Health management system, health management method, and program

Abstract

To provide a health management system capable of enhancing the health consciousness of persons present in a predetermined area and improving the health level of all the persons present in the predetermined area.SOLUTION: A health management system 1 according to an embodiment includes: a first determination part 1a for determining a moving state of a passerby based on image data obtained by photographing the passerby by a camera installed in a predetermined area; a calculation part 1b for calculating an indicator indicating a group health condition which is a health condition of all persons present in the predetermined area based on a determination result in the first determination part 1a; and a display part 1c for displaying the indicator calculated by the calculation part 1b.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a health management system, a health management method, and a program. [Background technology]

[0002] Patent Document 1 describes a technology that acquires biometric information of a target, identifies the position of the target in a collective distribution of biometric information of a group with the same attributes as the target, identifies biometric information corresponding to the position in a collective distribution of biometric information of a group with attributes different from those of the target, and uses the identified biometric information as input to estimate the health condition of the target using a predictive model. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-166441 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technology described in Patent Document 1 can estimate the health status of a target individual or a predetermined group of people, but it is necessary to identify the individual or the predetermined group and obtain the biometric information of the individual or the group. Therefore, the technology described in Patent Document 1 cannot estimate the health status of all people present (or present) in a specified area, including people entering and leaving the specified area of ​​a local government, nor can it improve the health status of all people present in the specified area.

[0005] The present disclosure has been made in consideration of the problems described above, and provides a health management system, health management method, and program that can raise the health awareness of people in a specified area and improve the overall health level of people in the specified area. [Means for solving the problem]

[0006] The health management system according to the present disclosure includes a first determination unit that determines the movement of passersby based on image data of the passersby captured by a camera installed within a specified area, a calculation unit that calculates an index indicating a collective health state, which is the health state of all people present within the specified area, based on the determination result of the first determination unit, and a display unit that displays the index calculated by the calculation unit.The health management system can display information indicating the overall health state of the specified area for people present within the specified area, thereby raising the health awareness of people present within the specified area and improving the health level of all people present within the specified area.

[0007] The display unit may display the calculated index for each of the predetermined areas in a ranking format, thereby enabling the health management system to compare health conditions with those of other predetermined areas, thereby raising health awareness among people in the predetermined area and improving the overall health level of people in the predetermined area.

[0008] The display unit may include a display device disposed outdoors in the predetermined area. In this way, the health management system allows the health status of the predetermined area to be confirmed outdoors, so that people's behavior outdoors from the time of confirmation can be changed, and the health level of the entire people in the predetermined area can be further improved.

[0009] The first determination unit may determine the movement of the pedestrian and determine the health condition of the pedestrian based on face image data included in the image data. This allows the health management system to determine the health condition of the pedestrian in a more multi-dimensional manner, thereby making it possible to display more accurate information indicating the health condition of the entire predetermined area.

[0010] The calculation unit may calculate a statistical value of the passing speed of all people present in the specified area based on the determination result of the first determination unit, and the display unit may display the statistical value as the index or as a part of the index. In this way, the health management system can make the information indicating the health status of the entire specified area easier to understand for people, thereby further improving the health level of all people present in the specified area.

[0011] Here, the calculation unit may determine a target value for the travel speed based on the statistical value, and the display unit may display the statistical value and the target value as the index or as a part of the index. In this way, the health management system can make people in a specified area aware of the goal, thereby further improving the health level of all people in the specified area.

[0012] The health management system may include a resident determination unit that determines whether the passerby is a resident residing in the specified area based on the image data, and determines the actual age of the resident if the passerby is a resident, and the calculation unit calculates a first statistical value that is a statistical value of the difference between the health age and the actual age of all people who exist and reside in the specified area based on the determination result of the first determination unit for the resident, calculates a non-resident health age that is the health age of all people who exist but do not reside in the specified area based on the determination result of the first determination unit for people other than the resident, and calculates a statistical value of the difference between the health age and the actual age of all people who exist in the specified area based on the first statistical value and the non-resident health age as the index or part of the index. In this way, the health management system can not only calculate the difference between the health age and the actual age of all people who exist in the specified area using a relatively accurate difference between the health age and the actual age of the resident, but also can make people in the specified area aware of goals based on the calculation result, thereby further improving the health level of all people in the specified area.

[0013] The health management system may include an acquisition unit that acquires determination data used to determine the health condition of the pedestrian from a terminal device carried by the pedestrian, and a second determination unit that determines the health condition of the pedestrian based on the determination data acquired by the acquisition unit, and the calculation unit may calculate the index based on the determination results of the first determination unit and the determination results of the second determination unit. This allows the health management system to determine the health condition of pedestrians in a more multi-dimensional manner, and therefore the information indicating the health condition of the entire specified area to be displayed can be more accurate.

[0014] The health management system may further include a generating unit that generates, for each of the predetermined areas, a change instruction for changing predetermined information related to life in the predetermined area based on the index calculated by the calculating unit. In this way, the health management system can change the predetermined information related to life in the predetermined area and people can act based on the changed information, thereby further improving the health level of the entire people in the predetermined area.

[0015] Here, the generating unit may generate the change instruction for each attribute of a resident residing in the specified area, whereby the health management system can change predetermined information related to life in the specified area for each attribute of the resident, and the resident can act based on the changed information, thereby further improving the health level of the entire people existing in the specified area.

[0016] The health management system may further include an incentive calculation unit that calculates an incentive to be granted for each of the predetermined areas based on the index calculated by the calculation unit. In this way, the health management system can grant the incentive calculated for each of the predetermined areas to each of the predetermined areas, thereby further improving the health level of the entire population in the predetermined areas.

[0017] The health management method according to the present disclosure comprises a computer determining the movement of passersby based on image data of the passersby captured by a camera installed within a specified area, calculating an index indicating a collective health state, which is the overall health state of people present within the specified area, based on the determination result, and controlling the computer to display the calculated index on a display device connected to the outside of the computer or provided within the computer. The health management method can display information indicating the overall health state of the people present within the specified area, thereby raising the health awareness of the people present within the specified area and improving the health level of the entire people present within the specified area.

