearing scores are unknown (terminal devices 20 that do not transmit mask information) so that they are notified of the alert information. That is, it is desirable to assign the second terminal identifier to as many terminal devices 20 as possible. Alternatively, terminal devices 20 with low mask wearing scores may be excluded from the second terminal identifier, so that only users with high mask wearing scores can receive the alert information. This is expected to encourage users to wear masks thoroughly in order to receive the alert information. Furthermore, terminal devices 20 that do not transmit mask information (mask wearing status information) may be excluded from the second terminal identifier, so that only users who transmit mask information can receive the alert information. Furthermore, only terminal devices 20 that frequently transmit mask information (at a predetermined frequency or more) may be assigned the second terminal identifier. This can be expected to encourage users to proactively send mask information in order to receive the warning information. In other words, the warning information can serve as an incentive for users to wear masks or to provide mask information. Furthermore, improving users' mask-wearing practices can be expected to help prevent the spread of virus infection in the medium to long term. Therefore, from the perspective of encouraging users to wear masks thoroughly and increasing the mask-wearing rate, it is desirable to exclude users (terminal devices 20) with low mask-wearing scores and users who do not provide mask information from the second terminal identifier so that they are not notified of the warning information. In other words, the identification unit 150 can set (determine) the terminal devices 20 that are targets of the second terminal identifier depending on the current virus infection situation and the desired effect to be prioritized by the infection prevention support system 1.

[0178] Returning to Fig. 27, the explanation will be continued. After executing S250, the identification unit 150 advances the processing to S260. In S260, the identification unit 150 generates alert information and transmits the alert information via the communication unit 110 to the terminal device 20 with the second terminal identifier recorded in the terminal device list T. That is, the identification unit 150 transmits the alert information to the second terminal device 20 located in the high-risk area HA. ​​The alert information includes information indicating that the terminal device 20 (second terminal device 20) is located in a place with a high risk of infection. Thereafter, the identification unit 150 ends the processing.

[0179] When the terminal device 20 receives alert information from the management device 100, the terminal device 20 displays the alert information on the display unit 22. FIG. 30 is a diagram illustrating an example of a display on the terminal device 20 according to the seventh embodiment. This diagram illustrates an example of the configuration of the alert information displayed on the display unit 22. As illustrated in the example shown in this diagram, the alert information includes information indicating that the user of the terminal device 20 is in a location with a high risk of infection, such as "There is a person not wearing a mask near you." Furthermore, the alert information may also include information urging the user to move, such as "Please move quickly to prevent infection." When the terminal device 20 receives alert information, the audio output unit 24 may output the alert information as audio. The alert information may also include information regarding the direction and distance of users who are unlikely to be wearing masks. For example, the terminal device 20 may display or output audio information such as "There is a person not wearing a mask 3 meters to the right of your direction of travel" or "There is a person not wearing a mask 2 meters north of your location." Furthermore, the terminal device 20 (second terminal device 20) that outputs the alert information may change the output format of the alert information depending on the distance from the user (first terminal device 20) who is not wearing a mask. For example, when the distance from the second terminal device 20 to the first terminal device 20 is relatively long (far), the second terminal device 20 displays the alert information along with an alert sound such as "beep." In other words, when the distance between the two is far, the second terminal device 20 does not output audio, and therefore only displays the alert information on the screen. Furthermore, when the distance between the second terminal device 20 and the first terminal device 20 is medium, the second terminal device 20 displays the alert information and also outputs the alert information as audio using voice synthesis or the like. In other words, when the distance between the two is medium, the second terminal device 20 uses both audio output and screen display, as the need for an alert is high. Furthermore, the second terminal device 20 displays alert information and generates vibrations when the distance to the first terminal device 20 is relatively short (close). That is, when the distance between the two is short, the second terminal device 20 highly needs to alert the user, but at the same time, there is a possibility that the alert information may be heard by a user not wearing a mask, so the second terminal device 20 outputs vibrations instead of audio.By changing the output format according to the distance between the two devices in this way, it is possible to reliably communicate the alert information to the user, and to prevent trouble between users by not unnecessarily notifying users who are not wearing masks that the alert information has been output. Furthermore, the display format (such as character size, character color, and character decoration) of the alert information displayed on the display unit 22 may be changed according to the distance between the first terminal device 20 and the second terminal device 20. For example, the identification unit 150 may generate alert information with larger characters, a more conspicuous color, or a bold font as the distance between the two devices decreases. Furthermore, the control unit 28 of the terminal device 20 may determine the display format of the alert information according to the distance between the two devices.

[0180] Furthermore, the identification unit 150 or the control unit 28 of the terminal device 20 may change at least one of the display form and output form of the alert information depending on the mask wearing status information. For example, the identification unit 150 may generate alert information in which the characters are larger, the characters are in a more conspicuous color, or the characters are in a bolder color, the lower the mask wearing score of the first terminal device 20. In other words, the identification unit 150 may generate alert information with a higher degree of emphasis to more strongly attract the attention of the user of the second terminal device 20, the lower the mask wearing score of the first terminal device 20. Furthermore, the identification unit 150 may generate alert information in which the number of notification means for the alert information increases, the lower the mask wearing score of the first terminal device 20. For example, the identification unit 150 may generate "display alert information" to be displayed on the display unit 22 of the terminal device 20 when the mask wearing score of the first terminal device 20 is equal to or greater than 40 and less than 60. When the wearing score of the first terminal device 20 is equal to or greater than 20 and less than 40, the identification unit 150 may generate, in addition to the display alert information, “vibration alert information” that causes the terminal device 20 to output a vibration. When the wearing score of the first terminal device 20 is less than 20, the identification unit 150 may generate, in addition to the display alert information and the vibration alert information, “audio alert information” that causes the terminal device 20 to output a sound. Furthermore, when the wearing score of the second terminal device 20 can be acquired, the identification unit 150 may change at least one of the display form and the output form of the alert information according to the wearing score of the second terminal device 20. For example, the lower the wearing score of the terminal device 20, the more emphasized the display form may be, or the more notification means may be used. Furthermore, the display form and the output form of the alert information may be changed using both the wearing score of the first terminal device 20 and the wearing score of the second terminal device 20. Furthermore, the identification unit 150 may change at least one of the display form and the output form of the alert information using at least one of the wearing score of the first terminal device 20 and the wearing score of the second terminal device 20, and both the distance between the first terminal device 20 and the second terminal device 20. For example, the lower the wearing score and the closer the distance between the first terminal device 20 and the second terminal device 20, the more emphasized the display form may be, or the more notification means may be used.Furthermore, the process of changing the display form and the output form may be performed by the control unit 28 of the terminal device 20. For example, when transmitting alert information to the second terminal device 20 via the communication unit 110, the identification unit 150 transmits the alert information together with the wearing score of the first terminal device 20 and the wearing score of the second terminal device 20. The control unit 28 of the second terminal device 20 that receives the alert information may change at least one of the display form and the output form of the alert information based on the wearing score of at least one of the first terminal device 20 and the second terminal device 20.

