Information analysis device, information analysis method, and program

Abstract

To provide an information analysis device that can identify environmental factors that affect gait. [Solution] The information analysis device comprises: a collection unit that collects gait information showing the measurement results of the gait patterns of multiple pedestrians in a target area; a detection unit that detects the location of periodic disturbances in the time-series data of sensor data included in the gait information; an identification unit that identifies the environmental factors at the location of periodic disturbances in the time-series data of sensor data; and an output unit that outputs information regarding the identified environmental factors.

Description

Technical Field

[0001] The present disclosure relates to an information analysis apparatus, an information analysis method, and a program.

Background Art

[0002] In an aging society, the concept of healthy life expectancy is emphasized. For example, research results have been reported that there is a correlation between the walking speed of the elderly and their remaining life expectancy. Against this background, gait has attracted attention as an indicator for evaluating health. In order to realize a user-friendly city construction, it is important to improve urban infrastructure including road environments that affect people's healthy life expectancy such as gait conditions. For example, there is a service that detects gait conditions using sensors and presents information according to the detected gait conditions.

[0003] Patent Document 1 discloses an electronic device aimed at acquiring information according to a user's behavior state. The device of Patent Document 1 acquires multiple types of sensor information and determines the behavior state of the target person. Based on the determination result, the device of Patent Document 1 selects, as sensor information to be notified to the user, the sensor information corresponding to the determination result among multiple types of sensors.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In the long term, environmental factors such as road deterioration and steep slopes may gradually alter people's gait patterns, potentially increasing the risk of health problems and injuries. While the technology described in Patent Document 1 analyzes the relationship between detected behavioral states and environmental factors, it lacks a perspective that leads to environmental improvement. Comprehensively analyzing gait patterns of local residents and implementing environmental improvements based on this information could potentially improve the health of residents. In other words, it is necessary to identify the environmental factors that affect gait patterns and improve them in order to improve the health of residents.

[0006] The objective is to provide an information analysis device, information analysis method, and program that can identify environmental factors that affect gait. [Means for solving the problem]

[0007] An information analysis device according to one embodiment of the present disclosure includes: a collection unit that collects gait information showing the measurement results of the gait patterns of multiple pedestrians in a target area; a detection unit that detects locations where there are periodic disturbances in the time-series data of sensor data included in the gait information; an identification unit that identifies environmental factors at the locations where there are periodic disturbances in the time-series data of sensor data; and an output unit that outputs information regarding the identified environmental factors.

[0008] In one aspect of this disclosure, a computer collects gait information showing the measurement results of the gait patterns of multiple pedestrians in a target area, detects locations where there are periodic disturbances in the time-series data of sensor data included in the gait information, identifies the environmental factors at the locations where there are periodic disturbances in the time-series data of sensor data, and outputs information regarding the identified environmental factors.

[0009] A program according to one aspect of this disclosure causes a computer to perform the following processes: collect gait information showing the measurement results of the gait patterns of multiple pedestrians in a target area; detect locations where there are periodic disturbances in the time-series data of sensor data included in the gait information; identify environmental factors at the locations where there are periodic disturbances in the time-series data of sensor data; and output information regarding the identified environmental factors. [Effects of the Invention]

[0010] This disclosure makes it possible to provide an information analysis device, an information analysis method, and a program that can identify environmental factors that affect gait. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram illustrating an example of gait information collection by an information analysis device as described in this disclosure. [Figure 2] This is a conceptual diagram showing an example of the arrangement of the measuring device in this disclosure. [Figure 3] This block diagram shows an example of the configuration of the measuring device in this disclosure. [Figure 4] This is a conceptual diagram illustrating an example of gait information transmission in this disclosure. [Figure 5] This block diagram shows an example of the configuration of the information analysis device related to this disclosure. [Figure 6] This is an example of an environmental information table summarizing the environmental information used in this disclosure. [Figure 7] This is a conceptual diagram showing an example of a map of the area covered by this disclosure. [Figure 8] This is a conceptual diagram showing an example of how information on environmental factors is displayed, output from the information analysis device described in this disclosure. [Figure 9] This is a conceptual diagram showing an example of how information on environmental factors is displayed, output from the information analysis device described in this disclosure. [Figure 10] This is a conceptual diagram showing an example of how information on environmental factors is displayed, output from the information analysis device described in this disclosure. [Figure 11] This is a conceptual diagram showing an example of how information on environmental factors is displayed, output from the information analysis device described in this disclosure. [Figure 12] An example of the operation of the information analysis device described in this disclosure will be explained with reference to the drawings. [Figure 13] This is a conceptual diagram illustrating an example of gait information collection by an information analysis device as described in this disclosure. [Figure 14] It is a block diagram showing an example of the configuration of an information analysis device according to the present disclosure. [Figure 15] It is a flowchart showing an example of the operation of the information analysis device in the present disclosure. [Figure 16] It is a block diagram showing an example of the configuration of an information analysis device according to the present disclosure. [Figure 17] It is a conceptual diagram showing an example of the display of proposed information output from the information analysis device in the present disclosure. [Figure 18] It is a conceptual diagram showing an example of the display of proposed information output from the information analysis device in the present disclosure. [Figure 19] It is a conceptual diagram showing an example of the display of proposed information output from the information analysis device in the present disclosure. [Figure 20] It is a conceptual diagram showing an example of the display of proposed information output from the information analysis device in the present disclosure. [Figure 21] It is a conceptual diagram showing an example of the display of proposed information output from the information analysis device in the present disclosure. [Figure 22] It is a conceptual diagram showing an example of the display of proposed information output from the information analysis device in the present disclosure. [Figure 23] It is a conceptual diagram showing an example of the display of proposed information output from the information analysis device in the present disclosure. [Figure 24] It is a flowchart showing an example of the operation of the information analysis device in the present disclosure. [Figure 25] It is a block diagram showing an example of the configuration of an information analysis device according to the present disclosure. [Figure 26] It is a flowchart showing an example of the operation of the information analysis device in the present disclosure. [Figure 27] It is a block diagram showing an example of the hardware configuration for executing control and processing in the present disclosure.

Mode for Carrying Out the Invention

[0012] The embodiments for carrying out this disclosure will be described below with reference to the drawings. In this disclosure, the drawings used in the description of each embodiment are associated with one or more embodiments. Also, the elements included in each drawing may apply to one or more embodiments. The embodiments described below have technically preferred limitations for carrying out this disclosure, but the scope of the disclosure is not limited thereto. In all the drawings used in the description of the embodiments below, the same parts are denoted by the same reference numerals unless there is a specific reason not to. In the embodiments below, repeated descriptions of similar configurations and operations may be omitted. The direction of the arrows in the drawings is an example of the flow of signals, data, etc., and does not limit the flow of signals, data, etc.

[0013] (First Embodiment) First, the information analysis device according to the first embodiment will be described with reference to the drawings. The information analysis device of this embodiment collects gait information of pedestrians walking in a target area. For example, the information analysis device of this embodiment collects gait information using sensors placed on the footwear worn by the pedestrian.

[0014] Furthermore, the information analysis device of this embodiment collects environmental information of the target area. For example, the information analysis device of this embodiment may be configured to collect images and videos taken by surveillance cameras placed in the target area or by in-vehicle cameras mounted on vehicles as gait information and environmental information. For example, the information analysis device of this embodiment may be configured to collect information such as environmental information posted about the target area. The information analysis device of this embodiment uses the collected gait information and environmental information to identify environmental factors that affect gait. Environmental factors that affect gait can also be factors that affect health. For example, the condition and shape of roads can be environmental factors that affect health. Such environmental factors can have sudden or chronic effects. For example, roads with many bumps can have sudden effects such as injuries from falls. For example, roads that are sloped or have many undulations can have chronic effects on the hips, knees, and ankles from daily use. The information analysis device of this embodiment identifies environmental factors that can affect health.

[0015] (composition) Figure 1 is a conceptual diagram illustrating an example of gait information collection by an information analysis device in this disclosure. Figure 1 shows a pedestrian walking in a target area. The pedestrian is wearing shoes 100 equipped with a measuring device 10 that measures sensor data. The measuring device 10 measures physical quantities corresponding to the movement of the pedestrian's feet in accordance with the pedestrian's walking. For example, the measuring device 10 measures sensor data including spatial acceleration and spatial angular velocity. For example, the sensor data may be linked to the pedestrian who performed the measurement. In this case, the sensor data can be used to estimate the health status of the pedestrian according to their gait. For example, the sensor data may not be linked to the pedestrian who performed the measurement. In this case, the pedestrian's personal information is protected.

[0016] The pedestrian is walking while carrying a mobile terminal 170. Sensor data measured by the measuring device 10 is transmitted from the measuring device 10 to the mobile terminal 170. The mobile terminal 170 adds location data to the received sensor data. The mobile terminal 170 transmits the sensor data with added location data (gait information) to the information analysis device 12. For example, the pedestrian's gait may be obtained from images or videos taken by surveillance cameras placed on the street or on-board cameras mounted on vehicles. The configurations of the measuring device 10 and the information analysis device 12 will be described individually below.