[0018] The program according to the present disclosure is a program for causing a computer to execute a process of determining the movement of passersby based on image data of the passersby captured by a camera installed within a specified area, calculating an index indicating a population health state, which is the overall health state of people present within the specified area, based on the determination result, and displaying the calculated index on a display device connected to the outside of the computer or provided within the computer. The program can display information indicating the overall health state of people present within the specified area, thereby raising the health awareness of people present within the specified area and improving the health level of all people present within the specified area. Effect of the Invention

[0019] According to the present disclosure, it is possible to provide a health management system, a health management method, and a program that can raise the health awareness of people in a specified area and improve the overall health level of people in the specified area. [Brief description of the drawings]

[0020] [Figure 1] 1 is a block diagram showing an example of a configuration of a health management system according to an embodiment; [Diagram 2]FIG. 2 is a flow diagram illustrating an example of processing in the health management system of FIG. 1. [Diagram 3] FIG. 2 is a block diagram showing a more specific example configuration of the health management system of FIG. 1. [Figure 4] 4 is a schematic top view showing an example of the arrangement of a camera and a display device in the health management system of FIG. 3. [Diagram 5] 4 is a schematic diagram showing an example of a display image displayed on a display device in the health management system of FIG. 3. [Figure 6] 7 is a schematic diagram showing another example of a display image displayed on the display device in the health management system of FIG. 3. [Figure 7] FIG. 2 is a block diagram showing another more specific example configuration of the health management system of FIG. 1. [Figure 8] 8 is a schematic diagram showing an example of a display image displayed on a display device in the health management system of FIG. 7. [Figure 9] FIG. 8 is a block diagram showing an example configuration of a learning system that generates a learning model used in the health management system of FIG. 3 or FIG. 7. [Figure 10] FIG. 10 is a diagram showing an example of teacher data used in the learning system of FIG. [Figure 11] FIG. 2 illustrates an example of a hardware configuration included in the apparatus. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] 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. Also, not all of the configurations described in the embodiments are necessarily essential as means for solving the problems. The embodiments will be described below with reference to the drawings.

[0022] <Embodiment> Fig. 1 is a block diagram showing an example of the configuration of a health management system according to the present embodiment. As shown in Fig. 1, the health management system 1 according to the present embodiment can include a first determination unit 1a, a calculation unit 1b, and a display unit 1c.

[0023] The first determination unit 1a determines the movement of a passerby based on image data of the passerby photographed by a camera installed within a specified area. This image data can be acquired as data of the passerby photographed by a camera installed within the specified area. In order to acquire such image data, the health management system 1 can include an image acquisition unit (not shown). This image acquisition unit can include a communication unit. The image acquisition unit and the camera correspond to a monitoring unit that monitors the passerby, since the camera photographs the passerby and acquires the image data. The camera is an imaging device.

[0024] Here, the predetermined area may be any area that has been determined in advance, and may be, for example, one local government, a number of neighboring local governments, a commercial area such as a shopping street, a company's premises or buildings, or other geographical areas. The predetermined area is an area for managing passers-by. Therefore, even if the company's premises or buildings are set as the predetermined area, passers-by include not only employees but also visitors. In addition, for example, if one of the predetermined areas is a first local government (for example, Tokyo) and the other is a second local government (for example, Saitama Prefecture) adjacent to the first local government, if there is a person who lives in the second local government but visits the first local government, the following will occur. That is, the person's movement is determined as a passer-by in the first local government, and the person will be counted as a passer-by in the first local government when calculating the number of passers-by, as described below.

[0025] In addition, as can be seen from the example of a company building as the predetermined area, the installation location of the camera is not limited to outdoors, but may also include indoors. For example, the camera can be installed in one or more sensing areas arranged at the gate to the predetermined area or various other locations within the predetermined area. The sensing area at each installation location can also be called a sensing zone. In addition, for example, the movement of passersby is used to manage health conditions, so this sensing zone can also be called a health care zone. This health care zone can be installed as a zone where various data indicating health conditions are acquired by a user simply passing through the zone by walking or the like. The health care zone can include various sensors required for acquiring cameras and other information, a support such as a pole or gate that supports the cameras and other sensors, and a communication unit that transmits imaging data (image data) captured by the cameras and measurement results by the other sensors. As described as the installation location of the camera, the health care zone can be installed at least in a location where people are likely to pass through the predetermined area, such as the entrance to the predetermined area, and can also be installed continuously from that location, for example at a certain interval, or can be installed at a bus stop. The cameras can also be used as security cameras to improve security in a given area.

[0026] In addition, the state of movement of a pedestrian refers to the state of passage of a pedestrian. The movement of a pedestrian can refer to passage involving movement, such as walking or running of a pedestrian, or running of a person riding a bicycle. Therefore, the movement of a pedestrian can basically exclude movement by driving an automobile or a motorcycle, but since the state of movement can be determined from a face image, for example, when such a determination is made, movement by driving an automobile or a motorcycle can also be included.

[0027] The calculation unit 1b calculates an index indicating a population health condition, which is the health condition of all people present in the specified area, based on the judgment result by the first judgment unit 1a. The calculation unit 1b can calculate, as the index, for example, statistical values ​​such as walking pattern, gait, and health age by statistical calculation or by using a learning model. Here, the health age generally refers to an age calculated based on various measurements taken in a health checkup, but the health age here can be an age estimated from information obtained from image data so as to match it, and the definition is not important.

[0028] In other words, the first judgment unit 1a can obtain values ​​that enable the calculation unit 1b to calculate such indices, such as the walking state, gait, and health age of each passerby, as judgment results. The calculation unit 1b can also calculate the indices as estimated values, that is, estimate them. Note that this group health condition refers to the health condition within the above-mentioned specified area, so it can also be called an area health condition. In addition, the health management system 1 can also be called a health condition calculation system because it performs such calculations.

[0029] The display unit 1c displays the index calculated by the calculation unit 1b. The display unit 1c may include one or more display devices and a display control unit that controls the display on those display devices. The display unit 1c may visualize the index, but may also display a comparison result with a previous index, for example, a comparison between last week and this week. In addition, as an index, a value indicating an overall health age for a specified period, such as today, this week, or this month, may be calculated and displayed. Indicators for each specified area may be displayed on a map, similar to the method of displaying the weather in a weather forecast.

[0030] The above-mentioned first judgment unit 1a, calculation unit 1b, and display control unit can be provided as a control unit that controls the entire health management system 1. This control unit can be realized, for example, by an integrated circuit, and can be realized, for example, by a processor such as a CPU (Central Processing Unit), a working memory, and a non-volatile storage device. A control program executed by the processor is stored in this storage device, and the processor reads the program into the working memory and executes it, thereby achieving the judgment function in the first judgment unit 1a, the calculation function in the calculation unit 1b, and the display control function in the display control unit.

[0031] Next, an example of a health management method executed in the health management system 1 will be described with reference to Fig. 2. Fig. 2 is a flow diagram for explaining an example of processing in the health management system 1.

[0032] In this health management method, first, the first judgment unit 1a inputs image data of passersby captured by a camera installed within a specified area, and judges the movement of the passersby based on the image data (step S1). Next, the calculation unit 1b calculates an index indicating a collective health condition, which is the health condition of all people present within the specified area, based on the judgment result (step S2). Next, the display unit 1c displays the calculated index (step S3), and the process ends.

[0033] This health management method can be executed mainly by a computer, and in step S3, the computer controls a display device connected to an external device or provided in the computer to display the calculated index. The above-mentioned control program can include a program for causing a computer to execute the processing shown in this health management method.