[0181] According to the seventh embodiment, by identifying the location information of users who are unlikely to be wearing masks, it is possible to present warning information useful for reducing the risk of infection to users of nearby terminal devices 20. This makes it possible to reduce the possibility of virus infection for users of individual terminal devices 20. Since information obtained when the user of the terminal device 20 performs facial recognition is used to identify users who are unlikely to be wearing masks, a complex and expensive system is not required. This makes it possible to easily obtain information on the mask wearing status of people in unspecified locations, and therefore makes it possible to easily generate and provide warning information in unspecified locations.

[0182] Furthermore, since the user only needs to perform the normal operations for facial recognition and no special operations are required, the burden on the user is extremely low. Furthermore, since users generally perform facial recognition frequently to unlock the UI, information on the user's mask wearing status can be obtained frequently and in a natural way.

[0183] Note that when the management device 100 excludes users who are not wearing masks from the notification targets, users who are wearing masks are given the benefit of warning information. Therefore, it is possible to provide users with an incentive to wear masks. Also, when the management device 100 excludes users who do not provide mask information from the notification targets, users who provide mask information are given the benefit of warning information. Therefore, it is possible to provide users with an incentive to provide mask information.

[0184] <First Modification of Seventh Embodiment> In the seventh embodiment described above, the identification unit 150 of the control unit 130 of the management device 100 may set the range and shape of the high risk area HA, for example, the distance R, depending on the surrounding environment. However, instead of or in addition to this, the identification unit 150 may vary the range of the high risk area HA formed from the position of the terminal device 20 of a user not wearing a mask (the user of the first terminal device 20) depending on mask wearing status information (for example, a wearing score) of the user not wearing a mask.

[0185] Specifically, in S210 of FIG. 27 of the seventh embodiment, the identification unit 150 may set the predetermined value S of the wearing score to "60," and when creating the high-risk area map in S230, may set the value of the distance R of the high-risk area HA according to the wearing score. For example, if an incomplete state (Level 2) in which a user covers their mouth with a mask but not their nose is assigned a wearing score of "50," the identification unit 150 sets the distance R of the high-risk area HA formed from the position of a user (first terminal device 20) with a wearing score of "50" to "1 meter." Furthermore, if a substantially unworn state (Level 3) in which a mask is worn over the ears but under the chin and does not cover the mouth and nose is assigned a wearing score of "30," the identification unit 150 sets the distance R of the high-risk area formed from the position of a user with a wearing score of "30" to "2 meters." Furthermore, when the wearing score for a formally not wearing (not carrying) state (level 4) in which no mask is detected at all from the face image is set to "0," the identification unit 150 sets the distance R of the high-risk area formed from the user's position in the case of a wearing score of "0" to "3 meters." The identification unit 150 may then record the set distance R for each area identifier in the terminal device list T.

[0186] In this way, the identification unit 150 sets the distance R based on the user's mask wearing level and identifies the second terminal device 20 located within the distance R from the location of the first terminal device 20. Note that setting the high risk area as a circular area with a radius R is merely an example, and the shape of the high risk area HA may be arbitrary. The identification unit 150 may set the range of the high risk area HA based on the user's mask wearing level. That is, the lower the user's mask wearing level, the wider the range of the high risk area HA may be set. Furthermore, the identification unit 150 may set the high risk area HA based on the user's mask wearing level and the surrounding environment. For example, the range (shape and size) of the high risk area HA may be set based on the user's mask wearing level and weather conditions. The high risk area HA may also be set based on the user's mask wearing level and population density. That is, the identification unit 150 may set a predetermined range based on the location of the first terminal device 20 as the high risk area HA based on at least one of weather conditions, population density, and user's mask wearing status information. According to this modification, it is possible to set high risk areas HA individually depending on the level of mask wearing by the user, and the management device 100 can notify accurate warning information.

[0187] <Second Modification of Seventh Embodiment> The identification unit 150 may change the information provision process (infection risk reduction process) depending on the measures taken by the mask-less user to prevent viral infection. The measures to prevent viral infection refer to measures other than wearing a mask, and may be, for example, at least one of testing or vaccination. The testing may be, for example, a PCR (Polymerase Chain Reaction) test, an antigen test, etc.

[0188] For example, a user of the terminal device 20 transmits countermeasure information indicating that countermeasures against virus infection have been implemented to the management device 100 in advance. The countermeasure information may include the type of countermeasure and the countermeasure implementation date. The type of countermeasure is either "test" or "vaccination." For example, if the type of countermeasure is test, the countermeasure implementation date is the test date. For example, if the type of countermeasure is "vaccination," the countermeasure implementation date is the date on which vaccination is completed or the first day of the period during which the vaccine is valid. If the type of countermeasure is "test," the test results are included in the countermeasure information. If the type of countermeasure is "vaccination," the validity period of the vaccine is included in the countermeasure information. The management device 100 stores a countermeasure table (not shown) in the storage unit 170 that associates terminal identifiers with countermeasure information. When countermeasure information is received from the terminal device 20, the management device 100 records the terminal identifier and the countermeasure information in the countermeasure table. When executing the processing of the flowchart shown in FIG. 27 of the seventh embodiment, the control unit 130 refers to the countermeasure table and changes the processing depending on the countermeasure information. Specifically, at least one of the following processes is performed.

[0189] (Processing using countermeasure information 1) In S210, when extracting record Re, the identifying unit 150 obtains the latest countermeasure information corresponding to the terminal identifier in the mask information table 180 from the countermeasure table, and changes the value of the threshold S depending on whether the countermeasure information is valid. When the countermeasure type is "test," the countermeasure information is valid if the test result is "negative" and a predetermined number of days (predetermined time) has not elapsed from the test date to the processing time. When the countermeasure type is "vaccination," the countermeasure information is valid if the processing time is within the validity period of the vaccine. When the countermeasure information is valid, the identifying unit 150 sets the threshold to a smaller (lower) value than usual (when the countermeasure information is invalid or does not exist). This makes it less likely that a user with valid countermeasure information will be extracted as record Re even if their mask wearing score is low. Furthermore, when the countermeasure information is valid, the threshold S may be set to "0." This prevents record Re from being extracted even if a user with valid countermeasure information does not wear a mask at all.