[0017] [Measuring device] Figure 2 is a conceptual diagram showing an example of the arrangement of the measuring device in this disclosure. In the example in Figure 2, the measuring device 10 is installed at a position corresponding to the underside of the arch of the foot. For example, the measuring device 10 is placed in an insole inserted into a shoe 100. The measuring device 10 may be installed at a position other than the underside of the arch of the foot, as long as it can measure sensor data related to foot movement. For example, the measuring device 10 may be placed on the bottom surface of the shoe 100. For example, the measuring device 10 may be embedded in the body of the shoe 100. The measuring device 10 may or may not be detachable from the shoe 100. The measuring device 10 may also be installed on the socks worn by the user or on anklets or other ornaments worn by the user. The measuring device 10 may also be directly attached to the foot or embedded in the foot. The measuring device 10 may be placed inside one of the shoes 100 as long as it can measure data that allows for the estimation of the physical state.

[0018] Figure 3 is a block diagram showing an example of the configuration of a measuring device in this disclosure. The measuring device 10 includes a sensor 110, a control unit 113, a communication unit 115, and a power supply 117. The sensor 110 includes an acceleration sensor 111 and an angular velocity sensor 112. The sensor 110 may also include sensors other than the acceleration sensor 111 and the angular velocity sensor 112. A description of sensors other than the acceleration sensor 111 and the angular velocity sensor 112 that may be included in the sensor 110 is omitted.

[0019] The acceleration sensor 111 is a sensor that measures acceleration in three axes (also called spatial acceleration). The acceleration sensor 111 measures spatial acceleration as a physical quantity related to the movement of the foot. The acceleration sensor 111 outputs the measured acceleration to the control unit 113. For example, the acceleration sensor 111 can be a piezoelectric, piezoresistive, or capacitive type sensor. As long as it can measure acceleration, there are no limitations on the type of sensor used as the acceleration sensor 111.

[0020] The angular velocity sensor 112 is a sensor that measures angular velocity (also called spatial angular velocity) around three axes. The angular velocity sensor 112 measures spatial angular velocity as a physical quantity related to the movement of the foot. The angular velocity sensor 112 outputs the measured angular velocity to the control unit 113. For example, the angular velocity sensor 112 can use sensors of the vibration type, capacitive type, etc. There are no limitations on the type of sensor used as the angular velocity sensor 112 as long as it can measure angular velocity.

[0021] Sensor 110 can be implemented, for example, by an inertial measurement device that measures acceleration and angular velocity. An example of an inertial measurement device is an IMU (Inertial Measurement Unit). An IMU includes an acceleration sensor 111 that measures acceleration in three axes and an angular velocity sensor 112 that measures angular velocity around three axes. Sensor 110 may also be implemented by an inertial measurement device such as a VG (Vertical Gyro) or an AHRS (Attitude Heading Reference System). Alternatively, sensor 110 may be implemented by a GPS / INS (Global Positioning System / Inertial Navigation System). Sensor 110 may also be implemented by a device other than an inertial measurement device, as long as it can measure physical quantities related to foot movement.

[0022] The control unit 113 causes the acceleration sensor 111 and the angular velocity sensor 112 to measure sensor data. For example, the control unit 113 causes the acceleration sensor 111 and the angular velocity sensor 112 to start measuring when walking by the user is detected. For example, the control unit 113 starts measuring sensor data starting from the point when movement in the direction of travel is detected for either the left or right foot after the vertical height of both feet has been the same for a predetermined period of time. Alternatively, the control unit 113 may be configured to start measuring sensor data at a predetermined timing that is set in advance. For example, the control unit 113 may be configured to cause the acceleration sensor 111 and the angular velocity sensor 112 to start measuring in response to a measurement start signal transmitted from the information analysis device 12.

[0023] The control unit 113 acquires acceleration in three axes from the acceleration sensor 111. The control unit 113 also acquires angular velocity around the three axes from the angular velocity sensor 112. For example, the control unit 113 performs analog-to-digital conversion (AD conversion) on the acquired physical quantities (analog data) such as angular velocity and acceleration. Note that the physical quantities (analog data) measured by the acceleration sensor 111 and the angular velocity sensor 112 may be converted to digital data by the acceleration sensor 111 and the angular velocity sensor 112, respectively. For example, an AD conversion circuit that performs AD conversion on physical quantities (analog data) such as angular velocity and acceleration may be configured in the measuring device 10. The control unit 113 outputs the converted digital data (also called sensor data) to the communication unit 115. For example, the control unit 113 may be configured to temporarily store the sensor data in a storage unit (not shown).

[0024] The sensor data includes acceleration data and angular velocity data converted into digital data. The acceleration data includes acceleration vectors in the three axes. The angular velocity data includes angular velocity vectors around the three axes. The acquisition time of the acceleration data and angular velocity data is associated with each data set. The control unit 113 may also be configured to apply corrections to the acceleration data and angular velocity data, such as correction for mounting errors, temperature, and linearity.

[0025] For example, the control unit 113 is implemented by a microcomputer or microcontroller that performs overall control and data processing of the measuring device 10. For example, the control unit 113 includes a CPU (Central Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), flash memory, etc.

[0026] The communication unit 115 acquires sensor data from the control unit 113. The communication unit 115 transmits the acquired sensor data to the information analysis device 12. The sensor data transmitted from the communication unit 115 is received by the information analysis device 12. There are no particular limitations on the timing of sensor data transmission. For example, the communication unit 115 transmits sensor data at a preset transmission timing. For example, the communication unit 115 transmits sensor data in real time in response to sensor data measurement. For example, the communication unit 115 may be configured to store sensor data measured over a predetermined period and transmit the stored sensor data all at once at a preset timing. For example, the communication unit 115 may be configured to receive a measurement start signal from the information analysis device 12. In this case, the communication unit 115 outputs the received measurement start signal to the control unit 113.

[0027] The communication unit 115 transmits sensor data to the information analysis device 12 via a predetermined wireless communication method. For example, the communication unit 115 transmits sensor data to the information analysis device 12 via wireless communication (not shown) conforming to standards such as Bluetooth® or WiFi®. The communication of the communication unit 115 may conform to standards other than Bluetooth® or WiFi®. The communication unit 115 may also be configured to transmit sensor data to the information analysis device 12 via wired communication through a cable.

[0028] The power supply 117 is a battery that supplies power for the operation of the measuring device 10. For example, the power supply 117 can be a primary battery such as a lithium primary battery, a silver oxide battery, an alkaline button battery, or a zinc-air battery. For example, the power supply 117 can be a thin battery such as a coin-type or button-type battery. If a primary battery is used, it is preferable that the power supply 117 be a battery with a long lifespan. Alternatively, the power supply 117 may be a rechargeable secondary battery. If a secondary battery is used, the power supply 117 may be a battery that can be charged via a wired connection or a battery that can be wirelessly charged. If the power supply 117 can be wirelessly charged, the wireless power supply device can be placed in a place where footwear is kept, such as an entrance hall or shoe rack. By placing footwear equipped with the measuring device 10 on top of the wireless power supply device, the measuring device 10 can be charged when not in use.

[0029] Figure 4 is a conceptual diagram illustrating an example of gait information transmission in this disclosure. A measuring device 10 is positioned in the shoe 100 worn by the user. In the example in Figure 4, the measuring device 10 is positioned on the underside of the user's arch. Sensor data measured by the measuring device 10 in response to the user's walking is transmitted to a mobile terminal 170 carried by the user. The mobile terminal 170 receives the sensor data transmitted from the measuring device 10. The mobile terminal 170 adds position data to the received sensor data. The position data includes longitude and latitude information corresponding to the position where the sensor data was measured. The mobile terminal 170 transmits the sensor data (gait information) with added position data to an information analysis device 12.

[0030] [Information analysis device] Figure 5 is a block diagram showing an example of the configuration of an information analysis device according to this disclosure. The information analysis device 12 has a collection unit 121, a storage unit 122, a specification unit 125, and an output unit 127. For example, the information analysis device 12 is built on a server or in the cloud.

[0031] The collection unit 121 acquires gait information measured by measuring devices 10 placed on the shoes 100 of multiple users walking in the target area. The gait information includes sensor data and location data of the mobile terminal that transmitted the gait information. The location data of the location where the sensor data was measured is associated with the sensor data. The collected gait information is stored in the storage unit 122.

[0032] The collection unit 121 also collects environmental information of the target area. For example, environmental information may be collected through a Geographic Information System (GIS). Environmental information may also be collected through sensor networks or resident surveys. For example, environmental information may be obtained from images and videos obtained from surveillance cameras, dashcams, satellite images, radar, or lasers. For example, environmental information may be obtained from posts on social networking services (SNS) or word-of-mouth in internet communities. The collected environmental information is stored in the storage unit 122.