[0034] As described above, the health management system 1 can grasp the health conditions of people present in a specified area, for example, of a local government or the like, including people entering and leaving the specified area, that is, people who are present in the specified area at the time of image data acquisition, as a whole specified area. The health management system 1 can then display information indicating the grasped health conditions of the entire specified area. Thus, the health management system 1 can increase the health awareness of people present in the specified area and improve the health level of all people present in the specified area. The health level refers to a level indicating the health condition.

[0035] Next, a more specific configuration example of the health management system 1 will be described with reference to Figs. 3 to 6. Fig. 3 is a block diagram showing a more specific configuration example of the health management system of Fig. 1. Fig. 4 is a schematic top view showing an example of the arrangement of a camera and a display device in the health management system of Fig. 3. Fig. 5 is a schematic diagram showing an example of a display image displayed on the display device in the health management system of Fig. 3, and Fig. 6 is a schematic diagram showing another example of a display image displayed on the display device in the health management system of Fig. 3.

[0036] The health management system 2 shown in Fig. 3 can include a health management device 10, a plurality of display devices 20a, 20b,..., and a plurality of cameras 30a, 30b,... Of course, the camera 30a, etc. may not be included in the components of an example of the health management system 1. In the following, when the display devices 20a, 20b,... are not distinguished from one another, they will be referred to as display devices 20. Similarly, when the cameras 30a, 30b,... are not distinguished from one another, they will be referred to as camera 30.

[0037] Health management device 10 may include a control unit 11 that controls the entire health management device 10, a memory unit 12 that is configured as a memory device, and a communication unit 13 that is configured as a communication interface or the like that communicates with external devices. Health management device 10 may be configured to include, for example, a computer. Health management device 10 may be configured as a standalone device, or may be configured as a distributed system in which its functions are distributed.

[0038] The control unit 11 includes a first determination unit 1a and a calculation unit 1b, and also includes functions other than an interface for communication in the display control unit. The interface function for communication in the display control unit is performed by a communication unit 13. The communication unit 13 also functions as an example of an image acquisition unit, and receives image data acquired by the camera 30 from the camera 30.

[0039] The control unit 11 can be realized by, for example, a processor, a working memory, and a non-volatile storage device. The control program executed by the processor is stored in this storage device, and the processor reads the program into the working memory and executes it, thereby fulfilling the function of the control unit 11. The storage unit 12 can utilize a part of the storage area of ​​the storage device. The control program can include a program for implementing the determination function in the first determination unit 1a, a program for implementing the calculation function in the calculation unit 1b, and a program for implementing the display control function in the display control unit. In that case, the processor reads the program into the working memory and executes it, thereby fulfilling these functions. The functions not included in the control program can be realized by a hardware configuration.

[0040] The control unit 11 receives image data of a passerby photographed (captured) by a camera 30 installed within a predetermined area from the camera 30 via the communication unit 13, and judges the movement of the passerby based on the image data. The image data captured by the camera 30 and received from the camera 30 can be still image data, a series of still image data captured at a predetermined interval, or video image data. As described above, the movement can be, for example, a walking pattern, gait, health age, etc. The judgment results of the walking pattern and gait can be obtained as values ​​indicating the difference from a standard walking pattern and gait, respectively.

[0041] The control unit 11 calculates an index indicating a population health condition, which is the health condition of all people present in the specified area, based on the judgment result of the movement of passersby. The control unit 11 can calculate, as the index, for example, statistical values ​​such as walking behavior, gait, and health age, using the learning model 12a stored in the storage unit 12. The learning model 12a is a model trained by machine learning to input the judgment result and output the index, and the algorithm thereof is not important.

[0042] Alternatively, the control unit 11 can receive image data of passersby captured by a camera 30 installed within a predetermined area from the camera 30 via the communication unit 13, and calculate the above-mentioned indices from the image data using a learning model stored in the storage unit 12. The learning model in this case differs from the learning model 12a in that it is a model that has been machine-learned to input image data and output the above-mentioned indices. The algorithm of this learning model is not important.

[0043] Then, the control unit 11 performs control to display the calculated index on the display device 20. The display device 20 only needs to be able to visualize the index, but may also display a comparison result with a previous index, such as a comparison between last week and this week. In addition, as the index, a value indicating the overall health age for a specified period, such as today, this week, or this month, may also be calculated and displayed. Indicators for each specified area may also be displayed on a map, similar to the method of displaying the weather in a weather forecast.

[0044] The timing of calculation and display of such an index can be processed from image data acquired for a predetermined period such as one day. In this case, the control unit 11 can perform face recognition processing between image data to exclude duplicated people. Then, the control unit 11 performs processing such as selecting the oldest or newest data from the image data of a passerby captured multiple times during a predetermined period, or selecting image data that best represents the movement of the passerby by taking statistics, and the resulting image data can be used as input to the learning model 12a.

[0045] The memory unit 12 stores the above-mentioned learning model 12a, as well as other setting values ​​necessary for control in the control unit 11. The learning model 12a is a learning model that inputs the judgment results of the movement of passersby and outputs, for each predetermined area, an index indicating a population health state, which is the health state of all people present in the predetermined area, and the algorithm thereof is not limited. Furthermore, the input parameters are not limited to those mentioned above.

[0046] The learning model 12a can be obtained, for example, as follows. That is, a data set including the judgment result of the movement of each passerby and the correct answer data indicating a statistical value (index) obtained by statistically processing the health age of each passerby at that time, etc., can be input to an unlearned learning model and machine learning can be performed to obtain the learning model 12a. For example, a plurality of data sets in which at least one of the judgment timing and the specified area is different from each other can be used for learning. Indicators of passersby are not limited to such statistical values, and can be determined, for example, by a model creator or the like. The learning model 12a can be a model that can accurately judge an index indicating a group health state by learning data sets for many timings and specified areas without overlearning. A system that performs such learning will be described later.

[0047] Communication unit 13 communicates with camera 30 via a wired network, passing image data captured by camera 30 to control unit 11, and also communicates with display device 20 via the wired network, outputting a display image to display device 20 under the control of control unit 11. Either network may be a wireless network, and any method of communication between communication unit 13 and camera 30 or display device 20 may be used.

[0048] The camera 30 is a camera installed within a specified area, and transmits captured image data to the health management device 10 via a wired network. The timing of transmission may be, for example, at a specified interval, or when an image of a person is captured if the camera is provided with a person detection function. The camera 30 may have a built-in or connected communication interface for the transmission.

[0049] Here, an example is given in which the area shown in FIG. 4 is a predetermined area, and a plurality of cameras 30 are provided therein. The area shown in FIG. 4 includes a main road with lanes (roads) 51-53 and sidewalks 54, 55, a first small road with roads 56, 57 and sidewalks 58, 59 crossing the main road, and a second small road with roads 60, 61 and sidewalks 62, 63 forming a T-junction with the main road at the end of the main road. In addition, in this area shown in FIG. 4, two crosswalks 50 are provided crossing the roads 56, 57 of the first small road, and pedestrian bridges 64, 65 are provided along the first small road so that people can cross on foot over the roads 51-53 of the main road. Also, FIG. 4 shows a state in which users U1, U2, a car M1, and an autonomous mobile vehicle M2 such as an autonomous mobile bus exist within the illustrated area. However, since people, cars, etc. are constantly moving, this only shows a state at a certain moment.