[0190] (Processing using countermeasure information 2) In S230, when creating the high-risk area map, the identifying unit 150 obtains the latest countermeasure information corresponding to the terminal identifier included in the location information list P from the countermeasure table, and changes the range of the high-risk area HA depending on whether the countermeasure information is valid. For example, if the countermeasure information is valid, the value of the distance R defining the high-risk area HA is set smaller than usual (when the countermeasure information is invalid or does not exist). This makes it possible to reduce the number of second terminal devices 20 included in the high-risk area HA. ​​Furthermore, if the countermeasure information is valid, the distance R may be set to "0." This ensures that no second terminal devices 20 are included in the high-risk area HA even if a user for whom the countermeasure information is valid is not wearing a mask at all. Furthermore, the identifying unit 150 may record the corresponding distance R for each area identifier in the terminal device list T. Furthermore, in S250, the identifying unit 150 refers to the location information of the record Rc, and records the terminal identifier of the record whose location information falls within the high-risk area HA of the high-risk area map as the second terminal identifier in the terminal device list T.

[0191] In this way, the identification unit 150 individually sets the range of the high-risk area HA based on the virus infection countermeasures implemented by the user, and identifies the second terminal device 20 located within the range of the high-risk area HA. ​​This enables the management device 100 to notify more appropriate warning information.

[0192] <Third Modification of Seventh Embodiment> In the above-described seventh embodiment, in S250 of FIG. 27, if the location information of the terminal device 20 is within a high-risk area HA in the high-risk area map, the terminal identifier is recorded in the second terminal identifier of the terminal device list T. Here, if there are multiple users not wearing masks in the vicinity of the user of the terminal device 20 and the location information of the terminal device 20 is within multiple high-risk areas HA, the same terminal identifier is recorded multiple times in the second terminal identifier of the terminal device list T. In other words, the user of the terminal device 20 that is recorded multiple times in the second terminal identifier of the terminal device list T can be said to have multiple users not wearing masks in the vicinity and to be in a state where the risk of virus infection is very high. Note that being recorded multiple times in the second terminal identifier of the terminal device list T refers to the same terminal identifier being recorded in the "second terminal identifier" field of multiple records in the terminal device list T that have different area identifiers.

[0193] Therefore, in this modification, the management device 100 changes the alert level of the alert information to be transmitted to the terminal device 20 in stages according to the number of times the second terminal identifier is recorded in the terminal device list T. Hereinafter, the alert level may be simply referred to as the level.

[0194] 27, the identification unit 150 of the control unit 130 of the management device 100 sets a level of alert information for each terminal identifier recorded in the second terminal identifier field of the terminal device list T according to the number of overlaps, that is, the number of records in which the same terminal identifier is recorded. When transmitting alert information to a terminal device 20 via the communication unit 110, the identification unit 150 notifies the terminal device 20 of the set level.

[0195] For example, for a terminal device 20 whose terminal identifier duplication number is "3", the identification unit 150 transmits a level of "3" via the communication unit 110. Furthermore, for a terminal device 20 whose terminal identifier duplication number is "2", the identification unit 150 transmits a level of "2" via the communication unit 110. Furthermore, for a terminal device 20 whose terminal identifier duplication number is "1", the identification unit 150 transmits a level of "1" via the communication unit 110. In this way, the same level as the duplication number may be used, or the duplication number and the level may be different. For example, if the duplication number is in the range of "2" to "4", the level may be set to "2". Note that the identification unit 150 may include level information in the alert information and transmit it to the terminal device 20 via the communication unit 110.

[0196] The terminal device 20 changes the alert information notified to the user depending on the alert level. For example, the message of the alert information shown in FIG. 30 may be changed depending on the received alert level. For example, a message such as "We recommend you move to prevent infection" may be displayed when the level is "1," and a message such as "Please move immediately to prevent infection!" may be displayed when the level is "2." The display format of the alert information may also be changed depending on the alert level. For example, the higher the level, the larger the font size, the more noticeable the display color such as red, or the faster the blinking cycle on the screen. In other words, the higher the level, the stronger the emphasis may be to attract the user's attention. The output format of the alert information may also be changed depending on the alert level. For example, when the alert level is high, in addition to displaying a message on the display unit 22, the alert information may be output as audio from the audio output unit 24, or the terminal device 20 may be vibrated using a vibration function.

[0197] In the above description, the identification unit 150 transmits information of a set level when transmitting alert information to the second terminal device 20 via the communication unit 110. However, instead of this, the identification unit 150 may generate alert information according to the set level and transmit the generated alert information to the second terminal device 20 via the communication unit 110. For example, for a terminal device 20 whose duplication number of terminal identifiers is "3", the identification unit 150 transmits alert information according to a level "3" via the communication unit 110. Furthermore, for a terminal device 20 whose duplication number of terminal identifiers is "2", the identification unit 150 transmits alert information according to a level "2" via the communication unit 110. Furthermore, for a terminal device 20 whose duplication number of terminal identifiers is "1", the identification unit 150 transmits alert information according to a level "1" via the communication unit 110. That is, the identification unit 150 may change the message of the warning information or change the display format of the warning information according to the warning level, similar to the above-described processing in the terminal device 20. In this case, the terminal device 20 may output the received warning information as it is without changing it.

[0198] In this way, the identification unit 150 of the management device 100 transmits warning information with different warning levels to the second terminal device 20 via the communication unit 110, depending on the number of high-risk areas HA in which the second terminal device 20 is located. This makes it possible to present appropriate warning information to each user depending on the level of virus infection risk.

[0199] The identification unit 150 may set the level depending on the distance between a first terminal device 20 (first terminal identifier) ​​included in the terminal device list T and a second terminal device 20 (second terminal identifier) ​​that outputs the alert information. For example, the identification unit 150 may set the level to "3" if the distance between them is less than 1 meter, set the level to "2" if the distance is 1 meter or more but less than 2 meters, and set the level to "1" if the distance is 2 meters or more but less than 3 meters. In other words, the identification unit 150 of the management device 100 may transmit alert information with different alert levels to the second terminal device 20 via the communication unit 110 depending on the distance between the first terminal device 20 and the second terminal device 20. In this case, it is also possible to present appropriate alert information for each user depending on the level of virus infection risk.

[0200] <Embodiment 8> Next, an eighth embodiment will be described. The eighth embodiment is a modification of the seventh embodiment described above. In the seventh embodiment, the management device 100 notifies a user who is near a user who is not wearing a mask of warning information based on the most recent mask information and user position information of the user of the terminal device 20. In contrast, in the eighth embodiment, when it is predicted from the user's movement history that the user will approach a user who is not wearing a mask, warning information is transmitted to the terminal device 20 of that user.

[0201] Here, the information provision process of the management device 100 according to the eighth embodiment will be described in detail. The identification unit 150 of the control unit 130 of the management device 100 executes the information provision process at a predetermined timing, for example, every 10 seconds. The information provision process is a process in which, when a target user approaches a user not wearing a mask, the target user is sent alert information including information that there is a high possibility of virus infection at the predicted moving point.