[0033] Environmental information includes information that can affect gait patterns. For example, environmental information includes information about the topography, roads, traffic, lighting, urban design, facilities, congestion levels, seasons, and accessibility features of the districts included in the target area. Environmental information related to topography includes information about the gradient of slopes, the presence and number of stairs, and the unevenness of the ground. Environmental information related to roads includes information about the width of sidewalks, the condition of the pavement (smoothness, cracks, unevenness), the status of pedestrian-vehicle separation, and the placement of crosswalks. Environmental information related to traffic includes information about traffic volume, the placement and waiting times of traffic lights, and vehicle speed limits. Environmental information related to lighting includes information about the placement and brightness of streetlights and the amount of shade during the day. Environmental information related to urban design includes information about the density of buildings, the placement of green spaces and parks, and the presence or absence of rest areas such as benches. Environmental information related to facilities includes information about the distance to medical facilities and commercial facilities, and access to public transportation. Environmental information related to congestion includes information about pedestrian traffic volume and congestion levels during specific time periods or dates. Seasonal environmental information includes information on leaf accumulation, snow cover, and freezing conditions. Accessibility information includes information on the installation status of tactile paving and the presence or absence of ramps.

[0034] The memory unit 122 stores gait information and environmental information collected by the collection unit 121. The memory unit 122 also stores a map of the target area, which is a form of environmental information. The map of the target area stored in the memory unit 122 is associated with location-specific environmental information. For example, the environmental information is associated with longitude and latitude. For example, the environmental information is associated with addresses. For example, the environmental information is associated with specific facilities such as commercial facilities, public facilities, medical facilities, educational facilities, entertainment facilities, accommodation facilities, infrastructure-related facilities, and religious facilities. For example, the environmental information is associated with financial institutions, restaurants, factories, warehouses, office buildings, residences, parks, etc.

[0035] Figure 6 shows an example of a table summarizing environmental information in this disclosure (environmental information table). Environmental information table T is a table in which environmental information is associated with each location. Location A is a dimly lit, poorly visible, steep slope with an uneven surface. Location B is a bright, well-visible, slippery staircase. Location C is a busy pedestrian crossing. In these locations, pedestrians exhibit different gait patterns than in normal locations. The health of residents living near these locations may be affected in various ways depending on the changes in gait.

[0036] For example, in a location like position A, changes will appear in stride length, walking speed, leg lift, posture, balance, foot placement, and gaze. To cope with the unstable surface and steep slope, the pedestrian's stride length will decrease. To ensure safety, the pedestrian will walk more slowly than usual. To avoid uneven surfaces, the pedestrian will lift their legs higher. Pedestrians tend to lean forward when going uphill and backward when going downhill. To cope with the unstable surface, the pedestrian will try to maintain balance by spreading their arms or swaying their body from side to side. To cope with slippery surfaces, the pedestrian will try to grip the ground with the entire sole of their foot. To check the condition of the surface, the pedestrian will walk with their head lower than usual.

[0037] The changes in gait described above could have various effects on the health of residents living near location A. Excessive strain on the quadriceps, hamstrings, and calf muscles could lead to muscle fatigue and soreness. Excessive strain on the knee and ankle joints could lead to joint pain and inflammation. Constantly walking in an unstable position could lead to a long-term decline in balance. Unstable surfaces and dim lighting increase the risk of falls. Climbing steep inclines increases heart rate and respiratory rate, putting strain on the cardiopulmonary system. The need to constantly pay attention while walking increases mental stress. Walking in the same environment for extended periods could lead to poor posture, such as hunching or leaning forward. Constantly focusing on the road surface in dim lighting could increase eye strain. Increased energy expenditure compared to normal walking could lead to excessive fatigue. Climbing steep inclines could raise blood pressure, putting strain on the circulatory system. These effects could be particularly serious for the elderly and those with pre-existing health problems.

[0038] For example, in a location like position B, changes appear in stride length, walking speed, foot lift, posture, balance, and foot placement. Pedestrians tend to take shorter strides than usual to match the width of the stairs. Recognizing the risk of slipping, pedestrians walk more slowly and cautiously than usual. Pedestrians need to lift their feet higher to match the height of the stairs. Pedestrians tend to lean forward when going uphill and backward when going downhill. Pedestrians tend to try to lower their center of gravity. To cope with the slipperiness, pedestrians tend to grip the stairs with the entire sole of their foot and carefully land on their toes or heels. Pedestrians try to maintain balance by spreading their arms or swaying their bodies from side to side. Also, to maintain balance, pedestrians actively use handrails whenever possible.

[0039] The changes in gait described above may have various effects on the health of residents living near location B. These include: increased strain on the quadriceps and calf muscles, potentially leading to muscle fatigue and soreness; excessive strain on the knee and ankle joints, potentially causing joint pain and inflammation; increased risk of falls due to slippery surfaces; increased heart rate and respiratory rate when climbing stairs, putting strain on the cardiopulmonary system; increased mental stress due to constant awareness of the risk of slipping; increased eye strain from continuously focusing on stairs despite the bright environment; increased energy expenditure compared to normal walking, potentially leading to fatigue; increased blood pressure when climbing stairs, potentially putting strain on the circulatory system. In the short term, careful walking may improve balance and posture awareness. Also, in the short term, reflexes may be improved to cope with slippery environments. Careful foot movements may improve ankle flexibility. These effects will vary depending on an individual's age, physical fitness, and pre-existing health condition. This could have a significant impact on the elderly and people with pre-existing health problems. In places like location B, it is important to create a safer environment by using non-slip materials on stairs and installing appropriate handrails.

[0040] For example, in a location like position C, changes appear in stride length, walking speed, foot lift, posture, balance, foot placement, and walking rhythm. When pedestrians try to cross a crosswalk in a hurry before the traffic light changes, they lengthen their strides and increase their walking speed. When pedestrians become cautious and wary of vehicle movements, they shorten their strides and decrease their walking speed. Due to tension, pedestrians' shoulders rise, and their overall posture becomes stiff. In preparation for sudden movements or changes of direction, pedestrians tend to grip the ground with the entire sole of their foot and lower their center of gravity. Because they change their pace in response to vehicle movements, pedestrians cannot walk at a constant rhythm.

[0041] The changes in gait described above can have various effects on the health of residents living near location C. The constant need to be aware of one's surroundings can lead to accumulated mental stress and fatigue. Continuous stress can disrupt the balance of the autonomic nervous system. Being constantly on alert can cause tension in the neck, shoulders, and back muscles, potentially leading to fatigue and pain. The physical stress of crossing the pedestrian crossing increases heart rate. Sudden movements increase energy expenditure compared to normal walking. If unnatural postures due to tension become habitual, it can lead to long-term postural deterioration. Rushing and being distracted increases the risk of tripping and falling. These effects may be more pronounced for the elderly and those with pre-existing health problems. At busy pedestrian crossings like location C, measures to ensure pedestrian safety and reduce psychological burden are crucial, including ensuring sufficient crossing time, implementing pedestrian-vehicle separation signals, and installing pedestrian overpasses or underpasses.

[0042] Figure 7 is a conceptual diagram showing an example of a map of the area covered by this disclosure. Environmental information is associated with the locations included in Map M. Map M shows the locations of facilities such as train stations, hospitals, and stadiums in the area covered by Map M. Environmental information as described above is associated with the locations included in Map M.

[0043] The detection unit 123 acquires gait information collected in the target area from the storage unit 122. The detection unit 123 detects the location where a change in gait appears from the time-series data of the sensor data included in the gait information. That is, the detection unit 123 detects the location where the periodicity of the time-series data of the sensor data is disrupted. If the periodicity of the time-series data of the sensor data is disrupted for a single pedestrian, it is presumed that a sudden event occurred. On the other hand, if the periodicity of the time-series data of the sensor data is disrupted at the same location for multiple pedestrians, it is presumed that that location has some kind of characteristic. For example, at locations with changes in the road surface or gradient, or with steps, the periodicity of acceleration and angular velocity included in the sensor data may change rapidly. The detection unit 123 stores the location information of the location where a change in gait appears in the storage unit 122. The detection unit 123 may be configured to store the location information of the location where a change in gait appears in the storage unit 122 in association with the region containing that location.

[0044] The identification unit 125 detects location information for multiple pedestrians where the periodicity of the time-series data of the sensor data is disrupted. The identification unit 125 refers to the environmental information table T stored in the storage unit 122 and identifies the environmental information corresponding to the acquired location. If the environmental information corresponding to the acquired location is recorded in the environmental information table T, the identification unit 125 identifies the environmental information corresponding to that location as an environmental factor. In this case, the identified environmental information corresponds to information about the environmental factor. On the other hand, if the environmental information corresponding to the acquired location is not recorded in the environmental information table T, the identification unit 125 identifies that the environmental factor corresponding to that location is unknown. In this case, the fact that the environmental factor is unknown corresponds to information about the environmental factor.

