Information processing system, program and system

Abstract

To improve detection accuracy of detecting the occurrence of an event.SOLUTION: An information processing system includes: an acquisition unit that acquires respective position information detected by a first sensor device, a second sensor device, and a third sensor device located within a predetermined area; a first calculation unit that calculates a first relative distance between the first sensor device and the second sensor device, a second relative distance between the first sensor device and the third sensor device, and a third relative distance between the second sensor device and the third sensor device on the basis of the acquired position information; a second calculation unit that calculates a value corresponding to the first relative distance, a value corresponding to the second relative distance and a value corresponding to the third relative distance; and a determination unit that determines whether or not any of the value corresponding to the first relative distance, the value corresponding to the second relative distance and the value corresponding to the third relative distance exceeds a predetermined threshold.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to an information processing system, a program, and a system. [Background technology]

[0002] In recent years, techniques for monitoring the occurrence of natural disasters have been proposed.

[0003] For example, Patent Document 1 discloses a system that monitors slope displacement based on GPS (Global Positioning System) data output from a reference station installed outside the slope and GPS data output from a GPS station installed inside the slope. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-144623 Summary of the Invention [Problem to be solved by the invention]

[0005] There is a demand for improved accuracy in detecting the occurrence of an event. [Means for solving the problem]

[0006] An information processing system according to one aspect of the present invention includes an acquisition unit that acquires position information detected by a first sensor device, a second sensor device, and a third sensor device present in a predetermined area; a first calculation unit that calculates a first relative distance between the first sensor device and the second sensor device, a second relative distance between the first sensor device and the third sensor device, and a third relative distance between the second sensor device and the third sensor device based on the acquired position information; a second calculation unit that calculates a value related to the first relative distance, a value related to the second relative distance, and a value related to the third relative distance; and a determination unit that determines whether any of the value related to the first relative distance, the value related to the second relative distance, and the value related to the third relative distance exceeds a predetermined threshold. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram illustrating an example of a system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the location information acquisition process. [Figure 3] FIG. 3 is a diagram illustrating an example of the configuration of a sensor device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 5] FIG. 5 is a diagram showing an overview of the landslide detection logic. [Figure 6] Figure 6 is a diagram (1) showing a specific example of landslide detection logic. [Figure 7] Figure 7 is a diagram (2) showing a specific example of landslide detection logic. [Figure 8] Figure 8 is a diagram (3) showing a specific example of landslide detection logic. [Figure 9] FIG. 9 is a diagram illustrating an example of the configuration of a display control device according to the embodiment. [Figure 10] FIG. 10 is a diagram showing an example of the display control screen. [Figure 11] FIG. 11 is a diagram showing an example of the display content before a landslide disaster occurs. [Figure 12] FIG. 12 is a diagram showing an example of the display content after a landslide disaster occurs. [Figure 13] FIG. 13 is a flowchart showing the operation procedure of the information processing device. [Figure 14] FIG. 14 is a sequence diagram showing an example of the flow of providing information on landslide disasters to users in the overall system. [Figure 15] FIG. 15 is a sequence diagram showing an example of the flow of providing a three-dimensional map, which is map data, to a user in the overall system. [Figure 16] FIG. 16 is a hardware configuration diagram showing an example of a computer that realizes the functions of the device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0009] One or more embodiments (including examples, modifications, and application examples) described below can be implemented independently. However, at least a portion of the embodiments described below may be implemented in appropriate combination with at least a portion of another embodiment. These embodiments may include novel features that are different from each other. Therefore, these embodiments may contribute to solving different purposes or problems and may produce different effects from each other.

[0010] Furthermore, in the following embodiments, the events targeted by the proposed technology of the present invention are described as natural disasters that change the terrain, particularly landslides, but the proposed technology of the present invention can be applied to various events regardless of natural disasters.

[0011] <Embodiment> 1. Introduction There is a need to detect landslides in real time, rescue affected residents, and promptly guide residents in risk areas to evacuate through landslide warnings.In addition, while there are means of immediate notification such as SNS (Social Networking Service) to quickly initiate action to restore areas affected by landslides, the lack of a means of actively, quickly, and accurately obtaining information on disaster sites is also seen as a problem.