[0202] FIG. 31 is a flowchart showing an example of an information provision processing procedure according to the eighth embodiment. The processing shown in S300 to S330 in this figure is the same as the processing shown in S200 to S230 in FIG. 27. In S340, the identification unit 150 refers to the user position information table 190 in the storage unit 170, and selects an arbitrary unprocessed terminal device (terminal identifier) ​​from the terminal devices (terminal identifiers) in the table as the terminal device X. The terminal device X may also be referred to as the "terminal device 20 to be processed." Next, the identification unit 150 predicts the location information to which the terminal device X will move from the history of the location information in the user position information table 190. Specifically, the identification unit 150 estimates the moving direction and moving speed of the terminal device X from the difference in the history of the location information of the terminal device X, and predicts the location (moving point) to which the terminal device X will move after a predetermined time. Thereafter, the identification unit 150 proceeds to S350. In S350, the identification unit 150 determines whether the location information to which the terminal device X is predicted to move falls within the high-risk area HA. The processes of S340 and S350 together are sometimes called "intrusion prediction process into high-risk area HA" or "intrusion prediction process."

[0203] FIG. 32 is a diagram illustrating an example of a process for predicting intrusion into a high-risk area HA according to the eighth embodiment. As illustrated in FIG. 32, the terminal device X, which was located according to the position information (N303, E303), is located 10 seconds later according to the position information (N302, E302) closer to the high-risk area HA. ​​After another 10 seconds, the terminal device X is located according to the position information (N301, E301) closer to the high-risk area HA than the position information (N302, E302). That is, this diagram illustrates a state in which the terminal device X is approaching the high-risk area HA. ​​Here, the identification unit 150 predicts the position information of the terminal device X after a predetermined time has elapsed based on the difference in the history of the position information of the terminal device X. Note that multiple times may be set as this predetermined time. For example, the predetermined time may be "5 seconds," "10 seconds," "15 seconds," or "20 seconds," and the position information after each predetermined time has elapsed may be predicted. Alternatively, the predetermined time may be set to "30 seconds," and the location information may be predicted every "second" until the predetermined time has elapsed. Then, the identification unit 150 determines whether or not the terminal device X will enter the high-risk area HA within the predetermined time based on the predicted location information. As shown in FIG. 32, if the terminal device X is predicted to enter the high-risk area HA (S350: YES), the identification unit 150 proceeds to S360. On the other hand, if the terminal device X is predicted not to enter the high-risk area HA (S350: NO), the identification unit 150 proceeds to S370.

[0204] Although the high risk area HA is treated as stationary in Figure 32, the identification unit 150 may treat the high risk area HA as dynamic (moving) and perform intrusion prediction processing into the high risk area HA. FIG. 33 is a diagram illustrating an example of an intrusion prediction process when the high risk area HA is treated as dynamic. As shown in FIG. 33, the identification unit 150 acquires the history of location information of the first terminal device 20 that formed the high risk area HA from the user location information table 190. Then, the identification unit 150 predicts the location of the first terminal device 20 after a predetermined time has elapsed based on the history of the location information of the first terminal device 20, and determines whether or not the terminal device X will enter the predicted high risk area HA, i.e., the future high risk area HA, within a predetermined time. Note that this diagram illustrates how the terminal device X is predicted to enter the high risk area HA within a predetermined time from the current time. In other words, the identification unit 150 may predict the future locations of both the high risk area HA and the terminal device X (its user), and predict the future risk of the terminal device X based on the predicted location information.

[0205] 31, the description will continue. In S360, the identification unit 150 records the terminal identifier X of the terminal device X in the second terminal identifier of the terminal device list T. After that, the identification unit 150 advances the process to S370.

[0206] In S370, the identification unit 150 determines whether or not the location information of all terminal devices 20 in the user location information table 190 of the storage unit 170 has been predicted. In other words, it determines whether or not there are any unprocessed terminal devices 20. If the location information of all terminal devices 20 has been predicted (S370: YES), the identification unit 150 proceeds to S380. If the location information of all terminal devices has not been predicted (S370: NO), the identification unit 150 returns the process to S340 and repeats the processes from S340 onwards.

[0207] In S380, the identification unit 150 transmits the alert information to the terminal device 20 recorded in the second terminal identifier of the terminal device list T via the communication unit 110. After that, the identification unit 150 ends the process.

[0208] In the above description, the intrusion prediction process into the high risk area HA is based on at least the movement history of the terminal device X, but it may also be performed based on the movement history of the first terminal device 20 instead of the terminal device X. In this case, the terminal device X is treated as being stationary, and only the high risk area HA is treated as being moving.

[0209] When the terminal device 20 receives the alert information from the management device 100, the terminal device 20 displays the alert information on the display unit 22. FIG. 34 is an example of a display on the terminal device 20 according to the eighth embodiment, illustrating an example of the configuration of alert information displayed on the display unit 22. When the terminal device 20 receives the alert information, the audio output unit 24 may output the alert information by voice. The alert information may include information regarding the distance to the user not wearing a mask and the time remaining until the user enters the high-risk area HA. ​​For example, the terminal device 20 may display or output voice information such as "There is a person not wearing a mask 20 meters ahead of you," "If you continue on this path, you will encounter a person not wearing a mask in 15 seconds," or "In 10 seconds, you will cross a person not wearing a mask coming from diagonally to the right."

[0210] In this way, the identification unit 150 of the control unit 130 of the management device 100 predicts whether the terminal device X will be located in the high-risk area HA within a predetermined time based on the movement history of at least one of the first terminal device 20 and the terminal device X. If the identification unit 150 predicts that the terminal device X will enter the high-risk area HA, it identifies the terminal device X as the second terminal device 20. The identification unit 150 then notifies the second terminal device 20 of warning information via the communication unit 110. This makes it possible to avoid a situation in which the user of the terminal device 20 approaches a user not wearing a mask in advance. Therefore, it is possible to reduce the risk of the user of the terminal device 20 being infected with a virus.

[0211] <Embodiment 9> Next, a ninth embodiment will be described. The ninth embodiment is a modification of the seventh embodiment. In the seventh embodiment described above, the management device 100 provided the user with information indicating that the current location is high risk, as shown in FIG. 30. In the eighth embodiment described above, the management device 100 provided the user with information prompting the user to change the current direction of travel, as shown in FIG. 34. However, the information provided to the user is not limited to this. In the ninth embodiment, the management device 100 provides the user with information on a safe route with a low risk of infection. Specifically, the terminal device 20 and the management device 100 may perform the following processes.