[0045] Disruptions in the periodicity of the time-series data of sensor data may manifest depending on the weather. Therefore, the specific unit 125 may be configured to detect locations where the periodicity of the time-series data of sensor data is disrupted depending on the weather. For example, locations that are avoided when it rains may be prone to puddles. If this information is notified to local governments and the locations are improved, the number of areas that are difficult to walk in will be reduced. For example, locations that are avoided after it snows may have remaining snow. If this information is notified to local governments and the snow is removed from those locations, the number of areas that are difficult to walk in will be reduced.

[0046] The output unit 127 outputs information related to environmental factors. For example, the output unit 127 outputs an image that visually shows the environmental factors associated with each location on a map of the target area. For example, the information output from the output unit 127 is transmitted to an external system that uses that information. For example, the information output from the output unit 127 is transmitted to the management system of the local government that has jurisdiction over the target area. There are no particular limitations on the use of the information output from the output unit 127.

[0047] [Examples of application] Next, an example of the application of the environmental factors information output from the information analysis device 12 will be explained with reference to the drawings. In this example, information on environmental factors identified based on sensor data acquired in accordance with pedestrian movement in the target area is displayed on the screen of a management terminal of the local government that has jurisdiction over the target area.

[0048] Figure 8 is a conceptual diagram showing an example of the display of information on environmental factors output from the information analysis device in this disclosure. The management terminal 180 is an information processing device (computer) used by the local government. The screen of the management terminal 180 displays an image in which the locations where changes in gait patterns of multiple pedestrians have appeared are superimposed on a map of the target area. By viewing the image displayed on the screen of the management terminal 180, the locations where changes in gait patterns have appeared in the target area can be recognized. For example, the management terminal 180 can be configured to display environmental factors associated with a location where a change in gait patterns has appeared, depending on the selection of that location on the screen.

[0049] Figure 9 is a conceptual diagram showing an example of how information on environmental factors output from the information analysis device in this disclosure is displayed. Figure 9 shows an example where one of the locations where a change in gait was observed was selected. The screen of the management terminal 180 displays information on the environmental factors associated with the selected location. The screen of the management terminal 180 displays the information, "Ten instances of gait changes corresponding to falls were detected on the stone steps of the shrine." Persons in charge who view the information displayed on the screen of the management terminal 180 can recognize the possibility that there is a defect in the condition of the stone steps of the shrine at the selected location.

[0050] Figure 10 is a conceptual diagram showing an example of the display of information on environmental factors output from the information analysis device in this disclosure. The management terminal 180 is an information processing device (computer) used by the local government. The screen of the management terminal 180 displays an image in which areas where changes in gait have been observed for multiple pedestrians are superimposed on a map of the target area. By viewing the image displayed on the screen of the management terminal 180, areas where changes in gait have been observed in the target area can be recognized. For example, the management terminal 180 can be configured to display environmental factors associated with an area where a change in gait has been observed, depending on the selection of that area on the screen.

[0051] Figure 11 is a conceptual diagram showing an example of the display of information on environmental factors output from the information analysis device in this disclosure. Figure 11 shows an example in which one of the regions where a change in gait pattern is observed is selected. The screen of the management terminal 180 displays information on the environmental factors associated with the selected region. The screen of the management terminal 180 displays the information, "At a specific date and time, there have been many instances of a significant decrease in walking speed around the stadium." Personnel who view the information displayed on the screen of the management terminal 180 can recognize the events that occurred in the selected region at a specific date and time.

[0052] (operation) Next, an example of the operation of the information analysis device in this disclosure will be described with reference to the drawings. Figure 12 is a flowchart of an example of the operation of the information analysis device in this disclosure. In the description of the process according to the flowchart in Figure 12, the components of the information analysis device 12 will be considered the operating entities. The operating entity of the process according to the flowchart in Figure 12 may be the information analysis device 12. For example, the process according to the flowchart in Figure 12 is realized by a processor executing a program stored in the memory installed in a computer (not shown) on which the information analysis device 12 is implemented.

[0053] In Figure 12, first, the collection unit 121 collects pedestrian gait information and environmental information of the target area (step S11). The gait information and environmental information may be collected at different times or at the same time. The collected gait information and environmental information are stored in the storage unit 122.

[0054] Next, the detection unit 123 detects a position where there is a disturbance in the periodicity of the time-series data of the sensor data included in the gait information (step S12). For example, the detection unit 123 stores the position information of the detected position in the storage unit 122.

[0055] If a change in gait is observed in a predetermined number of people or more at the detected location (Yes in step S13), the identification unit 125 refers to the environmental information table T stored in the storage unit 122 to identify the environmental factors of the detected location (step S14). The predetermined number of people can be set arbitrarily. If environmental information corresponding to the acquired location is recorded in the environmental information table T, the identification unit 125 identifies the environmental information corresponding to that location as the environmental factor. On the other hand, if environmental information corresponding to the acquired location is not recorded in the environmental information table T, the identification unit 125 identifies that the environmental factors corresponding to that location are unknown. If a change in gait is not observed in a predetermined number of people or more at the detected location (No in step S13), the process in step S12 is repeated.

[0056] Following step S14, the output unit 127 outputs information regarding the identified environmental factors (step S15). For example, the information output from the output unit 127 is transmitted to an external system that uses that information.

[0057] As described above, the information analysis device of this embodiment comprises a collection unit, a storage unit, a detection unit, a specification unit, and an output unit. The collection unit collects gait information showing the measurement results of the gait patterns of multiple pedestrians in a target area. The storage unit stores an environmental information table in which environmental factors are associated with each location included in the target area. The detection unit detects locations where there are periodic disturbances in the time-series data of sensor data included in the gait information. The specification unit refers to the environmental information table and identifies the environmental factors at the locations where there are periodic disturbances in the time-series data of sensor data. The output unit outputs information regarding the identified environmental factors.

[0058] In this embodiment, gait information measured in the target area is collected, and locations with periodic disturbances in the time-series data of sensor data are detected. It is presumed that there are environmental factors that may affect gait at locations where periodic disturbances are detected for multiple pedestrians. In this embodiment, the environmental factors for each location where periodic disturbances are detected are identified by referring to an environmental information table. In other words, according to this embodiment, environmental factors that affect gait can be identified by detecting locations where periodic disturbances are detected for multiple pedestrians.

[0059] In one embodiment of this system, the output unit outputs an image that visually represents environmental factors associated with each location on a map of the target area. For example, the image visually representing environmental factors is displayed on the screen of a management terminal used by the local government. By viewing the image displayed on the management terminal screen, the locations in the target area where changes in gait patterns have occurred can be recognized.

[0060] In one embodiment of this system, the output unit outputs an image that visually represents environmental factors associated with a region that includes each location on a map of the target area. For example, the image visually representing environmental factors is displayed on the screen of a management terminal used by the local government. By viewing the image displayed on the management terminal screen, areas in the target area where changes in gait patterns have occurred can be recognized.

[0061] (Second Embodiment) Next, an information analysis device according to the second embodiment will be described with reference to the drawings. The information analysis device of this embodiment differs from the first embodiment in that it deletes gait information that is influenced by personal factors not included in environmental factors. In this embodiment, an example is given in which personal factors that affect a pedestrian's gait are detected using images and videos captured by a camera that photographs within the range of a target area. Personal factors may be configured to be detected in response to reports from pedestrians.

[0062] (composition) Figure 13 is a conceptual diagram illustrating an example of gait information collection by the information analysis device in this disclosure. Figure 13 shows a pedestrian walking in a target area. The pedestrian is walking while wearing shoes 200 equipped with a measuring device 20 that measures sensor data. The measuring device 20 measures physical quantities corresponding to the movement of the foot in accordance with the pedestrian's walking. For example, the measuring device 20 measures sensor data including spatial acceleration and spatial angular velocity. The sensor data measured by the measuring device 20 is transmitted from the measuring device 20 to a mobile terminal 270. The mobile terminal 270 adds location data to the received sensor data. The mobile terminal 270 transmits the sensor data (gait information) with location data added to it to the information analysis device 22.

[0063] Cameras 290 are placed in the target area. Images and videos captured by cameras 290 include location information of the location where they were captured. For example, camera 290 is a surveillance camera placed on a street. Camera 290 may also be implemented as an in-vehicle camera mounted on a vehicle. Alternatively, camera 290 may be a camera mounted on a portable terminal 270 carried by a pedestrian.

[0064] Pedestrians are walking while carrying a mobile terminal 270. In Figure 13, pedestrians are dragging suitcases, pushing strollers, or carrying large luggage. The sensor data measured in accordance with the pedestrians' movements includes factors different from the environmental factors in the target area. Images and videos captured by the camera 290 are transmitted to the information analysis device 22 as a form of environmental information. The pedestrians' gait patterns may also be obtained from images and videos captured by the camera 290. Below, the measurement device 20 will not be described, and the configuration of the information analysis device 22 will be explained.