[0050] As the cameras 30 provided in the area shown in FIG. 4, sensing zones 30a and 30f are provided in which sensors including the camera 30 are provided on the walkways 54 and 55 corresponding to the entrances and exits of the specified area, and cameras 30b and 30c are provided on the walkway 54, and cameras 30d and 30e are provided on the walkway 55. Although not shown, sensing zones can also be provided at the entrances and exits of the above areas on the walkways 58, 59, 62, and 63. The cameras 30b and 30c and the cameras 30d and 30e can be installed on poles provided on the walkways 54 and 55, respectively. The sensing zones 30a and 30f can be installed in an arch spanning both ends of the walkway 54, but can also be installed in a pole similar to the camera 30b.

[0051] At least one of the display devices 20 provided in the health management system 2 can be a display device such as a digital signage that is arranged outdoors in a predetermined area. In the example of FIG. 4, a digital signage 20j provided on the sidewalk 54, a digital signage 20k provided on the sidewalk 55, and a digital signage 20p for the roadway 51 are installed as the display devices 20. Since it can be said that it is desirable not to provide unnecessary information while driving, the calculated index does not need to be displayed on the digital signage 20p. By adopting such an outdoor display, the health management system 2 can check the health status of the predetermined area outdoors, so that the behavior of people outdoors from the time of checking can be changed, and the health level of the entire people present in the predetermined area can be further improved.

[0052] In order to specify the display device 20 to be displayed, the storage unit 12 stores location information indicating the location of the display device 20 or information indicating a specific area in which the display device 20 is installed (not shown). This allows an instruction to cause the display device 20 corresponding to the specific area to display the index calculated for that specific area. The location information may be any information that identifies the location, such as information indicating latitude and longitude, or information indicating coordinates on map data.

[0053] Furthermore, the control unit 11 can control the display device 20 to display the calculated index for each predetermined area in a ranking format. For example, as shown in FIG. 5, the display device 20 can display an image showing the calculated health age in a ranking format for each of the neighboring cities A to E as the predetermined area. FIG. 5 also shows an example in which the health age is displayed on a map of each city to make the positional relationship of each city easier to understand. Of course, the name of each city can also be displayed on the map. Also, information such as an arrow showing the up and down movement of the ranking over time can be displayed at the same time.

[0054] By adopting such a ranking format display, the health management system 2 allows the health status of a specific area to be compared with that of other specific areas and allows specific areas to compete with each other, thereby raising the health awareness of people in the specific area and further improving the overall health level of people in the specific area.

[0055] Furthermore, the control unit 11 can control the display device 20 to display the index of a specific predetermined area, such as an adjacent predetermined area, and the index of a target predetermined area in a comparable manner. For example, as shown in Fig. 6, the display device 20 can display an image showing the monthly change in health age calculated for the area and an adjacent area adjacent to the area.

[0056] By adopting such a comparative display, the health management system 2 can compare the health status with that of other designated areas and make designated areas compete with each other, thereby raising the health awareness of people in the designated area and further improving the overall health level of people in the designated area.

[0057] Furthermore, the control unit 11 may determine the movement of passersby as a function of the first determination unit 1a, and may also determine the health condition of passersby based on the facial image data included in the image data. The method of determining the health condition from the facial image is not limited. For example, the determination can be made based on various criteria, such as determining a high health age for people with a brownish complexion, determining a high health age for people with many wrinkles on the forehead or at the corners of the eyes, and determining a high health age for people with deep nasolabial folds.

[0058] The control unit 11 can also determine a psychological state such as a stress level as a type of health condition from the facial expression data included in the facial image data. It is assumed that there may be passersby whose facial images cannot be obtained due to the angle at which they are photographed, but since the information that is ultimately required is an index and can be statistically processed, in that case, it is sufficient to determine the psychological state only for passersby whose facial images have been obtained. The stress level may be an index indicating the degree of stress (stress level) of the user, and the stress level can be determined as one of a plurality of predetermined levels. The degree of stress may be, for example, a degree indicating whether the user is in an overstressed state or in a normal state. An overstressed state may indicate a state of impatience or irritation.

[0059] This allows the health management system 2 to determine the health condition of passersby in a more multi-dimensional manner, and therefore allows the displayed information indicating the health condition of the entire predetermined area to be more accurate.

[0060] In addition, the control unit 11 may calculate, as a function of the calculation unit 1b, a statistical value of the passing speed of all people present in a specified area as an index or as a part of the index based on the result of the judgment of the movement state. For example, the passing speed can be calculated by acquiring [amount of change in the position of the passerby identified from the image data] and [the acquisition interval of the camera image corresponding to the amount of change] for each passerby as the judgment result of the movement state, and [amount of change in the position of the passerby identified from the image data] / [the acquisition interval of the camera image corresponding to the amount of change] for each passerby. Then, the control unit 11 performs statistical processing on this value calculated for each passerby for all people present in the specified area to obtain a statistical value of the passing speed. The passing speed can also be calculated by distinguishing between the walking speed of pedestrians and the running speed of bicycles. Of course, the learning model 12a can also be used for the calculation of the passing speed. In this case, the display device 20 displays the calculated statistical value of the passing speed as an index or as a part of the index.

[0061] By visualizing and presenting the traffic speed within a specified area in this way, the health management system 2 can make the displayed information indicating the health status of the entire specified area easier to understand for people, thereby further improving the health level of all people present within the specified area. In other words, by visualizing and presenting the traffic speed within the specified area, the health management system 2 can improve the average traffic speed throughout the specified area and improve the health level.

[0062] Here, the control unit 11 may determine a target value for the travel speed based on the calculated statistical value, and display the determined target value as an index or as a part of the index, in addition to the statistical value, on the display device 20. In this way, the health management system 2 can make people in the specified area aware of the goal, thereby further improving the health level of the entire people in the specified area.

[0063] As an index other than the travel speed, for example, a skeleton is recognized from a person's posture and physique based on image data, a stride length and walking speed are calculated, and walking ability is calculated as a part of the index based on the skeleton, stride length, and walking speed, and a statistical value of walking ability can be calculated. Note that a learning model can also be used for such skeleton recognition.

[0064] Next, another more specific configuration example of the health management system 1 will be described with reference to Fig. 7 and Fig. 8. Fig. 7 is a block diagram showing another more specific configuration example of the health management system of Fig. 1. Fig. 8 is a schematic diagram showing an example of a display image displayed on a display device in the health management system of Fig. 7.