[0012] Therefore, the inventors of the present invention thought that by installing multiple sensor devices on land where landslides are likely to occur (for example, mountain slopes), and calculating the straight-line distance between the sensor devices in three-dimensional space, it would be possible to detect the occurrence of landslides quickly and with high accuracy.

[0013] In other words, the information processing related to the proposed technology of the present invention (hereinafter referred to as "information processing related to the embodiment") is a method in which, when multiple sensor devices are installed on a slope in a "special landslide warning area," the straight-line distance between two points in three-dimensional space between the sensor devices before and after the occurrence of a landslide is calculated in a brute-force manner, to determine the standard deviation value of the difference calculation results obtained by the brute-force calculation, and if the standard deviation value changes to or exceeds a threshold value, the occurrence of a landslide is detected.

[0014] [2. System Configuration] A system for realizing information processing according to an embodiment will be described with reference to FIG. 1. FIG. 1 is a diagram illustrating an example of a system according to an embodiment. As shown in FIG. 1, the system according to an embodiment may be configured by a plurality of different systems. For example, the system according to an embodiment may include a first system Sy1 on the back-end side, a second system Sy2 on the front-end side, an instruction device 400, an aircraft control device 500, and an aircraft FO.

[0015] FIG. 1 also shows an overall system Sy including a first system Sy1 on the back-end side, a second system Sy2 on the front-end side, an instruction device 400, an aircraft control device 500, and an aircraft FO.

[0016] First, the first system Sy1 will be described. The first system Sy1 corresponds to a system according to the embodiment. The first system Sy1 may include a sensor device 10, a reference station 20, a distribution device 30, a management device 40, and a back-end system 100.

[0017] The sensor device 10 may be a portable information processing terminal that can be installed at any location depending on the user's purpose. For example, the sensor device 10 may be installed in advance on land that is at risk of landslides, specifically on land designated as a special landslide warning area (e.g., a mountain slope). For this reason, the sensor device 10 may be a stationary information processing terminal that can be fixedly installed at any location depending on the user's purpose.

[0018] The sensor device 10 may also receive satellite signals. Specifically, the sensor device 10 may receive GNSS (Global Navigation Satellite System) signals from GNSS satellites (not shown). That is, the sensor device 10 may be equipped with a GNSS module (positioning module) including a GNSS receiver compatible with RTK (Real Time Kinematic) and an antenna. The sensor device 10 may also be equipped with a communication module for communicating with the distribution device 30 and the management device 40.

[0019] The sensor device 10 may perform positioning based on the correction information. Specifically, the sensor device 10 may first acquire its own position information based on a GNSS signal. Then, the sensor device 10 may receive correction information distributed from a distribution device 30 (described later). The sensor device 10 may correct its own position information based on the correction information. More specifically, the sensor device 10 may correct its own position information by RTK calculation using the correction information. That is, the sensor device 10 may acquire corrected position information by RTK calculation using the correction information. For this reason, the sensor device 10 may be equipped with a program capable of executing RTK calculation. The RTK calculation may be performed using a conventionally known method.

[0020] Furthermore, to realize the information processing according to the embodiment, a plurality of sensor devices 10 may be installed. For this reason, an example is shown in which the first system Sy1 includes a first sensor device 10-1, a second sensor device 10-2, a third sensor device 10-3, ..., an n-th sensor device 10-n as an example of the plurality of sensor devices 10. When it is not necessary to distinguish between the first sensor device 10-1, the second sensor device 10-2, the third sensor device 10-3, ..., the n-th sensor device 10-n, the sensor device 10 will be referred to as a sensor device 10. Note that time synchronization may be performed to synchronize the times among the plurality of sensor devices 10.

[0021] The reference station 20 may function as a reference station in RTK calculation. That is, the reference station 20 may have known coordinates (known coordinates) that indicate its own position. Furthermore, if there are multiple reference stations 20, each of the multiple reference stations 20 may have known coordinates.

[0022] The reference station 20 may receive satellite signals. Specifically, the reference station 20 may receive GNSS signals from GNSS satellites. For example, the reference station 20 may transmit information on known coordinates and information based on the GNSS signals to the broadcasting device 30. The information based on the GNSS signals may include information indicating the satellite that received the GNSS signals, information indicating the phase of the carrier wave, and the like.