[0065] [Information analysis device] Figure 14 is a block diagram showing an example of the configuration of an information analysis device according to this disclosure. The information analysis device 22 has a collection unit 221, a storage unit 222, a specification unit 225, and an output unit 227. For example, the information analysis device 22 is built on a server or in the cloud.

[0066] The data collection unit 221 has the same configuration as the data collection unit 121 in the first embodiment. The data collection unit 221 acquires gait information measured by measuring devices 20 placed on the shoes 200 of multiple users walking in the target area. The gait information includes sensor data and location data of the mobile terminal that is the source of the gait information. The sensor data is associated with location data of the location where the sensor data was measured. The collected gait information is stored in the storage unit 222. The data collection unit 221 also collects environmental information of the target area. The environmental information includes images and videos taken by the camera 290. The images and videos taken by the camera 290 include location information of the location where they were taken. The collected environmental information is stored in the storage unit 222.

[0067] The memory unit 222 has the same configuration as the memory unit 122 of the first embodiment. The memory unit 222 stores gait information and environmental information collected by the collection unit 221. The memory unit 222 stores a map of the target area, which is a form of environmental information. Environmental information for each location is associated with the map of the target area stored in the memory unit 222. The memory unit 222 also stores images and videos captured by the camera 290.

[0068] The detection unit 223 acquires images and videos contained in environmental information collected in the target area. The detection unit 223 detects pedestrians from the acquired images and videos. The detection unit 223 detects individuals who have personal factors that may affect their gait among the detected pedestrians. Individuals with personal factors include people who walk while carrying heavy luggage in one hand, people who walk while pushing a stroller, and people who walk while using a cane. In other words, the detection unit 223 detects individuals whose walking state differs from normal walking in the images and videos. For example, the detection unit 223 uses image recognition technology to detect individuals with personal factors.

[0069] The detection unit 223 deletes gait information affected by individual factors from the storage unit 222. Specifically, when the detection unit 223 detects a person with individual factors, it deletes the sensor data measured at the location where that person was detected from the storage unit 222. The detection unit 223 also deletes sensor data measured during the time period in which a person with individual factors was detected. For example, the detection unit 223 deletes sensor data measured at locations included in images or videos. If a person included in an image or video can be identified, the detection unit 223 deletes the sensor data measured for that identified person. By deleting sensor data measured for a person with individual factors, temporary factors unrelated to environmental factors can be eliminated.

[0070] The detection unit 223 acquires gait information collected in the target area from the storage unit 222. The gait information acquired by the detection unit 223 does not include gait information influenced by individual factors. The detection unit 223 detects the location where a change in gait appears from the time-series data of the sensor data included in the gait information. In other words, the detection unit 223 detects the location where the periodicity of the time-series data of the sensor data is disrupted. If the periodicity of the time-series data of the sensor data is disrupted for a single pedestrian, it is presumed that a sudden event occurred. On the other hand, if the periodicity of the time-series data of the sensor data is disrupted at the same location for multiple pedestrians, it is presumed that that location has some kind of characteristic. For example, at locations with changes in the road surface or gradient, or with steps, the periodicity of acceleration and angular velocity included in the sensor data may change rapidly. The detection unit 223 stores the location information of the location where a change in gait appeared in the storage unit 222. The detection unit 223 may be configured to store location information of the position where a change in gait pattern occurs in the storage unit 222, associating it with the region containing that position.

[0071] The identification unit 225 detects location information for multiple pedestrians where the periodicity of the time-series data of the sensor data is disrupted. The identification unit 225 refers to the environmental information table stored in the storage unit 222 to identify the environmental information corresponding to the acquired location. If the environmental information corresponding to the acquired location is recorded in the environmental information table, the identification unit 225 identifies the environmental information corresponding to that location as an environmental factor. In this case, the identified environmental information corresponds to information about the environmental factor. On the other hand, if the environmental information corresponding to the acquired location is not recorded in the environmental information table, the identification unit 225 identifies that the environmental factor corresponding to that location is unknown. In this case, the fact that the environmental factor is unknown corresponds to information about the environmental factor.

[0072] The output unit 227 outputs information related to environmental factors. For example, the output unit 227 outputs an image that visually shows the environmental factors associated with each location on a map of the target area. For example, the information output from the output unit 227 is transmitted to an external system that uses that information. For example, the information output from the output unit 227 is transmitted to the management system of the local government that has jurisdiction over the target area. There are no particular limitations on the use of the information output from the output unit 227.

[0073] (operation) Next, an example of the operation of the information analysis device in this disclosure will be described with reference to the drawings. Figure 15 is a flowchart showing an example of the operation of the information analysis device in this disclosure. In the explanation of the process according to the flowchart in Figure 15, the components of the information analysis device 22 are considered the main operating entities. The main operating entity of the process according to the flowchart in Figure 15 may be the information analysis device 22. For example, the process according to the flowchart in Figure 15 is realized by a processor executing a program stored in the memory of a computer (not shown) on which the information analysis device 22 is implemented.

[0074] In Figure 15, first, the collection unit 221 collects pedestrian gait information and environmental information of the target area (step S21). The environmental information includes images and videos taken in the target area. The gait information and environmental information may be collected at different times or at the same time. The collected gait information and environmental information are stored in the storage unit 222.

[0075] Next, the detection unit 223 deletes the gait information affected by individual factors from the storage unit 222 (step S22).

[0076] Next, the detection unit 223 detects a position where there is a disturbance in the periodicity of the time-series data of the sensor data included in the gait information (step S23). The gait information at this stage does not include gait information affected by individual factors. For example, the detection unit 223 stores the position information of the detected position in the storage unit 222.

[0077] If a change in gait is observed in a predetermined number of people or more at the detected location (Yes in step S24), the identification unit 225 refers to the environmental information table T stored in the storage unit 222 to identify the environmental factors of the detected location (step S25). The predetermined number of people can be set arbitrarily. If environmental information corresponding to the acquired location is recorded in the environmental information table T, the identification unit 225 identifies the environmental information corresponding to that location as the environmental factor. On the other hand, if environmental information corresponding to the acquired location is not recorded in the environmental information table T, the identification unit 225 identifies that the environmental factors corresponding to that location are unknown. If a change in gait is not observed in a predetermined number of people or more at the detected location (No in step S24), the process in step S23 is repeated.

[0078] Following step S24, the output unit 227 outputs information regarding the identified environmental factors (step S26). For example, the information output from the output unit 227 is transmitted to an external system that uses that information.

[0079] As described above, the information analysis device of this embodiment comprises a collection unit, a storage unit, a detection unit, a specification unit, and an output unit. The collection unit collects gait information showing the measurement results of the gait patterns of multiple pedestrians in a target area. The storage unit stores an environmental information table in which environmental factors are associated with each location included in the target area. The detection unit removes gait information affected by personal factors that are not included in the environmental factors. The detection unit detects locations where there are periodic disturbances in the time-series data of sensor data included in the gait information collected for multiple pedestrians that is not affected by personal factors. The specification unit refers to the environmental information table and identifies the environmental factors at the locations where there are periodic disturbances in the time-series data of sensor data. The output unit outputs information regarding the identified environmental factors.

[0080] In this embodiment, gait information measured in the target area is collected, and gait information influenced by individual factors is removed. In this embodiment, the location of periodic disturbances is detected in the time-series data of sensor data included in the gait information that is not influenced by individual factors. It is presumed that there are environmental factors that may affect gait at the locations where periodic disturbances are detected for multiple pedestrians. In other words, according to this embodiment, environmental factors of environmental origin that are not influenced by the individual factors of pedestrians can be identified.

[0081] (Third embodiment) Next, the information analysis device according to the third embodiment will be described with reference to the drawings. The information analysis device of this embodiment differs from the first and second embodiments in that it generates suggestions according to identified environmental factors. In this embodiment, an example is given in which a new configuration is added to the information analysis device of the first embodiment. The configuration of this embodiment may also be added to the information analysis device of the second embodiment.

[0082] (composition) Figure 16 is a block diagram showing an example of the configuration of an information analysis device according to this disclosure. The information analysis device 32 includes a collection unit 321, a storage unit 322, a specification unit 325, a proposal generation unit 326, and an output unit 327. For example, the information analysis device 32 is built on a server or in the cloud.

[0083] The data collection unit 321 has the same configuration as the data collection unit 121 in the first embodiment. The data collection unit 321 acquires gait information measured by measuring devices placed in the shoes of multiple users walking in the target area. The gait information includes sensor data and location data of the mobile terminal that is the source of the gait information. The sensor data is associated with location data of the location where the sensor data was measured. The collected gait information is stored in the storage unit 322. The data collection unit 321 also collects environmental information of the target area. The environmental information may include images and videos taken by cameras placed in the target area. In that case, the images and videos taken by the cameras include location information of the location where they were taken. The collected environmental information is stored in the storage unit 322.