[0212] First, the user operates the terminal device 20 to specify a departure point and a destination. For example, the user may specify any point on a map, or may input the name of a station or facility. The current location of the terminal device 20 may also be used as the departure point. Alternatively, the terminal device 20 or the management device 100 may analyze the user's behavioral patterns from the terminal device 20's daily location information, recognize the user's home, workplace, friend's house, frequented store, etc., and infer the destination based on the user's current location. The terminal device 20 (the terminal device 20 requesting route guidance information) transmits information about the departure point and destination to the management device 100. The management device 100 refers to a map database or the like to identify the location information (latitude, longitude) of the departure point and destination specified by the user, and stores the information in the storage unit 170. The storage unit 170 stores the destination (latitude, longitude) of the terminal device 20 for each terminal identifier.

[0213] The management device 100 executes a process similar to that of the fourth embodiment to determine a route from the departure point to the destination with a low risk of infection. Specifically, after executing S330 in the flowchart of FIG. 31, it executes S390 (not shown) instead of S340. In S390, the identification unit 150 executes a similar process using the high-risk area map created in S330 instead of the mask wearing rate map data described in the fourth embodiment to create route guidance information. Specifically, it generates multiple (N) route candidates from the departure point to the destination, calculates an index S for each route candidate using equation (7), and selects the route with the smallest index S as the optimal route.

number

[0214] In equation (7), S[i] (i = 1 to N) is the index S of the i-th route, and D[i] is the distance of the i-th route. Furthermore, H[i, x] is a function whose value changes depending on whether or not point x on the i-th route is included in the high-risk area HA. ​​For example, if point x on the i-th route is included in the high-risk area HA, H[i, x] is a positive constant (e.g., "1"), and if point x on the i-th route is not included in the high-risk area HA, H[i, x] is "0." Alternatively, a function H[i, x] may be used in which, if point x on the i-th route is included in the high-risk area HA, the lower the mask wearing score of the first terminal device 20, the larger the positive value becomes, and if point x on the i-th route is not included in the high-risk area HA, the function H[i, x] is "0." In other words, the better the mask wearing status information at point x on the i-th route, the smaller the value of the function H[i, x] may be set. Furthermore, α and β are predetermined positive coefficients (weighting coefficients). The second term of Equation (7) indicates that the value of the function H[i,x] at point x of the i-th route is integrated (line integral) along the route. That is, according to Equation (7), the shorter the distance of each route candidate and the better the mask wearing status information along the route, the smaller (lower) the value of the index S. Therefore, the identification unit 150 selects the route with the smallest index S as the optimal route. That is, it preferentially selects a route that is as short as possible and that is not included in the high-risk area HA. ​​Furthermore, by changing the values ​​(balance) of α and β, it is possible to arbitrarily adjust the balance between the degree of emphasis placed on distance and the degree of emphasis placed on the mask wearing score. In other words, it is possible to adjust the nature (characteristics) of the route. An operation screen for specifying α and β may be displayed on the display unit 22 of the terminal device 20, allowing the user of the terminal device 20 to specify α and β. Furthermore, in Equation (7), the required time (travel time) of the route may be used instead of the distance D[i] of the route. That is, the shorter the time required for the route and the better the mask wearing status information along the route, the smaller the value of the index S. Next, the identification unit 150 proceeds from S390 to S391 (not shown). In S391, the identification unit 150 transmits route guidance information indicating the route created in S390 to the terminal device 20 that requested the route information via the communication unit 110.

[0215] In this way, the identification unit 150 of the control unit 130 of the management device 100 generates route guidance information based on the departure point information and destination information acquired from the terminal device 20 and the location information of the high-risk area HA. ​​Then, the identification unit 150 transmits the route guidance information to the terminal device 20 via the communication unit 110. After executing S391, the identification unit 150 ends the processing.

[0216] The terminal device 20 that has received the route guidance information displays a route guidance screen (navigation screen) shown in FIG. 35 on the display unit. FIG. 35 is a diagram showing an example of a display on the terminal device 20 according to the ninth embodiment, illustrating an example of the configuration of the route guidance screen. In this diagram, the optimal route from the departure point to the destination with a low risk of virus infection is indicated by a dotted line. By viewing such a screen, a user can easily understand a route that has a low risk of infection and efficiently reaches the destination. This reduces the risk of infection for each user. Note that the process of deriving a route by preferentially selecting points that are not included in the high-risk area HA described above may be performed by the control unit 28 of the terminal device 20 instead of the identification unit 150 of the control unit 130 of the management device 100.

[0217] <Embodiment 10> Next, a tenth embodiment will be described. The tenth embodiment is a modification of the seventh embodiment described above. In the seventh embodiment described above, the management device 100 notifies the terminal device 20 of a user who is near a user who is not wearing a mask of warning information based on the most recent mask information and user position information of the user of the terminal device 20. On the other hand, in the tenth embodiment, when another user is near a user who is not wearing a mask, mask wearing enforcement information encouraging the user to wear a mask is transmitted to the terminal device 20 of the user who is not wearing a mask. Note that in the tenth embodiment, all terminal devices 20 are assumed to transmit user position information to the management device 100. Furthermore, it is assumed that at least some of the terminal devices 20 are assumed to transmit mask information to the management device 100.

[0218] Next, the information provision process of the present embodiment 10 will be described in detail. The identification unit 150 of the control unit 130 of the management device 100 executes the information provision process at a predetermined timing, for example, every minute. The information provision process of the present embodiment 10 is a process of encouraging a user not wearing a mask to wear a mask when another user approaches the user not wearing a mask. The information provision process of the present embodiment 10 is also called a "mask wearing enforcement process."

[0219] 36 is a flowchart showing an example of an information providing process procedure according to embodiment 10. First, in S400, the identification unit 150 of the control unit 130 of the management device 100 acquires the current time CT from the clock unit 120. Thereafter, the identification unit 150 advances the process to S410.

[0220] In S410, the identification unit 150 refers to the user position information table 190 in the storage unit 170 and extracts the latest record for each terminal identifier as record Rc. That is, record Rc is the most recent position information for all users. Note that the identification unit 150 may extract, as record Rc, the latest record for each terminal identifier, a record whose reception time is within a predetermined period DT2 (e.g., 10 seconds) compared to the current time CT. Thereafter, the identification unit 150 proceeds to S420.

[0221] In S420, the identification unit 150 refers to the mask information table 180 in the storage unit 170 and extracts, as record Re, a record that satisfies a predetermined condition from the mask information recorded in the mask information table 180. For example, the identification unit 150 may extract, as record Re, a record whose latest wearing score for each terminal identifier is equal to or less than a predetermined value S. That is, record Re is information about a user not wearing a mask. Alternatively, the identification unit 150 may extract, as record Re, a record whose reception time is within a predetermined period DT1 (e.g., 1 minute) compared to the current time CT and whose wearing score is equal to or less than a predetermined value S. The predetermined value S may be, for example, "60," but is not limited to this value. Thereafter, the identification unit 150 proceeds to S430.

