Database construction device, hazard information providing device, route search device, and information gathering device

Abstract

To provide a database construction device capable of constructing a fall risk map that quantitatively grasps the fall situation.SOLUTION: A database construction device 20 collects at least positional information 12 of a user at each time and information on whether the user has fallen or not 11 from multiple user terminals 10 that each user carries while moving, and constructs the rate of falls for each location on the map as a fall risk map 21, 22.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a fall risk database construction device, a risk information providing device, a route search device, and an information collection device. [Background technology]

[0002] An example of a conventional technique related to preventing pedestrians from falling is Patent Document 1. In Patent Document 1, fixed cameras or vehicle-mounted mobile cameras are placed around dangerous locations where there is a possibility of falling or other dangerous experiences, and alarm speakers are also placed, and when a walking user approaches a dangerous location, the images captured by the cameras are analyzed, and if it is determined that the user is highly likely to fall or other dangerous experiences based on the user's attributes, moving speed, etc., an alarm is issued from the placed speaker or the user's terminal when the user approaches the dangerous location. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2022-32355 Summary of the Invention [Problem to be solved by the invention]

[0004] There is a strong need for fall prevention. For example, as people get older, they are more likely to fall while walking, which can lead to problems such as aftereffects. There is a need to detect roads and places with a high risk of falling in advance and avoid them.

[0005] In contrast, in the conventional technology, it is assumed that dangerous areas can be detected from images as areas with ice or unevenness, and dangerous areas are automatically detected from images using machine learning or the like, or dangerous areas are detected by the operator's visual inspection, but it is not always possible to clearly detect areas where a person may actually fall as areas with ice or unevenness from images. For example, an area without ice or unevenness may not be a problem on a sunny day, but may be a problem on a rainy day even if there are no dangerous areas such as puddles that can be detected in images, and may be particularly problematic for elderly people. For example, there may be dangerous areas where there is no ice, unevenness, or puddles, but the area is inclined and tends to make people fall easily for some reason, but such dangerous areas cannot be found as dangerous areas in the first place with conventional technology that relies on judgment from images. In addition, it is possible to detect inclined areas and make all inclined areas dangerous areas, for example, but this is expected to result in excessive attention and weaken the effect of the attention itself, and is not necessarily effective in preventing falls.

[0006] In other words, conventional technology that identifies dangerous areas based solely on image rules had the problem of being unable to quantitatively grasp the fall situation in a way that takes into account various circumstances, and therefore was not necessarily able to fully meet the need for fall prevention.

[0007] In view of the problems of the above-mentioned conventional technology, a first object of the present invention is to provide a database construction device that constructs a fall risk map that quantitatively grasps the fall situation. A second object of the present invention is to provide an information collection device serving as an individual user terminal that acquires information for the database construction device to collect at the individual user terminal. A third object of the present invention is to provide a danger information provision device serving as an individual user terminal that uses the fall risk map constructed by the database construction device in the individual user terminal. A fourth object of the present invention is to provide a route search device that performs route search using the fall risk map of the database construction device. [Means for solving the problem]

[0008] In order to achieve the first object, the present invention is characterized in that a database construction device collects at least the position information of each user at each time and the information on whether or not the user has fallen from a plurality of user terminals that each user carries while moving, and constructs a fall risk map of the fall rate for each position on a map. In addition, the database construction device further collects fall-related information as the collected information, thereby constructing the fall risk map for each classification of the fall-related information. In order to achieve the second object, the present invention is characterized in that an information collection device as a user terminal that acquires information to be collected by the database construction device at an individual user terminal, acquires information on whether or not a fall has occurred at each time based on the output of an acceleration sensor and / or an angular velocity sensor installed in the information collection device, and then acquires the fall-related information at each time by linking the information on whether or not a fall has occurred with the information on whether or not a fall has occurred. The third feature of the present invention is that the risk information providing device serves as an individual user terminal, which uses a fall risk map constructed by a database construction device in the individual user terminal, and transmits current position information at the current time to the database construction device to obtain information on the fall risk at the current position on the fall risk map and notify the user of the information.The fourth object of the present invention is to provide a route search device that performs a route search that minimizes cost by using a cost based at least on the fall risk in the fall risk map constructed by the database construction device. Effect of the Invention