[0065] 7 may include a health management device 10a, a plurality of display devices 20, a plurality of cameras 30, and a target management system 21. Of course, the camera 30a, the target management system 21, etc. may not be included in the components of an example of the health management system 1. The display device 20 and the camera 30 are as described in the configuration example of FIG.

[0066] The health management device 10a is a device that controls multiple display devices 20 and target management systems 21, and can be configured to include, for example, a computer. It can be said that the health management device 10a is equipped with a target management system control device for controlling the target management systems 21. The health management device 10a can be configured as a standalone device, but it can also be configured as a distributed system in which its functions are distributed. Also, although an example is given here in which one target management system 21 is included in the health management system 3, the number of target management systems to be controlled is not important.

[0067] The target management system 21 can be a system for managing various incentive targets, such as a points management system for managing points that can be used in a product purchasing service that can be used at least in the specified area. The type of product purchasing service and the value of the points to be awarded are not important. Of course, for convenience, the description will be given as one target management system 21, but a separate system can be constructed for each incentive target.

[0068] The health management system 3 may also include a group of sensors for obtaining information used for control in the health management device 10a, as a component of an example of the health management system 1. As shown in FIG. 3, the group of sensors may also include, for example, wearable devices 41a, 41b,... worn by each user, in addition to a plurality of cameras 30. The health management system 3 may also include terminal devices 40a, 40b,... that transmit information measured by the wearable devices 41a, 41b,... to the health management device 10a, and the terminal devices 40a, 40b,... may also be used to display indicators. Of course, the cameras 30a, etc., the wearable devices 41a, etc., and the terminal devices 40a, etc. may not be included in the components of an example of the health management system 1.

[0069] In the following description, when the terminal devices 40a, 40b, . . . and the wearable devices 41a, 41b, . . . are not distinguished from one another, they will be referred to as the terminal device 40 and the wearable device 41, respectively.

[0070] Although an example has been given in which the psychological state of a passerby, such as a stress level, is determined based on image data acquired by the camera 30, the psychological state can also be determined using vital information measured by the wearable device 41. The wearable device 41 is an example of a measuring device (measuring apparatus) that measures vital information of a user in order to determine the psychological state, such as the stress level, and other types of health conditions of the user using the health management apparatus 10a. The wearable device 41 can be, but is not limited to, a smart watch, a smart ring, an IC chip embedded in the body, or the like.

[0071] Furthermore, the vital information measured by the wearable device 41 may be, for example, information indicating one or more of pulse or heart rate, respiration (rate), blood pressure, body temperature, etc. Note that the measured vital information is not limited to this and may be information indicating an electrocardiogram, etc. Furthermore, the value of the vital information is information whose value changes even for the same user, for example, while holding the urge to go to the bathroom, while running, while walking normally, etc.

[0072] The wearable device 41 transmits the acquired vital information directly or indirectly to the health management device 10a. In other words, the wearable device 41 may have a built-in or connected communication interface for the transmission. Note that the wearable device 41 may also be configured to measure a stress level and transmit the measured value to the health management device 10a.

[0073] In a simple example, the wearable device 41 can be configured to spontaneously transmit vital information to the health management device 10a, for example, at a predetermined interval. This transmission may be direct or indirect. In this case, the health management device 10a can have a function of collecting and managing vital information as a server device (not shown) or the like. In this case, the wearable device 41 or a terminal device 40 such as a mobile terminal device connectable to the wearable device 41 may be permitted to transmit vital information to the health management device 10a in advance. In this example of spontaneous transmission, it is not necessary for the health management device 10a to send a vital information transmission request with the wearable device 41 specified. The vital information transmitted directly or indirectly from the wearable device 41 may include information indicating the user, and a resident determination unit described later may determine whether or not the user is a resident based on this information.

[0074] Regardless of whether the transmission is direct or indirect, and regardless of whether a request to transmit vital information is required, the vital information is received by communication unit 13 of health management device 10a and passed to control unit 11. As in this example, health management device 10a can include an acquisition unit that acquires data to be determined, such as vital information used to determine the health condition of a passerby, from wearable device 41, which is an example of a terminal device carried by a passerby. In Fig. 3, communication unit 13 and control unit 11 that controls the acquisition are examples of this acquisition unit.

[0075] An example will be given in which a wearable device 41 indirectly transmits vital information. The wearable device 41 transmits the vital information to a terminal device 40 used by a user wearing the device via short-range wireless communication or the like, and the terminal device 40 transmits the vital information to the health management device 10a. The terminal device 40 can be, for example, a mobile phone such as a smartphone, a tablet terminal, or a mobile PC (Personal Computer). In addition, the above and later-described short-range wireless communication methods can be used regardless of the method, and various methods can be adopted, such as Wi-Fi (registered trademark), Bluetooth (registered trademark), Bluetooth Low Energy (registered trademark), and ZigBee (registered trademark).

[0076] The terminal device 40 can also generate judgment data used to judge a health condition, such as a psychological state, from face image data captured by a camera provided therein, and transmit the judgment data to the health management device 10a. In this case, the judgment data can be obtained even without the wearable device 41. However, the health management device 10a can more accurately estimate the health condition of a passerby by acquiring both face image data and vital sign information as judgment data.

[0077] In addition, the determined data can be transmitted via a communication interface that is built into or connected to the camera 30 and that is capable of short-range wireless communication with the wearable device 41 or the terminal device 40.

[0078] The wearable device 41 or the terminal device 40 can be configured to automatically transmit the determined data when it enters an area where wireless communication with this communication interface is possible. In such a configuration, there is no need for the health management device 10a to send a request to transmit the determined data specifying the wearable device 41 or the terminal device 40. Also in this case, it is preferable to allow the wearable device 41 or the terminal device 40 to transmit the determined data to the health management device 10a in advance.

[0079] Alternatively, the wearable device 41 or the terminal device 40 can periodically transmit the determined data together with the position information to a server device (not shown) external to the health management system 3, and the server device can always manage the latest determined data and position information. In this case, the server device can be configured to return the determined data together with the position information when receiving a determined data transmission request from the health management device 10a. This allows the health management device 10a to use the determined data as determined data for a passerby in a specific area indicated by the position information.

[0080] Alternatively, the health management device 10a may transmit the determination data transmission request by broadcasting a notification according to the location information of the wearable device 41 or the terminal device 40, and in response to the transmission, the wearable device 41 or the terminal device 40 may return the determination data acquired in advance. In this case, the determination data may be transmitted when the wearable device 41 or the terminal device 40 enters a predetermined area only if the user of the wearable device 41 or the terminal device 40 permits the provision of information based on the location information.

[0081] The health management device 10a may further include a second determination unit that determines the health condition of a passerby based on the determined data acquired by the wearable device 41 or the terminal device 40. This second determination unit may also be realized as a function of the control unit 11. The second determination unit may input the determined data for each passerby from which the determined data can be acquired, and may determine the health condition of the passerby by using a learning model that outputs the health condition of the passerby. The algorithm of this learning model is not important.