[0222] In S430, the identification unit 150 creates a user area map based on the record Rc extracted in S410. The user area map is information indicating a user area UA, which is a predetermined range (area) based on the location of each user (each terminal device 20). FIG. 37 is a diagram showing an example of the configuration of a user area map according to the tenth embodiment. In the user area map, a predetermined distance R, for example, a radius of 2 meters, from the location information recorded in the record Rc, i.e., the location of all users, is set as the user area UA. Note that while FIG. 37 shows the user area UA as a circular area, it may also be configured as a rectangular area centered on the location information of the user. In other words, the user area UA may be an area of ​​any shape and size based on the user's location. Furthermore, the shape and size of the user area UA may be determined depending on surrounding conditions such as weather conditions and population density (terminal density). Note that FIG. 37 shows users A and B who are not wearing masks, but this is for the purpose of explaining the processing of S440 and S450; it is not necessary to identify users not wearing masks in S430. The description will continue by returning to Fig. 36. After executing S430, the identification unit 150 advances the process to S440.

[0223] In S440, the identification unit 150 creates a terminal device list T based on the record Re extracted in S420 and the user area map created in S430. Specifically, from the record Re, a record (enforcement target record) whose location information of record Re is included in the user area UA of the user area map is identified, and the identification unit 150 records the terminal identifier of the enforcement target record (enforcement target terminal identifier) ​​in the terminal device list T. However, if the terminal identifier of record Re differs from the terminal identifier of the terminal device 20 that forms the user area UA, the identification unit 150 records it in the terminal device list T. For example, the data format shown in FIG. 29 can be used for the terminal device list T. In this case, the enforcement target terminal identifier is recorded as a first terminal identifier in the terminal device list T, and other terminal identifiers (terminal identifiers that form other user areas UA) that exist near the enforcement target terminal identifier (within a predetermined distance R) are recorded as second terminal identifiers in the terminal device list T. In addition, the wearing score and distance R of the enforcement target terminal identifier may be recorded in the terminal device list T. Furthermore, instead of the distance R, the distance between the terminal device 20 with the enforcing terminal identifier and the other terminal devices 20 may be recorded. However, in the present embodiment 10, it is also possible to omit recording the wearing score, the distance R, and the second terminal identifier in the terminal device list T. That is, the terminal device list T records at least the terminal identifiers (first terminal identifiers) of users who are unlikely to be wearing masks while being in close proximity to other users. Thereafter, the identification unit 150 proceeds to S450.

[0224] In S450, the identification unit 150 transmits mask wearing enforcement information to the terminal device 20 recorded in the first terminal identifier of the terminal device list T. After that, the identification unit 150 ends the process.

[0225] In the example of the user area map shown in FIG. 37, users not wearing masks extracted as record Re are shown as user A and user B. Other users are users wearing masks (users whose wearing score is greater than a predetermined value S) or users whose mask wearing status is unknown (users who do not have a wearing score). In the user area map shown in FIG. 37, user A not wearing a mask is located within the user area UA of another user, that is, is in close proximity to the other user, so in S440, the terminal identifier of the terminal device 20 of user A not wearing a mask is recorded as the first terminal identifier in the terminal device list T. On the other hand, user B not wearing a mask is not located within the user area UA of another user, that is, is not in close proximity to the other user, so in S440, the terminal identifier of the terminal device 20 of user B not wearing a mask is not recorded as the first terminal identifier in the terminal device list T. Therefore, in S450, the terminal device 20 of user A who is not wearing a mask is the target for receiving the mask enforcement information, but the terminal device 20 of user B who is not wearing a mask is not the target for receiving the mask enforcement information. Through this processing, the management device 100 can appropriately transmit mask enforcement information to users for whom it is highly necessary and effective from the perspective of preventing the spread of infection. On the other hand, the management device 100 does not transmit mask enforcement information to users for whom it is not highly necessary, thereby preventing users from being overly stimulated, that is, from being unnecessarily upset. Furthermore, since the management device 100 selects users who are highly necessary and transmits mask enforcement information to them, compared to sending mask enforcement information uniformly to all users, users are more likely to agree with the instructions and wear masks as instructed, which increases the likelihood that users will follow the instructions.

[0226] When the terminal device 20 receives mask-wearing enforcement information from the management device 100, the terminal device 20 displays the mask-wearing enforcement information on the display unit 22. FIG. 38 is a diagram showing an example of a display on the terminal device 20 according to the tenth embodiment, and shows an example of the configuration of the mask-wearing enforcement information. For example, the terminal device 20 may display or output audibly information such as, "There is someone near you. Please wear a mask properly to prevent infection."

[0227] In anticipation of the possibility that a mask-unattenent user may not have a mask, a table recording location information of stores such as drugstores and convenience stores that sell masks may be stored in the storage unit 170 of the management device 100. When transmitting mask-wearing enforcement information, the identification unit 150 of the control unit 130 of the management device 100 may also transmit information about stores within a predetermined distance from the location information of the mask-unattenent user, such as the nearest store.

[0228] In this case, the terminal device 20 may notify the user of the mask-wearing recommendation and may display information about stores where masks can be purchased, such as map information, or may provide navigation to stores where masks can be purchased. The control unit 130 of the management device 100 may also include discount coupons or points that can be used when purchasing a mask and transmit this information to the terminal device 20 of the user who is not wearing a mask via the communication unit 110. The control unit 130 of the management device 100 may also award bonus points higher than usual to users who purchase a mask after presenting the mask-wearing recommendation to a store clerk at a store. By performing such processing, it is possible to alleviate users' resentment about receiving the "mask-wearing recommendation" warning, increase users' understanding, and encourage them to wear masks.

[0229] As described above, according to the tenth embodiment, the identification unit 150 of the control unit 130 of the management device 100 determines whether the distance between the first terminal device 20 of a user not wearing a mask and another terminal device 20 is within a predetermined value (threshold value). If the distance between the first terminal device 20 and the other terminal device 20 is within the predetermined value, the identification unit 150 notifies the first terminal device 20 via the communication unit 110 of information encouraging the user to wear a mask. As a result, when another user is present in the vicinity of a user not wearing a mask, the management device 100 can present information encouraging the user not wearing a mask (first terminal device 20) to wear a mask. Therefore, the management device 100 can reduce the possibility that users of individual terminal devices 20 will be infected with a virus. Note that the threshold value for determining the proximity between the first terminal device 20 and another terminal device 20 may be set based on the wear score. For example, the threshold value may be set to a larger value as the wear score of the first terminal device 20 becomes lower. Furthermore, for example, when the wearing score of another terminal device 20 can be acquired, the lower the wearing score, the larger the threshold value may be set. Furthermore, for example, when the wearing score of another terminal device 20 cannot be acquired (is unknown), the threshold value may be set to a larger value than when the wearing score of another terminal device 20 can be acquired and the wearing score is high.