[0009] According to the first feature, position information at each time and information on the actual occurrence or absence of falls are collected from a plurality of user terminals, and the actual fall rate for each position on the map is constructed as a fall risk map, so that a fall risk map that quantitatively grasps the fall situation can be constructed, thereby achieving the first object. According to the second feature, the second object is achieved by providing an information collection device as a user terminal that acquires information for the database construction device to collect in the individual user terminal. According to the third feature, the third object is achieved by providing a risk assessment device as a user terminal that uses the fall risk map constructed by the database construction device in the individual user terminal. According to the fourth feature, a route search is performed using a cost based at least on the fall risk of the fall risk map, thereby achieving the fourth object. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating a configuration of a fall information utilization system according to an embodiment. [Diagram 2] FIG. 2 is a functional block diagram of components of a fall information utilization system according to one embodiment. [Diagram 3] 3 is a functional block diagram of a first related information acquisition unit and a second related information acquisition unit according to an embodiment. FIG. [Figure 4] 11 is a flowchart illustrating an operation of the fall information utilization system according to one embodiment. [Diagram 5] 11 is a flowchart of an operation of an information collection device according to an embodiment. [Figure 6] 10 is a diagram showing a schematic diagram of a fall information DB to be constructed in a table format. FIG. [Figure 7] 13 is a diagram showing an example in which a fall risk map can be obtained as a heat map according to related information from a fall information DB. [Figure 8] 4 is a flowchart of the operation of a risk assessment device according to an embodiment. [Figure 9] FIG. 1 is a diagram illustrating an example of a hardware configuration of a typical computer. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] FIG. 1 is a diagram showing the configuration of a fall information utilization system 100 according to an embodiment. The fall information utilization system 100 includes terminals 50-k (k=1, 2, ..., N) configured as mobile devices such as smartphones carried and used by each of an unspecified number of N users Uk (k=1, 2, ..., N) moving around in a field F configured as outdoors and / or indoors, and a DB (database) construction device 20. For the sake of explanation, any one of the N people / N devices will be referred to as the terminal 50-k or the user Uk with respect to the users or terminals. In FIG. 1, the terminals 50-k can communicate with each other, and the terminal 50-k and the DB construction device 20 can communicate with each other via a network NW such as the Internet.

[0012] 2 is a functional block diagram of components of a fall information utilization system 100 according to one embodiment. The fall information utilization system 100 includes an information collection device 10, a DB construction device 20, and a danger information provision device 30. Here, the information collection device 10 and the danger information provision device 30 can be realized as a terminal 50-k used by each user Uk. Among the terminals 50-k, there may be one that serves as both the information collection device 10 and the danger information provision device 30, or one that serves as only one of them.

[0013] The information collection device 10 includes a fall detection unit 11 that detects whether or not a fall has occurred, a first positioning unit 12 that obtains positioning information of the information collection device 10 (i.e., positioning information of the terminal 50-k of the user Uk), a first related information collection unit 13 that obtains various related information that may affect whether or not a fall has occurred (weather, attributes, movement, living organisms, population density, etc., as described in detail below), and an information transmission unit 14 that links the information obtained by each of these units 11, 12, 13 as that of the user Uk and transmits it to the DB construction device 20.

[0014] The DB construction device 20 comprises a DB construction unit 21 that constructs a fall map using information about falls transmitted at multiple times from each of the multiple information collecting devices 10, a fall information DB 22 that stores the constructed fall map and transmits information about the fall map to a risk assessment unit 34 of the risk information providing device 30 in response to a request from a request unit 31 of the risk information providing device 30, and a route search unit 23.

[0015] The danger information providing device 30 includes a request unit 31 that requests a fall map from the DB construction device 20, a second positioning unit 32 that obtains positioning information of the danger information providing device 30 (i.e., positioning information of the terminal 50-k of the user Uk), a second related information collecting unit 33 that obtains various related information that may affect the occurrence or absence of a fall (weather, attributes, movement, living body, population density, etc., as will be described in detail later), a risk evaluation unit 34 that refers to the fall map transmitted from the fall information DB 22 of the DB construction device 20 in response to the request of the request unit 31 and obtains an evaluation result of the risk of falling at the current position of the user Uk of the terminal 50-k (danger information providing device 30) by using the information obtained by the second positioning unit 32 and the second related information acquiring unit 33, and a display unit 35. When it is determined that the risk of falling is high, the risk evaluation unit 34 can notify the user Uk using the terminal 50-k of the risk of falling by outputting an alert using voice or the like.

[0016] 2 illustrates only one information collecting device 10 and one danger information providing device 30, this is illustrated as any one of a large number of information collecting devices 10 and danger information providing devices 30. That is, as described with reference to FIG. 1, each of the terminals 50-k of each of the unspecified large number N users Uk can play the role of the information collecting device 10 and the danger information providing device 30 (or either one of them).