[0082] The terminal device 40 can also be used to display an index. That is, at least one of the display devices 20 provided in the health management system 3 can be the terminal device 40 used by a passerby. In this case, the control unit 11 identifies a person included in the image data by performing either one of face recognition processing and gait recognition processing based on the image data, and transmits a display image via the communication unit 13 to a terminal device previously associated with the person, thereby making it possible to display the display image on the terminal device. In this case, information indicating the judgment result for the individual may be displayed together with information on the entire predetermined area. Note that it is practical to perform such association only for residents of the predetermined area, for example, and in that case, visitors to the predetermined area need not be displayed on the terminal device.

[0083] Alternatively, even if an individual is not specified, the communication unit 13 may be configured to transmit a display image via broadband, and the terminal device 40 may be configured to display the image when it receives the image.

[0084] The determined data obtained in this manner can be used to calculate an index showing the population health state as follows.

[0085] The learning model 12c stored in the storage unit 12 is a learning model that inputs the judgment result of the movement of passersby (hereinafter, the first judgment result) and the judgment result of the health condition of passersby based on the judged data (hereinafter, the second judgment result), and outputs an index indicating the collective health condition, which is the health condition of all people present in each predetermined area, regardless of its algorithm, etc. Also, the input parameters are not limited to these.

[0086] The learning model 12c can be obtained, for example, as follows. That is, a data set including the first judgment result, the second judgment result, and correct answer data indicating a statistical value (index) obtained by statistically processing the health age, etc., of each passerby at that time can be input to an unlearned learning model and machine learning can be performed to obtain the learning model 12c. For example, a plurality of data sets in which at least one of the judgment timing and the predetermined area is different from each other can be used for learning. In addition to such statistical values, the indicator of the passerby can be determined, for example, by a model creator or the like. The learning model 12c can be a model that can accurately determine an indicator indicating the health status of a group by learning data sets for many timings and predetermined areas without overlearning. A system that performs such learning will be described later.

[0087] Using such learning model 12c, control unit 11 can be configured to calculate an index indicating the population health state based on the first judgment result and the second judgment result. However, control unit 11 can also be configured to calculate an index indicating the population health state based on the first judgment result and the second judgment result without using learning model 12c.

[0088] In this way, by configuring health management device 10a to calculate an index using not only the first judgment result but also the second judgment result, it is possible to judge the health condition of passersby in a more multi-dimensional manner, and therefore the information displayed indicating the health condition of the entire specified area can be made more accurate.

[0089] Health management device 10a may also include a resident determination unit that determines whether or not a passerby is a resident residing in a specified area, and determines the actual age of the passerby if the passerby is a resident, based on image data received from camera 30. Health management device 10a may include, as the resident determination unit, a person information DB 12b, and a function of determining whether or not a passerby is a resident while referring to person information DB 12b, and a function of determining the actual age of the resident, and these functions may be provided in control unit 11.

[0090] The resident determination unit can determine whether a person is a resident and determine the actual age of the resident by, for example, at least one of face recognition processing and gait recognition processing. Therefore, the person information DB 12b can be a DB that stores at least one of face image data and gait data, and actual age information or personal identification information such as a name or ID including the actual age information, for each user residing in a specific area. In addition, the personal identification information can include information such as an ID that identifies the wearable device 41, or information such as an ID that identifies a terminal device 40 that can be connected to the wearable device 41, instead of or in addition to the name or ID.

[0091] However, the person information DB12b does not need to include personal identification information. This is because the control unit 11 can determine whether or not a person is a resident by comparing the image data with at least one of the face image data and the gait data, and can specify the actual age if the person is a resident. Note that the person information DB12b is a database (DB) that is referenced to determine whether or not a passerby is a resident, and does not need to be stored in a configuration that does not include the resident determination unit.

[0092] When face recognition processing is used to determine the resident, it is preferable that the camera 30 is installed so as to match conditions such as position, image capture direction, image capture magnification, etc., so that the user's face can be captured, and that the camera 30 is set up to capture images. When gait recognition processing is used to determine the resident, the camera 30 does not need to be installed so as to match such conditions, and it is sufficient that the camera 30 is installed so as to match conditions such as position, image capture direction, image capture magnification, etc., so that the user's walking figure can be captured (i.e., the entire user can be captured).

[0093] The resident determination unit may, for example, detect the presence of a person from the imaging data obtained by the camera 30, and perform the above-mentioned comparison process when the presence of a person is detected. In other words, the resident determination unit may perform the above-mentioned comparison process when a person enters the imaging range of the camera 30.

[0094] The resident determination unit can also be configured to use a learning model to determine whether or not a person is a resident and the actual age of the resident. That is, instead of the person information DB 12b, a learning model that inputs at least one of face image data and image data capturing an entire image of a resident in a predetermined area, and outputs information indicating the user, the wearable device 41, or the terminal device 40 including the actual age information, can be stored in the storage unit 12. During operation, the control unit 11 inputs image data captured by the camera 30 to this learning model, and can obtain information indicating the user, the wearable device 41, or the terminal device 40 including the actual age information, and can obtain the actual age information if the person is a resident. In the learning stage, machine learning is performed on a mobile terminal device used by each individual, and the resulting learning model or learned coefficients, etc. are transmitted to the health management device 10a, so that the health management device 10a can use the learning model for the individual to determine whether or not a person is a resident and determine the actual age if the person is a resident.

[0095] Then, the control unit 11 can calculate a first statistical value, which is a statistical value of the difference between the health age and the actual age of all people who exist and live in the specified area, based on the result of the determination of the movement state of the resident. The health age of each passerby can be estimated, for example, based on walking speed, gait (walking pattern), walking posture, etc., or based on gray hair, facial expression (facial aging), stress level, etc. obtained by analyzing face image data. The actual age can be calculated using the actual age information of the person who is determined to be a resident. The first statistical value can be obtained by statistically processing the health age of each passerby relative to the actual age for all residents. Then, the control unit 11 calculates the non-resident health age, which is the health age of all people who exist and do not live in the specified area, based on the result of the determination of the movement state of non-residents. The non-resident health age can also be estimated from walking speed, facial expression, etc., like the resident health age.

[0096] Furthermore, the control unit 11 can calculate a statistical value of the difference between the health age and the actual age for all people present in the specified area based on the first statistical value and the non-resident health age as an index or part of the index. In this way, the control unit 11 may estimate a statistical value of the difference between the health age and the actual age for all residents and non-residents by referring to the actual age information for residents.