[0230] As in the above embodiments 1 to 10, the management devices 10, 100 in the infection prevention support system 1 can acquire information on the mask wearing status of people in unspecified locations and generate and provide information that is useful for reducing the risk of infection.

[0231] The present invention is not limited to the above-described embodiment, and modifications can be made as appropriate without departing from the spirit of the present invention. For example, the management device 10, 100 may include a monitoring unit that monitors the activation status of the UI of each terminal device 20. In this case, the monitoring unit (not shown) of the management device 10, 100 may inquire of the terminal device 20 about the activation status (lock status) of the UI at predetermined intervals, and if the UI is activated (unlocked), request the terminal device 20 to transmit a mask wearing status based on the most recent face image for face authentication and location information. Furthermore, the control unit 13, 130 of the management device 10, 100 may function as the monitoring unit.

[0232] In the above-described embodiment, the mask-wearing status is determined using a facial image for facial authentication. However, this is not limiting. For example, when a video call (videophone) is made on the terminal device 20, the mask-wearing status may be determined based on a facial image for the video call. Furthermore, for example, the mask-wearing status may be determined based on an image captured by an in-camera (selfie camera) of a smartphone or the like. The control unit 13, 130 (monitoring unit) of the management device 10, 100 may inquire of the terminal device 20 at predetermined intervals about the use of the video call or the selfie camera, and, if the video call or the selfie camera is used, request the terminal device 20 to transmit the mask-wearing status based on the most recent facial image and location information. Alternatively, the control unit 13, 130 may request the terminal device 20 to transmit the most recently captured facial image data and location information. Furthermore, the terminal device 20 may be triggered by the use of the video call or the selfie camera to transmit the facial image captured for that purpose to the management device 10.

[0233] Furthermore, the above-described first to sixth embodiments may be arbitrarily combined. For example, a modified example of the first embodiment may be combined with the second embodiment and the third embodiment. Furthermore, the second embodiment may be combined with the sixth embodiment. Furthermore, the fourth embodiment may be combined with the fifth embodiment. In this case, when generating route guidance information, the user is prompted to specify the departure date and time in addition to the departure point and destination. The control unit 13 predicts the arrival date and time based on this information. Furthermore, the control unit 13 calculates the future mask wearing rate in each area and each facility for the period from the departure date and time to the arrival date and time (future point in time). The control unit 13 preferentially selects a route that is predicted to have a high mask wearing rate at a future point in time and has a short travel distance (or a short travel time). Similarly, the fourth embodiment may be combined with the sixth embodiment. By such a combination, it is possible to preferentially select a route that is predicted to have a low number of infected people at a future point in time and has a short travel distance (or a short travel time) and present it to the user.

[0234] Furthermore, the above-described seventh to tenth embodiments may be arbitrarily combined. For example, at least one of the first to third modifications of the seventh embodiment may be combined with the eighth embodiment. Furthermore, the eighth embodiment may be combined with the ninth embodiment. In this case, when generating route guidance information, the user is prompted to specify the departure date and time in addition to the departure point and destination. The control unit 130 predicts the arrival date and time based on this information. Furthermore, the control unit 130 predicts the location of the high-risk area HA during the period from the departure date and time to the arrival date and time (future point in time). The control unit 130 preferentially selects a route that passes through a point that is a predetermined distance or more away from the high-risk area HA at a future point in time and has a short travel distance (or a short travel time). By using such a combination, it is possible to preferentially select a route that can avoid the high-risk area HA at a future point in time and has a short travel distance (or a short travel time) and present it to the user.

[0235] At least one of the above-described first to sixth embodiments may be combined with at least one of the seventh to tenth embodiments in any desired manner.

[0236] In the above embodiment, the present invention has been described as being configured as hardware, but the present invention is not limited to this. Any processing of the present invention can also be realized by having a processor execute a computer program.

[0237] In the above examples, the program can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic storage media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical storage media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, DVDs (Digital Versatile Discs), BDs (Blu-ray (registered trademark) Discs), and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)). The program may also be supplied to a computer by various types of transitory computer-readable media. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. The temporary computer-readable medium can supply the program to the computer via a wired communication path such as an electric wire or an optical fiber, or via a wireless communication path.

[0238] In the above-described embodiments, the computer is configured as a computer system including a personal computer, etc. However, the present invention is not limited to this. The computer can also be configured as a LAN (local area network) server, a computer (personal computer) communication host, a computer system connected to the Internet, etc. It is also possible to distribute functions among devices on a network and configure a computer across the entire network. Furthermore, the management device 10 of each embodiment can be configured using a distributed processing system in which multiple computers execute different functions, or a parallel processing system in which multiple computers execute the same function in parallel.