[0017] 3 is a functional block diagram of the first related information acquisition unit 13 and the second related information acquisition unit 33 according to an embodiment. As can be understood from the fact that the names are formally divided into first and second and the corresponding reference numerals 131 to 136 / 331 to 336 are attached to the drawings, the related information acquired by the first related information acquisition unit 13 and the second related information acquisition unit 33 is common, but is used in different ways. That is, the first / second weather information acquisition unit 131 / 331 acquires weather information, the first / second attribute information acquisition unit 132, 332 acquires attribute information, the first / second movement information acquisition unit 133 / 333 acquires movement information, the first / second biometric information acquisition unit 134 / 334 acquires biometric information, the first / second ground information acquisition unit 135 / 335 acquires ground information, and the first / second population density information acquisition unit 136 / 336 acquires population density information, as information related to the information collecting device 10 / the danger information providing device 30, respectively.

[0018] The related information acquired by the first related information acquisition unit 13 is used to construct a fall map, specifically in step S1 of Fig. 4, which will be described later. The related information acquired by the second related information acquisition unit 33 is used to actually evaluate the risk of falling using the constructed fall map, specifically in step S3 of Fig. 4, which will be described later.

[0019] 4 is a flowchart of the operation of the fall information utilization system 100 according to one embodiment. In step S1, information on falls is collected over a certain period of time in a plurality of information collection devices 10 (terminals 50-k of a plurality of users Uk). In step S2, the DB construction device 20 constructs a fall information DB 22 using the information collected in step S1. In step S3, the fall information DB 22 constructed in step S2 is referenced, and the terminal 50-k used by a specific user Uk who is moving functions as a danger information provision device 30 to evaluate the risk of a fall for that user Uk.

[0020] The evaluation of the risk of falling in step S3 is not limited to being performed once, but can be performed continuously for each of a large number of users Uk for a period desired by that user Uk.

[0021] FIG. 5 is a flowchart of the operation of the information collection device 10 according to an embodiment, showing a detailed example of step S1 in FIG.

[0022] In step S11, in the information collection device 10 carried as the terminal 50-k and moving with the user Uk in any field F (for example, indoors such as a shopping mall and / or outdoors such as a street corner) where the user Uk can move around by walking, etc., the fall detection unit 11, the first positioning unit 12 and the first related information acquisition unit 13 are started to operate, and each starts to acquire whether or not a fall has occurred, location information and related information.

[0023] In step S12, it is determined whether or not a fall has occurred at the current time t. If a fall has occurred, the process proceeds to step S14 to record that a fall has occurred, and if a fall has not occurred, the process proceeds to step S13.

[0024] Here, when the fall detection unit 11 detects that a fall has occurred at the current time t, it can determine whether a fall has occurred in step S12. The fall detection unit 11 monitors in real time the acceleration data and / or angular velocity data (referred to as "motion data") output as time-series data by the acceleration sensor and / or angular velocity sensor installed in the information collection device 10 (the terminal 50-k of the user Uk), and determines whether the behavior of the motion data for a certain period immediately prior to the current time t (for example, 5 seconds up to the current time t) indicates a fall of the user Uk, thereby determining whether a fall has occurred.

[0025] Any existing method may be used as a method for determining whether or not a fall has occurred from movement data over a certain period of time. For example, a large amount of movement data over a certain period of time, both when there have been falls and when there have not been falls, can be prepared as learning data, and the determination can be made using a model trained by machine learning or deep learning using the learning data.

[0026] In step S13 (in the case of no fall), it is determined whether the current time t corresponds to the timing for recording information about no fall, and if so, the process proceeds to step S14 to record that there was no fall, and if not, the process proceeds to step S15 to omit recording at the current time t.

[0027] The information recording timing in step S13 may be determined based on whether the current time t corresponds to the time of information recording timing at regular intervals (for example, every 5 seconds), or based on whether the difference (distance) between the position information p(tn) at the immediately previous time (past time tn where n>0) when proceeding to step S14 and information recording is performed and the current position information p(t) exceeds a threshold. Here, the position information p(tn) and p(t) used are those acquired by the first positioning unit 12. Alternatively, the fall map constructed by the fall information DB 22 may be classified into different location sections in advance, and the time when the current position information p(t) switches from one location section to another adjacent location section as the user Uk moves may be determined as the information recording timing.

[0028] In step S14, the presence or absence of a fall at the current time t (if the process goes from step S12 to step S14, a fall has occurred, and if the process goes from step S13 to step S14, no fall has occurred), the position information p(t) acquired by the first positioning unit 12 at the current time t, and the related information acquired by the first related information acquisition unit 13 at the current time t are linked as information for the user Uk at time t, and are transmitted from the information transmission unit 14 to the DB construction unit 21. Details of this information will be described later with reference to FIG.

[0029] In step S15, the current time t is switched to the next time t+1, and the process returns to step S12. Note that step S15 controls the processing rate (such as the frame rate in the case of video) when repeating the flow of Fig. 5, and the processing rate may be set to a predetermined rate (e.g., every second) according to the available computational resources and network resources.