[0084] The memory unit 322 has the same configuration as the memory unit 122 of the first embodiment. The memory unit 322 stores gait information and environmental information collected by the collection unit 321. The memory unit 322 stores a map of the target area, which is a form of environmental information. Environmental information for each location is associated with the map of the target area stored in the memory unit 322. In addition, the memory unit 322 may store images and videos captured by a camera.

[0085] The detection unit 323 acquires gait information collected in the target area from the storage unit 322. The detection unit 323 detects the location where a change in gait appears from the time-series data of the sensor data included in the gait information. That is, the detection unit 323 detects the location where the periodicity of the time-series data of the sensor data is disrupted. If the periodicity of the time-series data of the sensor data is disrupted for a single pedestrian, it is presumed that a sudden event occurred. On the other hand, if the periodicity of the time-series data of the sensor data is disrupted at the same location for multiple pedestrians, it is presumed that that location has some kind of characteristic. For example, at locations with changes in the road surface or gradient, or with steps, the periodicity of acceleration and angular velocity included in the sensor data may change rapidly. The detection unit 323 stores the location information of the location where the change in gait appears in the storage unit 322. The detection unit 323 may be configured to store the location information of the location where the change in gait appears in the storage unit 322 in association with the region containing that location.

[0086] The identification unit 325 detects location information for multiple pedestrians where the periodicity of the time-series data of the sensor data is disrupted. The identification unit 325 refers to the environmental information table stored in the storage unit 322 to identify the environmental information corresponding to the acquired location. If the environmental information corresponding to the acquired location is recorded in the environmental information table, the identification unit 325 identifies the environmental information corresponding to that location as an environmental factor. In this case, the identified environmental information corresponds to information about the environmental factor. On the other hand, if the environmental information corresponding to the acquired location is not recorded in the environmental information table, the identification unit 325 identifies that the environmental factor corresponding to that location is unknown. In this case, the fact that the environmental factor is unknown corresponds to information about the environmental factor.

[0087] The proposal generation unit 326 generates proposal information corresponding to the identified environmental factors. For example, the proposal generation unit 326 generates proposal information corresponding to environmental factors using a large-scale language model. For example, the proposal generation unit 326 is configured to generate proposal information corresponding to environmental factors using a machine learning model that has been trained to output proposal information in response to environmental factor input. The proposal generation unit 326 accesses the large-scale language model or machine learning model via an interface such as an API (Application Programming Interface). If it is a dedicated large-scale language model or machine learning model, it may be built into the information analysis device.

[0088] The suggestion generation unit 326 may be configured to generate suggestion information tailored to the personal factors of users utilizing the service to which the information analysis device 32 is applied. For example, the user's personal factors can be pre-registered in the application for receiving services using the information analysis device 32. The user's personal factors may be detected from images or videos captured by a camera that photographs the area of ​​the target region. The suggestion information tailored to the personal factors is generated in accordance with the surrounding environmental factors where the user is walking. For example, the suggestion generation unit 326 may generate suggestion information recommending that a user carrying a trunk with wheels walk along a recommended route with minimal unevenness in the road surface.

[0089] The suggestion generation unit 326 may be configured to generate suggestion information tailored to the health status of a user utilizing a service to which the information analysis device 32 is applied. Health status is a form of individual factor. For example, a user's health status can be pre-registered in an application for receiving services utilizing the information analysis device 32. A user's health status may be determined using sensor data measured by a measuring device placed in the user's shoes. Suggestion information tailored to the health status is generated in accordance with the surrounding environmental factors where the user is walking. For example, the suggestion generation unit 326 may generate suggestion information recommending that a user with a foot disability walk along a recommended route with a gentle slope.

[0090] The output unit 327 outputs information about environmental factors, including the generated proposal information. For example, the output unit 327 outputs an image that visually shows the environmental factors associated with each location on a map of the target area. The output unit 327 may also be configured to output only the proposal information. For example, the information output from the output unit 327 is sent to an external system that uses that information. For example, the information output from the output unit 327 is sent to the management system of the local government that has jurisdiction over the target area. There are no particular limitations on the use of the information output from the output unit 327.

[0091] [Examples of application] Next, an example of the application of the environmental factors information output from the information analysis device 32 will be explained with reference to the drawings. In this example, information on environmental factors identified based on sensor data acquired in accordance with pedestrian walking in a target area is displayed on the screen of a management terminal of the local government that has jurisdiction over the target area. The information on environmental factors includes suggested information generated according to the environmental factors. Below, an example is shown in which one of the areas where changes in gait patterns are observed in the target area is selected. The management terminal or mobile terminal screen displays information on environmental factors associated with the selected area.

[0092] Figure 17 is a conceptual diagram showing an example of the display of suggestion information output from the information analysis device in this disclosure. The screen of the management terminal 380 displays information corresponding to environmental factors, stating, "At specific times, there have been many instances of significantly reduced walking speed around the stadium." Personnel who view the information corresponding to environmental factors displayed on the screen of the management terminal 380 can recognize the events that occurred in the selected area at specific times. The screen of the management terminal 380 also displays suggestion information, stating, "We recommend traffic control when specific events are held." The suggestion information displayed on the screen of the management terminal 380 includes suggestions that recommend improving living conditions in the target area while maintaining the current infrastructure. Personnel who view the suggestion information displayed on the screen of the management terminal 380 can recognize that it would be beneficial to focus on traffic control when events are held in this area.

[0093] Figure 18 is a conceptual diagram showing an example of the display of suggested information output from the information analysis device in this disclosure. The screen of the management terminal 380 displays information corresponding to environmental factors, stating, "At specific times, there have been many instances of significantly reduced walking speed around the stadium." Personnel who view the information corresponding to environmental factors displayed on the screen of the management terminal 380 can recognize the events that occurred in the selected area at specific times. The screen of the management terminal 380 also displays suggested information, stating, "We recommend widening the sidewalks around the stadium." The suggested information displayed on the screen of the management terminal 380 includes suggestions to improve the current infrastructure. Personnel who view the suggested information displayed on the screen of the management terminal 380 can recognize that it would be beneficial to improve the infrastructure in this area.

[0094] Figure 19 is a conceptual diagram showing an example of the display of suggestion information output from the information analysis device in this disclosure. The screen of the management terminal 380 displays information corresponding to environmental factors, such as "There have been many incidents of pedestrians falling near the hospital." Personnel who view the information corresponding to environmental factors displayed on the screen of the management terminal 380 can recognize the incidents that occurred in the selected area at a specific date and time. In addition, the screen of the management terminal 380 displays suggestion information such as "We recommend prioritizing improvements over other roads." The suggestion information displayed on the screen of the management terminal 380 includes a suggestion to prioritize improving the infrastructure in this area over other areas. Personnel who view the suggestion information displayed on the screen of the management terminal 380 can recognize that it would be better to prioritize improving the infrastructure in this area over other areas.

[0095] Figure 20 is a conceptual diagram showing an example of the display of suggestion information output from the information analysis device in this disclosure. The screen of the management terminal 380 displays information corresponding to environmental factors, such as "There have been many incidents of pedestrians falling near the hospital." Personnel who view the information corresponding to environmental factors displayed on the screen of the management terminal 380 can recognize the incidents that occurred in the selected area at a specific date and time. In addition, the screen of the management terminal 380 displays suggestion information such as "We recommend improving services such as public transportation and ride-sharing." The suggestion information displayed on the screen of the management terminal 380 includes a suggestion to improve transportation services in this area. Personnel who view the suggestion information displayed on the screen of the management terminal 380 can recognize that it would be better to improve transportation services in this area.

[0096] Figure 21 is a conceptual diagram showing an example of the display of suggestion information output from the information analysis device in this disclosure. The user is walking with a mobile terminal 370. For example, the user's walking speed is measured by a measuring device 30 mounted on the shoes 300 the user is wearing. Assume the user has a slow walking speed and needs to improve their health. For such a user, it is desirable to be advised to walk briskly along an easy route. The screen of the mobile terminal 370 displays suggestion information stating, "For your health, we recommend walking briskly along the recommended route below." The suggestion information displayed on the screen of the mobile terminal 370 includes a suggestion to walk briskly along an easy path. A user who views the suggestion information displayed on the screen of the mobile terminal 370 can recognize that walking briskly along the recommended route is beneficial. For example, the screen of the mobile terminal 370 used by a user with no health problems may be configured to display a recommended route such as walking around a nearby park. With this configuration, municipalities with many residents who don't walk much because their cities are too convenient can guide residents at risk of future frailty due to lack of exercise to engage in appropriate physical activity. For example, by using sensor data measured by a measuring device 30 installed in the shoes 300 worn by the user, it becomes possible to provide an exercise plan that includes an appropriate recommended route tailored to the user's muscle strength, etc.