[0239] Furthermore, some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes. (Appendix A1) a collection unit that collects, for each of a plurality of terminal devices, information on whether a user of the terminal device is wearing a mask and location information of the terminal device; an index generation unit that generates an index indicating the mask wearing status in a target area based on the collected information on the mask wearing status and the collected location information; an output unit that outputs information related to the index; Equipped with The information on the mask wearing state is generated based on a face image for user authentication captured by the terminal device. Information processing device. (Appendix A2) The facial image for user authentication is captured to unlock the user interface of the terminal device. 10. The information processing device according to claim 1, (Appendix A3) the collection unit collects a score that quantifies the mask wearing state of the user as information about the mask wearing state, The index generation unit regards terminal devices whose location information is included in the target area as target terminals, and generates, as the index, a ratio of terminal devices whose score is equal to or greater than a predetermined threshold value among the target terminals, or a representative value of the score of the target terminals. An information processing device according to appendix A1 or A2. (Appendix A4) The information processing device according to any one of appendices A1 to A3, wherein the index indicates a mask wearing rate or a proportion of each wearing level categorized into wearing states. (Appendix A5) The collecting unit receiving face image data from each of the plurality of terminal devices; a generation unit for generating, for each of the plurality of terminal devices, information on the mask wearing state of the user of the terminal device based on a face image received from the terminal device; An information processing device according to any one of appendices A1 to A4. (Appendix A6) The collection unit acquires, for each of the plurality of terminal devices, face recognition score information of the user of the terminal device as the mask wearing state information from the terminal device. An information processing device according to any one of appendices A1 to A4. (Appendix A7) The output unit transmits information related to the index to the terminal device. An information processing device according to any one of appendices A1 to A6. (Appendix A8) The indicator generation unit identifies a terminal device included in the target area based on current location information of the terminal device, location information predicted after a predetermined time has elapsed based on the current location information, or location information specified by the terminal device, and generates the indicator based on information on the mask wearing state of the identified terminal device. An information processing device according to any one of appendices A1 to A7. (Appendix A9) The index generation unit determining the target area based on departure point information and destination information acquired from the terminal device; generating route guidance information indicating a route from the departure point to the destination based on the departure point information, the destination information, and the index of the target area; The output unit transmits the route guidance information to the terminal device. An information processing device according to any one of appendices A1 to A8. (Appendix A10) The index generation unit predicts an index indicating a mask wearing status in a target area from the present time onward based on the information on the mask wearing status collected up to the present time, The output unit outputs information related to the predicted index. An information processing device according to any one of appendices A1 to A9. (Appendix A11) The index generation unit predicts the number of people infected with an infectious disease from the present time onwards based on the information on the mask wearing status collected up to the present time, The output unit outputs information about the predicted number of people infected with the infectious disease. An information processing device according to any one of appendices A1 to A10. (Appendix A12) a plurality of terminal devices; Information processing device Equipped with Each of the plurality of terminal devices captures a face image for user authentication; The information processing device includes: a collection unit that collects, for each of a plurality of terminal devices, information on whether a user of the terminal device is wearing a mask, detected from the face image, and location information of the terminal device; an index generation unit that generates an index indicating the mask wearing status in a target area based on the collected information on the mask wearing status and the collected location information; an output unit that outputs information related to the index; Equipped with Infection prevention support system. (Appendix A13) The terminal device captures the face image in response to execution of an unlock process for unlocking a user interface. The infection prevention support system described in Appendix A12. (Appendix A14) On the computer, a collection process for collecting, for each of a plurality of terminal devices, information on the mask wearing state of the user of the terminal device and location information of the terminal device; An index generation process that generates an index indicating the mask wearing status in a target area based on the collected information on the mask wearing status and the collected location information; an output process for outputting information related to the index; A program for executing The mask wearing state is generated based on a face image for user authentication captured by the terminal device. program. (Appendix B1) a collection unit that collects information on a mask wearing state of a user of a first terminal device and location information of the first terminal device; an identification unit that, when the information on the mask wearing state collected by the collection unit does not satisfy a predetermined standard, identifies a terminal device located within a predetermined range based on the position of the first terminal device or a terminal device that is expected to be within the predetermined range as a second terminal device; a communication unit that notifies the second terminal device; Equipped with The information on the mask wearing state is generated based on a face image for user authentication captured by the first terminal device. Information processing device. (Appendix B2) The identification unit sets the predetermined range based on at least one of information on weather conditions, population density, and a state of wearing a mask by the user, and identifies a second terminal device located within the predetermined range. 10. The information processing device according to claim 8, wherein the information processing device is a device for processing information according to claim 1. (Appendix B3) The communication unit transmits, to the second terminal device, alert information indicating that the second terminal device is located in a place where there is a high risk of infection. An information processing device according to Appendix B1 or B2. (Appendix B4) the identification unit identifies, for each of the plurality of first terminal devices that have transmitted information on a mask wearing state that does not satisfy the predetermined standard, a range within a predetermined distance from the location of the first terminal device as a high-risk area; The communication unit transmits different alert information to the second terminal device depending on the number of high-risk areas in which the second terminal device is located. An information processing device according to any one of appendices B1 to B3. (Appendix B5) When the information on the mask wearing state collected by the collection unit does not satisfy a predetermined standard, the identification unit predicts, based on a movement history of at least one of the first terminal device and the second terminal device, that the second terminal device will be located within a high-risk area within a predetermined distance from the location of the first terminal device within a predetermined time period; The communication unit notifies the second terminal device. An information processing device according to any one of appendices B1 to B4. (Appendix B6) When the information on the mask wearing state collected by the collection unit does not satisfy a predetermined standard, the identification unit identifies an area within a predetermined distance from the location of the first terminal device as a high-risk area; generating route guidance information indicating a route from the departure point to the destination based on departure point information and destination information acquired from another terminal device and location information of the high-risk area; The communication unit transmits the route guidance information to the other terminal device. An information processing device according to any one of appendices B1 to B5. (Appendix B7) the identifying unit, when the information on the mask wearing state collected by the collecting unit does not satisfy a predetermined standard, determines whether the first terminal device is located within a predetermined distance from another terminal device; When the determination is true, the communication unit notifies the first terminal device. An information processing device according to any one of appendices B1 to B6. (Appendix B8) On the computer, A collection process of collecting information on a mask wearing state of a user of a first terminal device and location information of the first terminal device; If the information on the mask wearing state does not satisfy a predetermined standard, a determination process is performed to determine, as a second terminal device, a terminal device located within a predetermined range based on the position of the first terminal device or a terminal device expected to be within the predetermined range; a communication process for notifying the second terminal device; A program for executing The information on the mask wearing state is generated based on a face image for user authentication captured by the first terminal device. program. [Explanation of symbols]

[0240] 1,1a Infection prevention support system 10,100 Management device (information processing device) 11,110 Communications Department 12,120 Timing section 13,130 Control unit 14,140 Collection Department 15 Indicator generator 16 Output section 17,170 storage section 18,180 Mask Information Table 19 Map Database 20 Terminal equipment 21 Communications Department 22 Display section 23 Input section 24 Audio output section 25 Location identification part 26 Face Recognition Unit 27 Imaging unit 28 Control Unit 29 Memory section 30 Relay Device 150 Specific section 190 User Location Information Table Network Internet T Terminal Device List HA High Risk Area UA User Area

Claims

1. an imaging unit that captures a facial image of a user of the terminal device; a location identification unit that acquires location information of the terminal device; Based on the face image for user authentication captured by the imaging unit, the user is identified as a legitimate user. and determining whether the user is wearing a mask, and a control unit that generates When the control unit determines that the user currently using the mask is an authorized user, a transmitting unit that transmits the wearing state information and the position information to a management device; Mask wearing rate, which corresponds the location information of each area with the mask wearing rate in that area a receiving unit that receives data from the management device; Equipped with The control unit determines a display format for each area according to the mask wearing rate. Terminal device.

2. The control unit determines the mask wearing rate in the area specified based on the position information of the position specifying unit. is less than a predetermined value, a warning is issued. The terminal device according to claim 1 .

3. The receiving unit receives a predicted data including a predicted value of the mask wearing rate in each area corresponding to a future date and time. further receiving data from the management device; The control unit refers to the prediction data and calculates the date and time included in the user's schedule information. If the predicted mask wearing rate for a certain area is less than a predetermined value, a warning message will be sent. Ru, 3. The terminal device according to claim 1 or 2.

4. The terminal device computer A step of capturing a face image of a user of the terminal device; acquiring location information of the terminal device; Based on the facial image taken for user authentication, it is determined whether the user is a legitimate user. and generate mask wearing status information indicating whether the user is wearing a mask. Steps and If the user is determined to be an authorized user, transmitting the mask wearing state information and the location information to a management device; Mask wearing rate, which corresponds the location information of each area with the mask wearing rate in that area receiving data from the management device; A program for executing the generating step determines a display format for each area depending on the mask wearing rate; program.

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