[0030] 5, in step S14, instead of transmitting information from the information transmitting unit 14 to the DB constructing unit 21 every time step S14 is reached, information may be transmitted in a lump after a certain amount of information is accumulated in the information collecting device 10. For example, information collected in one day may be transmitted in a lump at night when it is known that the user who uses the information collecting device 10 has returned home and is not moving around.

[0031] According to the flow of Fig. 5, the DB construction unit 21 consolidates information collected over a certain period of time by a large number of information collecting devices 10, and the fall information DB 22 can be constructed. Fig. 6 is a diagram showing the constructed fall information DB in a table format. Column C1 is the date and time when information was acquired by the user terminal 50-k (information collecting device 10), and column C2 is the presence or absence of a fall at that date and time. Note that in the example of Fig. 6, data D1 when a fall occurred and data D2 when no fall occurred are sorted and distinguished, but this is for the purpose of explanation, and the method of recording may be arbitrary.

[0032] Columns C3, C4, and C5 are examples of user attribute information related to falls acquired by the first attribute information acquisition unit 132. The first attribute information acquisition unit 132 can acquire information such as age group (user age category) such as 30s, 40s, and 50s as in column C3, gender as in column C4, and other attributes that may affect falls (for example, the presence or absence of motor disabilities or sensory disabilities such as visual / hearing disabilities) as in column C5.

[0033] In addition, since the user attributes acquired by the first attribute acquisition unit 132 do not change from moment to moment at each time t=1, 2, ... in real time while the user is walking, it is sufficient to use the information input by the user in advance in a fixed manner.

[0034] Columns C6 and C7 are examples of movement information acquired by the first movement information acquisition unit 133, and as the movement mode as shown in column C6, a classification of movement speed (for example, walking / running in two stages of slow / fast) and a movement direction as shown in column C7 (movement direction in north-south, east-west on map information) may be acquired by the first movement information acquisition unit 133. Note that the first movement information acquisition unit 133 can acquire such movement information as information on the speed by referring to the history of position information p(t) on the map information acquired by the first positioning unit 12 at each time t=1, 2, ... in real time.

[0035] In columns C8 and C9, examples of location information acquired by the first positioning unit 12 are shown in the form of longitude and latitude as location information on a map. The first positioning unit 12 can acquire location information by performing location acquisition of the information collecting device 10 (terminal 50-k) using any existing method such as (outdoor) GPS (Global Positioning System), indoor GPS using strength information of a beacon signal from a Wifi (registered trademark) access point whose installation position is known, or a combination of these.

[0036] In the field C10, examples of weather information at the time t acquired by the first weather information acquisition unit 131 are shown as sunny, cloudy, rainy, etc., and the acquired weather information may include not only the weather but also temperature, amount of rainfall, amount of snowfall, and the presence or absence of thunder. The first weather information acquisition unit 131 may acquire the location information acquired by the first positioning unit 12 and the weather information at the time t by accessing via the network NW a separate server (not shown) that manages the weather information and provides a weather information service.

[0037] In the field C11, examples of bioinformation acquired by the first bioinformation acquisition unit 134 are shown as judgment results at a predetermined stage, for example, as being classified as good, normal, or poor condition in three stages. The first bioinformation acquisition unit 134 can acquire the bioinformation of the user Uk at the time t by analyzing the output of any combination of existing biosensors such as a heart rate sensor, a blood flow sensor, a body temperature sensor, and a sweat sensor worn by the user Uk using a model that has been learned in advance.

[0038] In the field C12, examples of ground information acquired by the first ground information acquisition unit 135 are shown as information on the shape and / or slope of the ground (the road surface if it is a road) on which the user Uk walks or runs, and which is classified as a specific category such as flat, uneven, slope, etc. (for example, "flat that is a slope that is not a horizontal plane and has no unevenness" or "slope and unevenness"). Such ground information can be obtained by accessing via the network NW a separate server (not shown) that manages the ground information in association with the position information of the map information, and acquiring the ground information of the location that corresponds to the position information acquired by the first positioning unit 12 at the time t.

[0039] In the field C13, examples of population densities acquired by the first population density acquisition unit 136 are shown as a predetermined level, for example, three levels of high, medium, and low (the location is congested, has an average degree of congestion, and is not congested and is empty). Regarding such population densities, a separate server (not shown) that manages the population density information in association with the location information of the map information is accessed via the network NW, and the population density of the location corresponding to the location information acquired by the first positioning unit 12 at the time t can be acquired.

[0040] The DB construction unit 21 compiles the fall information DB22, whose elementary contents are exemplified in FIG. 6 described above, according to the specified related information for each position on the map or for each map range that is previously divided into grids or the like, and can construct the fall information DB22 as a "fall hazard map," so to speak, in the form of a heat map that maps the degree of fall risk as diagrammatically shown in FIG. 7, as information on the occurrence of falls within that map range.