[0097] Figure 22 is a conceptual diagram showing an example of the display of suggestion information output from the information analysis device in this disclosure. The user carrying the mobile terminal 370 is walking with a cane. For a user walking with a cane, it is difficult to continue walking on a steep road. Therefore, it is desirable for such a user to be recommended a road with less incline. The screen of the mobile terminal 370 displays suggestion information that says, "We recommend that you walk along the following recommended route with less incline." The suggestion information displayed on the screen of the mobile terminal 370 includes a suggestion to walk on a road with less incline. A user who views the suggestion information displayed on the screen of the mobile terminal 370 can recognize that it is better to walk the recommended route.

[0098] Figure 23 is a conceptual diagram showing an example of the display of suggestion information output from the information analysis device in this disclosure. A user carrying a mobile terminal 370 is walking while carrying a trunk equipped with wheels. For a user walking while carrying a trunk, it is difficult to continue walking on a road with many bumps and uneven surfaces. Therefore, it is desirable for such a user to be recommended a road with fewer bumps and uneven surfaces. The suggestion information displayed on the screen of the mobile terminal 370 is displayed as, "We recommend that you walk along the following recommended route with fewer bumps and uneven surfaces." The suggestion information displayed on the screen of the mobile terminal 370 includes a suggestion to walk on a road with fewer bumps and uneven surfaces. A user who views the suggestion information displayed on the screen of the mobile terminal 370 can recognize that it is better to walk the recommended route.

[0099] (operation) Next, an example of the operation of the information analysis device in this disclosure will be described with reference to the drawings. Figure 24 is a flowchart of an example of the operation of the information analysis device in this disclosure. In the description of the process according to the flowchart in Figure 24, the components of the information analysis device 32 are considered the main operating entities. The main operating entity of the process according to the flowchart in Figure 24 may be the information analysis device 32. For example, the process according to the flowchart in Figure 24 is realized by a processor executing a program stored in the memory of a computer (not shown) on which the information analysis device 32 is implemented.

[0100] In Figure 24, first, the collection unit 321 collects pedestrian gait information and environmental information of the target area (step S31). The gait information and environmental information may be collected at different times or at the same time. The collected gait information and environmental information are stored in the storage unit 322.

[0101] Next, the detection unit 323 detects a position where there is a disturbance in the periodicity of the time-series data of the sensor data included in the gait information (step S32). For example, the detection unit 323 stores the position information of the detected position in the storage unit 322.

[0102] If a change in gait is observed in a predetermined number of people or more at the detected location (Yes in step S33), the identification unit 325 refers to the environmental information table stored in the storage unit 322 to identify the environmental factors of the detected location (step S34). The predetermined number of people can be set arbitrarily. If environmental information corresponding to the acquired location is recorded in the environmental information table, the identification unit 325 identifies the environmental information corresponding to that location as the environmental factor. On the other hand, if environmental information corresponding to the acquired location is not recorded in the environmental information table, the identification unit 325 identifies that the environmental factors corresponding to that location are unknown. If a change in gait is not observed in a predetermined number of people or more at the detected location (No in step S33), the process in step S32 is repeated.

[0103] Following step S34, the suggestion generation unit 326 generates suggestion information corresponding to the identified environmental factors (step S35).

[0104] Next, the output unit 327 outputs information about the identified environmental factors and the generated suggestion information (step S36). For example, the information output from the output unit 327 is transmitted to an external system that uses that information.

[0105] As described above, the information analysis device of this embodiment comprises a collection unit, a storage unit, a detection unit, a specification unit, a suggestion generation unit, and an output unit. The collection unit collects gait information showing the measurement results of the gait patterns of multiple pedestrians in a target area. The storage unit stores an environmental information table in which environmental factors are associated with each location included in the target area. The detection unit detects locations where there are periodic disturbances in the time-series data of sensor data included in the gait information. The specification unit refers to the environmental information table and identifies the environmental factors at the locations where there are periodic disturbances in the time-series data of sensor data. The suggestion generation unit generates suggestion information corresponding to the identified environmental factors. The output unit outputs information regarding the identified environmental factors.

[0106] In this embodiment, suggested information is output that corresponds to the identified environmental factors. In other words, according to this embodiment, suggested information can be provided that corresponds to the identified environmental factors. For example, the method of this embodiment can be used by local governments for urban development. For example, it is possible to use the method of this embodiment to collect gait information throughout an entire town and improve infrastructure such as roads according to the health status of residents. By collecting only gait information without linking it to residents' personal information, privacy issues can be resolved. For example, in areas with many inclines, reducing the inclines can reduce the risk of falls for residents. For example, if a town is too convenient and many people do not walk much, there is a possibility that the number of residents who develop frailty will increase in the future. Considering such a situation, it is conceivable that this method could be used to propose the construction of parks and sports facilities that contribute to health improvement according to the health status of residents in each area.

[0107] In one embodiment of this system, the output unit outputs suggestion information corresponding to environmental factors associated with each location on the map of the target area. According to this embodiment, it is possible to provide suggestion information corresponding to environmental factors identified for each location included in the target area.

[0108] In one embodiment of this design, the output unit outputs suggestion information corresponding to environmental factors related to the area including each location on the map of the target area. According to this designation, suggestion information corresponding to environmental factors identified for each area included in the target area can be provided.

[0109] The method of this embodiment can be configured to work in conjunction with ride-sharing or taxi dispatch services. The system can be configured to activate the dispatch service application when signs of fatigue appear in the user's walking or when walking exceeds a pre-set time. For example, the method of this embodiment can also be applied to a service that dispatches an ambulance in response to the detection of a sudden injury.

[0110] The method of this embodiment can also be applied to recommending the purchase of new shoes. For example, a user who walks unsteadily while wearing high heels should be recommended to purchase low heels. For example, a user at high risk of bunions should be recommended to purchase larger shoes. For example, a user who shows signs of instability due to ill-fitting shoes should be recommended to purchase shoes of the appropriate size.

[0111] (Fourth Embodiment) Next, the information analysis device in the fourth embodiment will be described with reference to the drawings. The information analysis device in this embodiment has a simplified configuration compared to the information analysis devices in the first to third embodiments. For example, the functions of the components of the information analysis device in this embodiment are realized by the functions of the components of the information analysis devices in the first to third embodiments.

[0112] (composition) Figure 25 is a block diagram showing an example of the configuration of an information analysis device according to this disclosure. The information analysis device 42 comprises a collection unit 421, a detection unit 423, a identification unit 425, and an output unit 427.

[0113] The collection unit 421 collects gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area. The detection unit 423 detects locations where there are periodic disturbances in the time-series data of sensor data included in the gait information. The identification unit 425 identifies the environmental factors at the locations where there are periodic disturbances in the time-series data of sensor data. The output unit 427 outputs information regarding the identified environmental factors.

[0114] (operation) Figure 26 is a flowchart illustrating an example of the operation of the information analysis device in this disclosure. In describing the process according to the flowchart in Figure 26, the components of the information analysis device 42 will be described as the operating entity. The operating entity of the process according to the flowchart in Figure 26 may also be the information analysis device 42.

[0115] In Figure 26, first, the data collection unit 421 collects gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area (step S41).

[0116] Next, the detection unit 423 detects the location where there is a disturbance in the periodicity of the time-series data of the sensor data included in the gait information (step S42).

[0117] Next, the identification unit 425 identifies the environmental factors at the locations where there is a disturbance in the periodicity of the time-series data of the sensor data (step S43).

[0118] Next, the output unit 427 outputs information regarding the identified environmental factors (step S44).

[0119] In this embodiment, gait information measured in the target area is collected, and locations where periodic disturbances occur in the time-series data of the sensor data are detected. It is presumed that there are environmental factors that can affect gait at locations where periodic disturbances are detected for multiple pedestrians. In other words, according to this embodiment, by detecting locations where periodic disturbances are detected for multiple pedestrians, environmental factors that affect gait can be identified.

[0120] (Hardware) Next, the hardware configuration for performing the control and processing described in this disclosure will be explained with reference to the drawings. Figure 27 is a block diagram showing an example of a hardware configuration for performing the control and processing described in this disclosure. Here, an information processing device 90 (computer) is shown as an example of a hardware configuration. The information processing device in Figure 27 is an example configuration for performing the control and processing described in this disclosure and does not limit the scope of this disclosure.

[0121] As shown in Figure 27, the information processing device 90 comprises a processor 91, memory 92, auxiliary storage device 93, input / output interface 95, and communication interface 96. In Figure 27, interface is abbreviated as I / F (Interface). The information processing device 90 may include at least one or more of the processor 91, memory 92, auxiliary storage device 93, input / output interface 95, and communication interface 96. The processor 91, memory 92, auxiliary storage device 93, input / output interface 95, and communication interface 96 are connected to each other via a bus 98 so that they can communicate data. In addition, the processor 91, memory 92, auxiliary storage device 93, and input / output interface 95 are connected to a network such as the Internet or an intranet via the communication interface 96.