[0097] The statistical value of the difference between the health age and the actual age can also be calculated using a learning model. For example, a supervised learning model that inputs the results of the judgment of the movement state (walking state, stress level, etc.) for a resident, outputs the difference between the health age and the actual age indicated by a face image, etc., and calculates the difference between the health age and the actual age for all passersby, and calculates the statistical value of the difference. Alternatively, a supervised learning model that inputs the results of the judgment of the movement state (walking state, stress level, etc.) for a resident, outputs the statistical value of the difference between the health age and the actual age indicated by a face image, etc., and calculates the statistical value of the difference between the health age and the actual age for all passersby. The statistical value of the difference between the health age and the actual age can also be calculated using the learning model 12a by constructing the learning model 12a so that the statistical value of the difference between the health age and the actual age is a part of the output parameters of the learning model 12a.

[0098] By configuring the system to calculate the statistical value of the difference between health age and actual age in this way, the health management system 3 can calculate the difference between health age and actual age for all people in a specified area using the relatively accurate difference between health age and actual age for a resident. Furthermore, the health management system 3 configured in this way can make people in a specified area aware of goals based on the calculation results, thereby further improving the health level of all people in the specified area.

[0099] The health management system 3 may also include an incentive calculation unit that calculates an incentive to be granted for each predetermined area based on the calculated index. Furthermore, the health management system 3 may also include an granting unit that issues an instruction to grant the calculated incentive to the target management system 21 via the communication unit 13. This incentive calculation unit can be implemented as one function of the control unit 11, and this granting unit can also be implemented as one function of the control unit 11. The management system information 12d stored in the memory unit 12 can be referred to when calculating such an incentive and when issuing an instruction to grant it.

[0100] The management system information 12d may include a connection destination such as an IP (Internet Protocol) address of the target management system 21 and an incentive value when an incentive is awarded. The management system information 12d may be changeable by an administrator or the like. In other words, the control unit 11 may include a setting unit (not shown) that sets the management system information 12d to be changed.

[0101] This granting unit may grant an incentive to a specific area when, for example, the calculated index such as health age is higher than a predetermined standard (for example, the average or median for all the specific areas). The incentive can be granted, for example, by granting points or electronic money that can be used at least in the specific area to the specific area to which the incentive is granted, or by increasing the government subsidy for the specific area. In addition, the incentive can be granted by lowering the premiums of the insurance subscribed to in the specific area (by discounting the premiums), or by increasing the funds for health promotion activities in the specific area. In either case, the granting unit may instruct the granting to the target management system 21 corresponding to the grantee.

[0102] With this configuration, the health management system 3 can grant incentives calculated for each specified area for each specified area, thereby further improving the health level of the entire population residing in the specified area.

[0103] Furthermore, the health management device 10a may include a generating unit that generates, for each predetermined area, a change instruction for changing predetermined information related to life in the predetermined area based on the index calculated by the function of the calculating unit 1b. Life in the predetermined area may refer to one or more of food, clothing, and shelter in the predetermined area. Information indicating the change instruction destination and the type of change to be made may be stored in the memory unit 12, for example.

[0104] The destination of the change instruction may be, for example, a predetermined facility, store, fee management system, etc., and the change instruction in this case may be an instruction to discount or increase overall fees related to food, clothing, and shelter, such as fares for public facilities, taxis, and buses, and the cost of food and drink at restaurants. For example, when the health level is lower than a predetermined value or is a predetermined value lower than in the past, the control unit 11 may notify a certain store of an instruction to increase the price of ramen by a certain amount and reduce the price of soba by a certain amount, and may display a menu image reflecting the instruction on the display device 21a of the store, as exemplified in FIG. 8.

[0105] Furthermore, the destination of the change instruction may be, for example, a predetermined transportation device (elevator, escalator (a step-like lifting device), horizontal escalator, etc.), and the change instruction may be an instruction to change the moving speed of the transportation device. For example, when the health level is lower than a predetermined value or is lower than a predetermined value compared to the past, the control unit 11 can slow down the moving speed of the transportation device so that passersby do not ride the transportation device as much, thereby eliminating their desire to use it. In this way, by controlling to increase inconvenience, it is possible to induce an increase in the exercise load.

[0106] By being equipped with such a generation unit, the health management system 3 can change predetermined information related to daily life within a specified area, and people can act based on the changed information, thereby further improving the health level of the entire population residing within the specified area.

[0107] The generating unit may generate a change instruction for each attribute of a resident residing in a predetermined area. The resident is not limited to a resident photographed by the camera 30 as a passerby, and may be a change instruction for a store or facility used by a general resident. The attribute may be, for example, an attribute distinguished by a healthy person, a person with a cane, an elderly person, a person with a disability, or an attribute distinguished by a passerby's gender, age, walking ability, or the like. The attribute may be determined from image data acquired by the camera 30, but may also be determined from individual identification information obtained by communication with the terminal device 40 or the like. The control unit 11 may also preferentially display a detour route when setting a route for navigation on the terminal device 40, only for a resident with a certain attribute, according to the calculated index.

[0108] By being equipped with such a generation unit, the health management system 3 can change predetermined information related to daily life within a specified area for each resident's attributes, and the residents can act based on the changed information, thereby further improving the health level of the entire population residing within the specified area.

[0109] Finally, a configuration example of a learning system that generates the above-mentioned various learning models will be described with reference to Fig. 9 and Fig. 10. Fig. 9 is a block diagram showing a configuration example of a learning system that generates a learning model used in the health management system 2 of Fig. 3 or the health management system 3 of Fig. 7. Fig. 10 is a diagram showing an example of teacher data used in the learning system of Fig. 9.

[0110] 9 may include a control unit 81, an input unit 82, and a storage unit 83. The learning system 80 may be constructed using a computer such as a PC for AI (Artificial Intelligence) learning. However, the learning system 80 may be configured as a single device or may have functions distributed across multiple devices.

[0111] The control unit 81 controls the entire learning system 80. The control unit 81 can be realized, for example, by an integrated circuit, and can be realized, for example, by a processor, a working memory, and a non-volatile storage device. A control program executed by the processor is stored in this storage device, and the processor reads the program into the working memory and executes it, thereby fulfilling the function of the control unit 81. The control program can include a learning program that executes learning. Note that the storage device can also utilize the memory unit 83.

[0112] The input unit 82 can be configured with at least one of an interface for performing data input operations and a communication interface for inputting data from an external device via communication. The input unit 82 inputs a data set of teacher data 84 required for learning, and stores it in the memory unit 83 so that it can be referenced during learning. The memory unit 83 can store this teacher data 84, and can store a learning model 85 as an unlearned model.

[0113] In the processing by the learning system 80, the control unit 81 performs machine learning on a learning model 85 as an unlearned model based on teacher data 84, and sets the learning model 85 as a trained model. Furthermore, when re-learning is required, the learning model 85 as a trained model can be re-trained based on a newly prepared data set.

[0114] The teacher data 84 for generating the learning model 12a may be a data set including the judgment result of the movement of each passerby and the correct answer data indicating a statistical value (index) obtained by statistically processing the health age, etc., of each passerby at that time, as described above. For example, multiple data sets in which at least one of the judgment timing and the predetermined area is different from each other may be used for learning.