[0041] 7 is a diagram showing an example in which a fall risk map can be obtained as a heat map according to related information from the fall information DB 22. In example EX1, the presence or absence of falls in a specified related information (assumed to be α) in a grid-like map range d1 to d5 is shown by plotting the positions where falls occurred with black circles (●) and the positions where no falls occurred with white circles (○), and example EX2 shows the fall risk map of the related information α of example EX1 in the form of a heat map. In example EX2, the darker the color, closer to black, the higher the risk of falling, and the lighter the color, closer to white, the lower the risk of falling.

[0042] In examples EX3 and EX4, in a common map range d1 to d5, a fall occurrence / absence plot in a specified separate related information (assumed to be β) and a corresponding fall risk map are shown in a similar format.

[0043] According to this embodiment, a fall risk map corresponding to the specified related information can be obtained in the form of a heat map, as exemplified in Fig. 7. For example, with attribute α="age group is in the 60s" and attribute β="age group is in the 50s" as related information, information can be obtained that for the age group in the 60s, the range d3 has a "high" fall risk, the range d5 has a "medium" fall risk, and the other locations d1, d2, and d4 have a "low" fall risk, and information can be obtained that for the age group in the 50s, the range d3 has a "medium" fall risk, and the other locations d1, d2, d4, and d5 have a "low" fall risk.

[0044] That is, location d3 is dangerous for both ages 60 and 50, but is especially dangerous for people in their 60s. This makes it possible to obtain precise map information of the degree of risk of falling according to detailed related information.

[0045] In addition, as to which related information the DB construction unit 21 will create a fall risk map for, any designation can be made for all or part of the various related information acquired by the first related information acquisition unit 13. For example, attribute information acquired by the first attribute information acquisition unit 132, such as gender or age, may not be designated, and only weather information acquired by the first weather information acquisition unit 131 may be designated. For example, examples EX1 and EX2 in FIG. 7 are for the case where the related information is weather α="rain" and correspond to more dangerous cases, and examples EX3 and EX4 are for the case where the weather β="sunny" and correspond to less dangerous cases.

[0046] That is, in this embodiment, on the premise that a sufficient amount of information is collected by the information collecting device 10, detailed information can be obtained based on the actual presence or absence of falls in the past about how the fall risk varies depending on the weather, attribute, movement, biological information, ground information, and population density even at the same location on the map, by using meteorological information, attribute information, movement, biological information, ground information, and population density (using all or any part of each of these pieces of information) as related information. Also, from the standpoint of a user Uk who uses his / her own terminal 50-k as the danger information providing device 30, precise information on the fall risk can be obtained that reflects the actual presence or absence of falls in the related information (weather information, attribute information, movement information, biological information, ground information, and population density) that actually applies to the user Uk, and measures can be taken to prevent falls by paying attention in advance when the risk is high.

[0047] FIG. 8 is a flowchart of the operation of the danger information providing device 30 according to an embodiment, showing a detailed example of step S3 in FIG.

[0048] In step S31, in the danger information providing device 30 carried as its terminal 50-k and moving with the user Uk in any field F (for example, indoors such as a shopping mall and / or outdoors such as a street corner) where the user Uk can move around by walking, etc., the second positioning unit 32 and the second related information acquisition unit 33 are started to operate, and acquisition of location information and related information is started.

[0049] Here, the process of acquiring the location information of the second positioning unit 32 is common to the process of the first positioning unit 11, and the location information p(t) of the danger information providing device 30 as the terminal 50-k can be acquired in real time at each time t=1, 2, ... by any existing method such as outdoor GPS and / or indoor GPS.

[0050] 3, the related information acquired by each of the units 331-336 of the second related information acquisition unit 33 is the same as that acquired by each of the units 131-136 of the first related information acquisition unit 13, and related information in the danger information providing device 30 as the terminal 50-k can be acquired. (Therefore, duplicated explanations will be omitted.) For example, the second attribute information acquisition unit 332 acquires attribute information such as the age of the user Uk, but since this does not change in real time at each time t=1, 2, ..., it is sufficient to use the attribute information that the user Uk inputted as his / her own information only once at the beginning in a fixed manner.

[0051] In step S32, it is determined whether the current time t is the timing for risk assessment processing, and if it is, proceed to step S33 to perform risk assessment at the current time t, and if it is not the timing, proceed to step S34 to omit risk assessment at the current time t.