[0122] The processor 91 loads a program (instruction) stored in an auxiliary storage device 93 or the like into memory 92. For example, the program is a software program for executing the control and processing described in this disclosure. The processor 91 executes the program loaded into memory 92. By executing the program, the processor 91 performs the control and processing described in this disclosure. The processor 91 may be composed of a single piece of hardware or multiple pieces of hardware.

[0123] Memory 92 is a storage device having an area where programs are deployed. The processor 91 deploys programs stored in auxiliary storage devices 93, etc., into memory 92. Memory 92 can be implemented using volatile memory such as DRAM (Dynamic Random Access Memory). Alternatively, non-volatile memory such as MRAM (Magnetoresistive Random Access Memory) may be used as memory 92. Memory 92 may be composed of a single piece of hardware or multiple pieces of hardware.

[0124] The auxiliary storage device 93 stores various data, such as programs. For example, the auxiliary storage device 93 can be implemented by a local disk such as a hard disk or flash memory. The auxiliary storage device 93 may be configured by a single piece of hardware or by multiple pieces of hardware. The auxiliary storage device 93 may also be configured as external hardware. It is also possible to configure the system to store various data in memory 92 and omit the auxiliary storage device 93.

[0125] The input / output interface 95 is an interface for connecting the information processing device 90 to peripheral devices based on standards and specifications. The communication interface 96 is an interface for connecting to external systems and devices via a network such as the Internet or an intranet, based on standards and specifications. The input / output interface 95 may be composed of a single piece of hardware or multiple pieces of hardware. The input / output interface 95 and the communication interface 96 may be common as interfaces for connecting to external devices.

[0126] The information processing device 90 may be connected to input devices such as a keyboard, mouse, or touch panel, as needed. These input devices are used to input information and settings. When a touch panel is used as an input device, the screen with touch panel functionality serves as the interface. The processor 91 and the input devices are connected via an input / output interface 95.

[0127] The information processing device 90 may be equipped with a display device for displaying information. If a display device is provided, the information processing device 90 is equipped with a display control device (not shown) for controlling the display of the display device. The information processing device 90 and the display device are connected via an input / output interface 95.

[0128] The information processing device 90 may be equipped with a drive device. The drive device mediates between the processor 91 and the recording medium (program recording medium) by reading data and programs stored on the recording medium and writing the processing results of the information processing device 90 to the recording medium. The information processing device 90 and the drive device are connected via an input / output interface 95.

[0129] The above is an example of a hardware configuration that enables the control and processing described in this disclosure. The hardware configuration in Figure 27 is an example of a hardware configuration that executes the control and processing described in this disclosure, and does not limit the scope of this disclosure. Programs that cause a computer to execute the control and processing described in this disclosure are also included in the scope of this disclosure.

[0130] A program recording medium that stores a program for performing the processing in this embodiment is also included in the scope of the present invention. For example, the program recording medium is a computer-readable, non-transient recording medium. The recording medium can be implemented as an optical recording medium such as a CD (Compact Disc) or DVD (Digital Versatile Disc). The recording medium may also be implemented as a semiconductor recording medium such as a USB (Universal Serial Bus) memory or an SD (Secure Digital) card. Furthermore, the recording medium may be implemented as a magnetic recording medium such as a flexible disk, or other recording media.

[0131] The components in this disclosure may be combined in any way. The components in this disclosure may be implemented by software. The components in this disclosure may be implemented by circuitry.

[0132] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure can be made as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0133] Some or all of the above embodiments may also be described as follows, but are not limited to the following. In the following appendices, the dependents of each category may also be dependent on other categories. The descriptions included in the following appendices are significant as grounds for amendment. (Note 1) A collection unit that collects gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area, A detection unit that detects the location of periodic disturbances in the time-series data of sensor data included in the gait information, A unit for identifying environmental factors at locations where there are periodic disturbances in the time-series data of the aforementioned sensor data, An information analysis device comprising: an output unit that outputs information regarding the identified environmental factors. (Note 2) The specified part is, An information analysis device according to Appendix 1, which identifies the environmental factors at locations where periodic disturbances are detected in the time-series data of the sensor data by referring to an environmental information table to which the environmental factors are associated with each location included in the target area. (Note 3) The detection unit is Remove the gait information that is affected by personal factors not included in the aforementioned environmental factors, An information analysis device according to Appendix 2 for detecting the location of periodic disturbances in the time-series data of sensor data included in the gait information that is not affected by the aforementioned personal factors. (Note 4) The output unit is, An information analysis device according to any one of the appendices 1 to 3 that outputs an image visually showing the environmental factors related to each location on a map of the target area. (Note 5) The output unit is, An information analysis device according to Appendix 4 that outputs an image visually representing the environmental factors related to the area including each location on the map of the target area. (Note 6) An information analysis device according to any one of the appendices 1 to 3, comprising a proposal generation unit that generates proposal information corresponding to the identified environmental factors. (Note 7) The output unit is, An information analysis device according to Appendix 6 that outputs suggested information corresponding to the environmental factors related to each location on the map of the target area. (Note 8) The output unit is, An information analysis device according to Appendix 7 that outputs proposed information corresponding to the environmental factors related to the area including each location on the map of the target area. (Note 9) Computers Gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area was collected. The time-series data of the sensor data included in the gait information is used to detect the location where there is a periodic disturbance. In the time-series data of the aforementioned sensor data, identify the environmental factors at the locations where there are periodic disturbances. An information analysis method that outputs information regarding the identified environmental factors. (Note 10) On the computer, A process for collecting gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area, A process for detecting the location of periodic disturbances in the time-series data of sensor data included in the gait information, A process to identify environmental factors at locations where periodic disturbances occur in the time-series data of the aforementioned sensor data, A program that performs a process to output information about the identified environmental factors. Furthermore, some or all of the configurations described in Appendices 2 to 8, which are subordinate to Appendice 1 above, may also be subordinate to Appendices 9 and 10 in the same way as those described in Appendices 2 to 8. Moreover, not limited to Appendices 1, 9, and 10, some or all of the configurations described as appendices may also be subordinate to various hardware, software, various recording means for recording software, or systems, without departing from the embodiments described above. [Explanation of symbols]

[0134] 10 Measuring devices 12, 22, 32 Information analysis equipment 110 Sensor 111 Accelerometer 112 Angular velocity sensor 113 Control Unit 115 Communications Department 117 Power supply 121, 221, 321 Collection Department 122, 222, 322 storage section 123, 223, 323 Detection Unit 125, 225, 325 Specific part 127, 227, 327 Output section 326 Proposal generation section

Claims

1. A collection unit that collects gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area, A detection unit that detects the location of periodic disturbances in the time-series data of sensor data included in the gait information, A unit for identifying environmental factors at locations where there are periodic disturbances in the time-series data of the aforementioned sensor data, An information analysis device comprising: an output unit that outputs information regarding the identified environmental factors.

2. The specified part is, The information analysis device according to claim 1, which identifies the environmental factors at locations where a disturbance in periodicity is detected in the time-series data of the sensor data by referring to an environmental information table in which the environmental factors are associated with each location included in the target area.

3. The detection unit is Remove the gait information that is affected by personal factors not included in the aforementioned environmental factors, The information analysis device according to claim 2, which detects the location of periodic disturbances in the time-series data of sensor data included in the gait information that is not affected by the aforementioned personal factors.

4. The output unit is, The information analysis device according to any one of claims 1 to 3, which outputs an image visually showing the environmental factors related to each location on a map of the target area.

5. The output unit is, The information analysis device according to claim 4, which outputs an image visually showing the environmental factors related to a region including each location on a map of the target area.

6. The information analysis apparatus according to any one of claims 1 to 3, comprising a suggestion generation unit that generates suggested information corresponding to the identified environmental factors.

7. The output unit is, The information analysis device according to claim 6, which outputs suggested information corresponding to the environmental factors related to each location on the map of the target area.

8. The output unit is, The information analysis device according to claim 7, which outputs suggested information corresponding to the environmental factors related to the area including each location on the map of the target area.

9. Computers Gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area was collected. The time-series data of the sensor data included in the gait information is used to detect the location where there is a periodic disturbance. In the time-series data of the aforementioned sensor data, identify the environmental factors at the locations where there are periodic disturbances. An information analysis method that outputs information regarding the identified environmental factors.

10. On the computer, A process for collecting gait information showing the measurement results of the gait patterns of multiple pedestrians in the target area, A process for detecting the location of periodic disturbances in the time-series data of sensor data included in the gait information, A process to identify environmental factors at locations where periodic disturbances occur in the time-series data of the aforementioned sensor data, A program that performs a process to output information about the identified environmental factors.

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