[0115] Moreover, the teacher data 84 when generating the learning model 12c can be, for example, a data set including the first judgment result, the second judgment result, and correct answer data indicating a statistical value (index) obtained by statistically processing the health age of each passerby at that time, as described above. To give a more specific example, the teacher data 84 when generating the learning model 12c can be a data set as illustrated in FIG. 10. The data set illustrated in FIG. 10 includes the travel speed of each passerby obtained as the first judgment result and the stress level of each passerby obtained as the second judgment result as explanatory variables, and includes the health age of all people present in a specified area as a response variable. Note that, for convenience, FIG. 10 illustrates only the travel speed and stress level of one passerby as explanatory variables, but the travel speed and stress level of the maximum possible number of passersby may be used as explanatory variables.

[0116] Furthermore, when the control unit 11 calculates an index using a learning model that outputs an index from image data of passersby photographed by a camera 30 installed within a specified area, the teacher data 84 used to generate the learning model can have, for example, the image data (or the pixel group constituting it) acquired by the camera 30 as the explanatory variable and the health age of all people present within the specified area as the objective variable. When generating other learning models, a similar learning system can be used with only different algorithms, teacher data, etc.

[0117] <Other embodiments> The health management system according to the above-described embodiment is not limited to the above-described configuration example, and is not limited to the configuration for executing the above-described processing example, as long as it can perform its functions.

[0118] Each of the devices constituting the health management system described in the above embodiment may have the following hardware configuration: Fig. 11 is a diagram showing an example of the hardware configuration included in the device.

[0119] Device 100 shown in Fig. 11 is a device in the health management system according to the above embodiment, and includes a processor 101, a memory 102, and a communication interface (I / F) 103. Processor 101 may be, for example, a CPU, a GPU (Graphics Processing Unit), or an MPU (Micro Processor Unit) also called a microprocessor. Processor 101 may include multiple processors.

[0120] The functions of each part in each device can be realized by processor 101 reading a program stored in memory 102 and executing it in cooperation with communication I / F 103. Note that communication I / F 103 is provided with at least one of a wireless communication I / F and a wired communication I / F depending on the device. In addition, each device can include an I / F with, for example, a sensor, an input / output device, etc., that is necessary depending on the device.

[0121] The above-mentioned program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiments when the program is loaded into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or the tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disk (DVD), Blu-ray® disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes electrical, optical, acoustic, or other forms of propagating signals.

[0122] The present disclosure is not limited to the above-described embodiment, and can be modified as appropriate without departing from the spirit and scope of the present disclosure. In addition, the present disclosure includes implementation in which the examples in the above-described embodiment are appropriately combined. [Explanation of symbols]

[0123] 1, 2, 3 Health Management System 1a 1st judgment part 1b Calculation part 1c Display section 10, 10a Health management device 11 Control section 12 Storage section 12a, 12c Learning Model 12b Person information DB 12d Management System Information 13. Communications Department 20a, 20b, 20 display device 20j, 20k, 20p digital signage 21 Target Management System 30a, 30f Camera (Sensing Zone) 30b, 30c, 30d, 30e Camera 40, 40a, 40b Terminal device 41, 41a, 41b Wearable devices 50 Crosswalk 51, 52, 53, 56, 57, 60, 61 Lanes (Roadways) 54, 55, 58, 59, 62, 63 Sidewalk 64, 65 Pedestrian Bridge 80 Learning System 81 Control Unit 82 Input section 83 Storage section 84 Teacher Data 85 Learning Model 100 devices 101 Processor 102 Memory 103 Communication Interface B1 Bicycle M1 Automobile M2 Autonomous Mobile Vehicle (Autonomous Mobile Bus) U1, U2 users

Claims

1. A first determination unit that determines a state of movement of a pedestrian based on image data of the pedestrian captured by a camera installed within a predetermined area; a calculation unit that calculates an index indicating a population health condition, which is a health condition of all people present in the specified area, based on a result of the determination by the first determination unit; and a display unit that displays the index calculated by the calculation unit; and A health management system comprising:

2. The display unit displays the index calculated for each of the predetermined areas in a ranking format. The health management system according to claim 1 .

3. The display unit includes a display device disposed outdoors in the predetermined area. The health management system according to claim 1 or 2.

4. The first determination unit determines a state of movement of the passerby and determines a health condition of the passerby based on face image data included in the image data. The health management system according to claim 1 or 2.

5. The calculation unit calculates a statistical value of a passing speed of all people present in the predetermined area based on a determination result by the first determination unit, The display unit displays the statistical value as the index or as a part of the index. The health management system according to claim 1 or 2.

6. The calculation unit determines a target value of a traffic speed based on the statistical value, The display unit displays the statistical value and the target value as the index or as a part of the index. The health management system according to claim 5 .

7. a resident determination unit that determines whether the passerby is a resident residing in the specified area based on the image data, and determines an actual age of the resident if the passerby is a resident; the calculation unit calculates a first statistical value which is a statistical value of the difference between the health age and the actual age for all people who exist and reside in the specified area based on the judgment result by the first judgment unit for the residents, calculates a non-resident health age which is the health age for all people who exist but do not reside in the specified area based on the judgment result by the first judgment unit for people other than the residents, and calculates, as the index or part of the index, the statistical value of the difference between the health age and the actual age for all people who exist in the specified area based on the first statistical value and the non-resident health age. The health management system according to claim 1 or 2.

8. an acquisition unit that acquires data to be used for judging a health condition of the passerby from a terminal device carried by the passerby; a second determination unit that determines a health condition of the passerby based on the determined data acquired by the acquisition unit; Equipped with The calculation unit calculates the index based on a determination result by the first determination unit and a determination result by the second determination unit. The health management system according to claim 1 or 2.

9. a generation unit that generates, for each of the predetermined areas, a change instruction for changing predetermined information related to life in the predetermined area based on the index calculated by the calculation unit; The health management system according to claim 1 or 2.

10. The generation unit generates the change instruction for each attribute of a resident residing in the specified area. The health management system according to claim 9.

11. an incentive calculation unit that calculates an incentive to be provided for each of the predetermined areas based on the index calculated by the calculation unit; The health management system according to claim 1 or 2.

12. The computer determines the movement of pedestrians based on image data of the pedestrians captured by cameras installed within a specified area; The computer calculates an index indicating a population health condition, which is the health condition of all people present in the specified area, based on the determination result; The computer controls the display of the calculated index on a display device connected to an external device of the computer or provided in the computer. Health management method.

13. On the computer, A state of movement of a pedestrian is determined based on image data of the pedestrian captured by a camera installed within a predetermined area; Based on the result of the determination, an index showing a population health state, which is the health state of all people present in the specified area, is calculated; The calculated index is displayed on a display device connected to an external device of the computer or provided in the computer. A program for executing a process.

Images