[0052] The determination in step S32 may be made, similarly to step S13 in FIG. 5, by determining whether the current time t corresponds to a predetermined processing timing (for example, every 5 seconds), whether the distance between the position information p(tn) at the time when the risk was assessed at the most recent past time tn (n>0) obtained by the second positioning unit 32 and the current position information p(t) is greater than or equal to a threshold value, and by determining in advance by distinguishing between location sections in the fall map whether the current position information p(t) corresponds to a point in time when the user Uk has moved and switched from one location section to another adjacent location section.

[0053] The reason why the decision not to perform a fall risk assessment in step S32 is to prevent unnecessary strain on computational resources and network resources due to the interval for risk assessment being excessively shorter than an interval that is sufficiently short to enable advance notification of risk. Therefore, the judgment threshold value, etc. of step S32 may be set in advance so that the notification of the risk of falling is performed at an appropriate timing that is neither too short nor too long.

[0054] In step S33, the request unit 31 transmits the position information p(t) of the second positioning unit 32 at the current time t and the related information of the second related information acquisition unit 33 to the fall information DB 22, and the fall information DB 22 transmits the position information p(t) at the current time t and fall map information corresponding to the specified related information (as described in Figure 7, in the form of a heat map, in which the fall risk is given in three levels, for example, high, medium, and low) to the risk assessment unit 34, and presents this fall risk information to the user Uk.

[0055] In addition, if the risk of falling is determined to be high and exceeds a threshold value (for example, if it falls under high or medium out of three levels of high, medium, and low), the risk assessment unit 34 may notify the user Uk that there is a risk of falling at the current time t by any method such as displaying a screen, turning on a light, outputting a warning voice, or activating a vibrator.

[0056] In step S33, not only the fall map information for only one location, namely, position p(t) at the current time t, but also the fall map information for a specified range around the position p(t) (for example, a range of a radius of 100 m centered on the position p(t)) may be transmitted in heat map format to the risk assessment device 50, so that the user may view the fall map in heat map format for position p(t) and his / her surroundings on the display unit 35 composed of a display or the like.

[0057] When viewing in the heat map format, it is possible to accept a user's instruction to modify the related information and switch to a map for different related information for viewing, rather than viewing only the map corresponding to the related information at the current time t acquired by the second related information acquisition unit 33. For example, when weather is used as related information, the weather at the current time t is sunny, and the user initially views a map for sunny weather, but upon receiving a request from the user to view a map for rainy weather, the map may be switched to the map for rainy weather for the user to view.

[0058] In step S34, the current time t is updated to the next time t+1, and then the process returns to step S32. The significance of step S34 is the same as that of step S15 in Fig. 5, and step S34 is for managing the processing rate (for example, every second) of the danger information providing device 30.

[0059] As described above, as a modified example of the flow of FIG. 5, in step S33, rather than transmitting position information p(t) for the current time t and related information to the fall information DB 22 each time at the relevant time t to obtain the relevant fall risk information, information on a fall risk map covering the range of position information p(t) predicted in advance (for example, when used in conjunction with a route guidance service that obtains route information from the current location to the destination by specifying the current location and destination, where the range of the user's travel route is clear from map information) and the range of related information may be stored (as a cache) in the danger information providing device 30, and the fall risk map as the cache may be compared with information on the current time t of the second positioning unit 32 and the second related information 33 to obtain information on the fall risk at the current time t.

[0060] When used in conjunction with a route guidance service (i.e., when not only route information but also fall risk information is provided to a user who is in the middle of receiving route guidance information provided by any existing technology), for example, if the fall risk is determined to be low at the current time t (and a notification to that effect is also given to the user from the risk assessment unit 34), but the user Uk is expected to be in a place with a high fall risk at a future time t+n after a certain time n>0, the risk assessment unit 34 may evaluate the future fall risk in advance and notify the user. Here, any existing method may be used for the route search algorithm and route designation interface in the route guidance service, and these processes may be handled by a separate server (not shown).

[0061] In addition, as a request separate from or in addition to the request for provision of a fall map or fall risk received from the request unit 31, the route search unit 23 may accept a request for route search from the user, notify the user of the results of the route search, and display the route information on a map on the display unit 35 together with the user's current location (which may be the current location and its fall risk).

[0062] The route search unit 23 can search for a route with the minimum cost using any existing method, for example, Dijkstra's algorithm. As is known, the nodes of a graph structure are each position on a map, and the edges connecting the nodes are (element) routes, and route search can be performed using Dijkstra's algorithm or the like to minimize the sum of the costs of each edge constituting the entire route. Here, in addition to the cost based on the required time and distance used in the existing method, the present embodiment further uses the fall risk in the heat map for each related information in the fall information DB 22 as the cost as the route cost, thereby making it possible to guide the user to a route that not only has a short required time, etc., but also has a low fall risk with respect to a route that the user can walk or run on his / her own feet. That is, the route search unit 23 accepts designation of the current position, destination position, and related information from the user, obtains a heat map according to the related information from the DB construction device 20, refers to the cost based on falls on each route (the higher the risk of falling, the lower the cost), and takes into consideration other given costs based on the required time, etc., and then notifies the user of the route search results from the current position to the destination position. The cost of the fall risk for each route may be set as the average value or representative value of the heat map of the fall risk on the route area.

[0063] In addition, in FIG. 2, the route search unit 23 is included in the DB construction device 20, but the route search unit 23 (route search device) may be provided as a server device or the like separate from the DB construction device 20.

[0064] Regarding the designation of the related information used in step S33, among the related information of the original data in the fall information DB22 (before it is compiled into a fall severity risk map), a common time stamp (date and time information, the date and time in column C1 in the example of Figure 6) is linked to everything other than the attribute information and ground surface information. Therefore, although it is not explicitly shown as a functional block in Figure 3, information for distinguishing the date and time information based on all or part of the time period (for example, morning, night, or daytime), day of the week (Monday to Sunday, weekend or other, holiday or other), season, and which month in December the current month is may be designated as the related information.

[0065] By designating this information as related information, it becomes possible to use information from the fall risk map in a way that reflects, for example, that the risk of falling is higher at night, or that the risk of falling is higher on holidays than on weekdays, even for locations on the same map.

[0066] Various supplementary examples, alternative examples, additional examples, etc. will be described below with respect to the embodiments of the present invention.

[0067] (1) According to an embodiment of the present invention, a fall risk map can be used to collect and utilize information on actual falls that have occurred in the past, thereby preventing falls in similar circumstances from continuing to occur in the future, thereby contributing to preventing injuries and disabilities caused by falls. This can contribute to Goal 3 of the United Nations-led Sustainable Development Goals (SDGs) "Ensure healthy lives and promote well-being for all at all ages."

[0068] (2) The first related information acquisition unit 13 and the second related information acquisition unit 33 are configured to acquire all or part of the weather, attributes, movement, living body, ground surface, and population density as related information related to falls, but if the related information can be considered constant in the intended use, or if there is a distinction but it does not affect whether a fall has occurred, the related information may not be acquired. In this case, the first related information acquisition unit 13 and the second related information acquisition unit 33 are omitted from the fall information utilization system 100, and a fall risk map that is commonly used by all users and in all weather conditions is constructed based only on the position information at each time and the information on whether a fall has occurred, and the fall risk can be evaluated by referring to this map.

[0069] (3) For locations on the map where it is determined that there is insufficient information collection regarding the occurrence of falls (for example, locations where the amount of data on the occurrence of falls obtained at that location within a certain period of time is less than a threshold value, referred to as "missing locations"), on the assumption that sufficient information on the occurrence of falls has not been collected at the missing locations, but ground information and / or population density information can be referenced by accessing a separate server, etc., the risk assessment in step S3 may be performed using information on the risk of falls from other locations where it is determined that the ground information and / or population density is similar, and where there is information on the occurrence of falls but is not a missing location and where fall risk map information has been obtained.

[0070] The similarity of ground information and / or population density can be determined using any evaluation index (such as the distance between vectors) that evaluates the similarity between the two variables (or one variable if one of the variables is selected), and the value of the fall risk map for one of the most similar locations can be used. If there are multiple locations that are determined to have high similarity, the fall risk value can be estimated as a weighted sum of these top locations.

[0071] (4) Fig. 9 is a diagram showing an example of a hardware configuration in a general computer. Each of the information collecting device 10, the DB construction device 20, and the danger information providing device 30 can be realized as one or more computer devices 70 having such a configuration. When each of the information collecting device 10, the DB construction device 20, and the danger information providing device 30 is realized by two or more computer devices 70, information required for processing may be transmitted and received via a network. The computer device 70 comprises a CPU (central processing unit) 71 that executes predetermined instructions, a GPU (graphics processing unit) 72 as a dedicated processor that executes some or all of the instructions executed by the CPU 71 in place of or in cooperation with the CPU 71, a RAM 73 as a main storage device (memory) that provides a work area for the CPU 71 (and GPU 72), a ROM 74 as an auxiliary storage device (storage), a communications interface 75, a display 76, an input interface 77 that accepts user input via a mouse, keyboard, touch panel, etc., a camera 81, a speaker 82, a light 83, a vibration element 84, a position sensor 85, and a bus BS for transmitting and receiving data between these.

[0072] Each functional unit of the information collecting device 10, the DB construction device 20, and the danger information providing device 30 can be realized by a CPU 71 and / or a GPU 72 that reads a predetermined program corresponding to the function of each unit from a ROM 74 and executes it. Both the CPU 71 and the GPU 72 are a type of arithmetic device (processor). Here, when display-related processing is performed, a display 76 also operates in conjunction with the GPU 72, and when communication-related processing related to data transmission and reception is performed, a communication interface 75 also operates in conjunction with the GPU 72.

[0073] The first positioning unit 12 and the second positioning unit 32 can obtain position information, which is a positioning result, by using an output from a position sensor 85 that can perform any positioning by outdoor and / or indoor GPS, etc. When the risk assessment unit 34 notifies the user that there is a risk of falling, the notification may be made visually by displaying on the display 76 or turning on the light 83, or may be made audibly by using the speaker 82, or may be made audibly and / or tactilely by using a vibration element 84 composed of a vibrator, etc., as a notification by vibration generation. The risk assessment unit 34 may change the notification method depending on whether there is a risk of falling or not. When there is no risk of falling, an output composed of contents different from those when there is a risk of falling may be made, or the user may be informed in advance that no output from the speaker 82, the light 83, or the vibration element 84 indicates that there is no risk of falling, and the notification of no risk of falling may be realized by not outputting the output. The display unit 35 that displays the fall risk map, the current position, and the searched route may be realized as display processing in the display 76. [Explanation of symbols]

[0074] 100... fall information utilization system, 10... information collection device (50-k... user terminal), 20... DB construction device, 30... danger information provision device (50-k... user terminal), 11... fall detection unit, 12... first positioning unit, 13... first related information acquisition unit, 14... information transmission unit, 21... DB construction unit, 22... fall information DB, 23... route search unit (route search device), 31... request unit, 32... second positioning unit, 33... second related information acquisition unit, 34... danger assessment unit, 35... display unit 131,332...first and second meteorological information acquisition units, 132,332...first and second attribute information acquisition units, 133,333...first and second movement information acquisition units, 134,334...first and second biometric information acquisition units, 135,335...first and second ground information acquisition units, 136,336...first and second population density acquisition units

Claims

1. A database construction device that collects at least location information of each user at each time and information on whether or not the user has fallen from multiple user terminals that each user carries while moving, and constructs a fall risk map of the rate of falls for each location on a map.

2. The database creation device according to claim 1, further comprising fall-related information collected as the collected information, and constructing the fall risk map for each classification of the fall-related information.

3. 3. The database construction device according to claim 2, wherein the fall-related information is collected including meteorological information for the position information at each time.

4. 3. The database construction device according to claim 2, wherein the fall-related information includes and is collected from the user at least one of information on the user's age, sex, and whether or not the user has a motor or cognitive disability.

5. 3. The database creation device according to claim 2, wherein the fall-related information is collected including a magnitude and / or a direction of movement speed in the position information at each time.

6. 3. The database creation device according to claim 2, wherein the fall-related information is collected including biological information of the user at each time.

7. 3. The database creation device according to claim 2, wherein the fall-related information is collected by including information on the shape and / or slope of the ground at each point in time in the position information.

8. 3. The database creation device according to claim 2, wherein the fall-related information is collected by including information on population density at a location corresponding to the position information at each time.

9. A risk information providing device as an individual user terminal, which uses a fall risk map constructed by the database construction device according to any one of claims 2 to 8, comprising: A danger information providing device characterized by transmitting current location information and fall-related information to the database construction device, thereby obtaining fall risk information for the current location on the fall risk map according to the fall-related information and notifying the user.

10. The danger information providing device according to claim 9, characterized in that the danger information providing device displays information on the risk of falling in a surrounding area of ​​the position at the current time to the user on a map corresponding to the fall-related information.

11. The danger information providing device described in claim 10, characterized in that by sending fall-related information separate from the transmitted fall-related information to the database construction device, a map corresponding to the fall-related information is displayed to the user as a map that can be viewed by switching for each different fall-related information.

12. The user is in the middle of receiving route guidance information, 11. The danger information providing device according to claim 10, wherein the danger information providing device notifies the user of information on a risk of falling at a position at the current time on a route in the route guidance information.

13. The danger information providing device of claim 10, characterized in that when the database construction device determines that there is insufficient data storage regarding the occurrence or absence of falls at the location information at the current time, the fall risk on the fall risk map at another location determined to have similar ground information and / or population density is used as an estimate of the fall risk in the location information at the current location.

14. 9. A route search device, comprising: a database creation device according to claim 1, which searches for a route with the minimum cost by using a cost based at least on a fall risk in a fall risk map created by the database creation device according to claim 1.

15. An information collection device as a user terminal, which acquires information to be collected by the database construction device according to any one of claims 2 to 8 at an individual user terminal, comprising: An information collecting device characterized by obtaining information on whether or not a fall has occurred at each time based on output from an acceleration sensor and / or an angular velocity sensor installed in the information collecting device, and then obtaining fall-related information at each time in association with the information on whether or not a fall has occurred.

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