[0023] Specifically, the reference station 20 may transmit various information to the distribution device 30 based on, for example, the standards of the Radio Technical Commission For Maritime Services (RTCM). The reference station 20 may also transmit, for example, ephemeris to the distribution device 30. The reference station 20 may be appropriately installed at any location (for example, a location within the area where the sensor device 10 is installed) by any business operator or the like.

[0024] The broadcasting device 30 may be, for example, a server device. The broadcasting device 30 may receive, from the reference station 20, information on the known coordinates of the reference station 20 and information on the GNSS signal received by the reference station 20. The broadcasting device 30 may generate correction information for correcting an error in positioning by the sensor device 10 based on the information on the known coordinates and GNSS signal of a reference station 20 to be processed among the reference stations 20. The correction information may include, for example, information on the known coordinates of the reference station 20 and information on the phase of a carrier wave from a GNSS satellite.

[0025] The broadcasting device 30 may transmit the generated correction information to the sensor device 10. Note that the information included in the correction information is not limited to the above example. The correction information may include any information necessary for the RTK calculation by the sensor device 10.

[0026] Here, positioning by RTK calculation using correction information will be described. First, the sensor device 10 may acquire rough position information (approximate position information) of the sensor device 10 by positioning based on GNSS signals. Then, the broadcasting device 30 may generate correction information including information on the known coordinates of the reference station 20 and information based on the GNSS signals. The broadcasting device 30 may transmit the correction information to the sensor device 10. The sensor device 10 may correct the approximate position information by RTK calculation using the correction information. That is, the sensor device 10 may calculate information (corrected position information) by correcting the approximate position information using the correction information by RTK calculation.

[0027] The sensor device 10 may transmit the corrected position information to the management device 40. In addition, the management device 40 may transmit the corrected position information to the backend system 100.

[0028] The management device 40 may act as an intermediary for transmitting and receiving information between the sensor device 10 and the backend system 100. For example, the management device 40 may acquire corrected location information transmitted by the sensor device 10 and transmit the acquired corrected location information to the backend system 100. The management device 40 may be a server operating on a data center configured on a public cloud such as AWS (Amazon Web Service).

[0029] The first system Sy1 does not need to include the management device 40, and the corrected location information may be transmitted directly from the sensor device 10 to the backend system 100. Alternatively, the sensor device 10 may transmit the corrected location information to the distribution device 30, and the distribution device 30 may transmit the corrected location information to the backend system 100.

[0030] The backend system 100 corresponds to an information processing system according to the embodiment. The backend system 100 may be configured, for example, by one or more server devices, but in this embodiment, it will be described as a single server device. Therefore, hereinafter, the backend system 100 will be referred to as an information processing device 100.

[0031] The information processing device 100 executes back-end processing among the information processing according to the embodiment. The main back-end processing may be a landslide detection process that detects the occurrence of a landslide in real time based on position information acquired from the sensor device 10, or a process that generates a three-dimensional map from three-dimensional point cloud data generated by the air vehicle FO. The information processing device 100 can acquire the three-dimensional point cloud data via the air vehicle control device 500.

[0032] Furthermore, when the information processing device 100 detects the occurrence of a landslide disaster, it may notify alert information indicating the occurrence of the landslide disaster to the front-end system 200 or the indicating device 400. The alert information may include at least information indicating the occurrence of the landslide disaster and information on the area where the landslide disaster occurred.

[0033] Next, the second system Sy2 will be described. The second system Sy2 may include meteorological information DA1, landslide special zone information DA2, a wearable device WT, and a front-end system 200.

[0034] The weather information DA1 may include local weather information provided by the Japan Meteorological Agency. The weather information may also include rainfall data measured by a rainfall sensor. The weather information DA1 may be provided to the front-end system 200 from an external device belonging to the Japan Meteorological Agency through API linkage via the Internet.

[0035] The special landslide disaster area information DA2 is information indicating areas of land that are deemed to be at risk of harm to the lives or bodies of residents in the event of a landslide disaster, and may be provided by local governments. The special landslide disaster area information DA2 may be provided to the front-end system 200 from an external device belonging to each local government through API linkage via the Internet.

[0036] Although not shown in FIG. 1, information about no-entry areas that exist in various places (for example, information about no-entry areas in special landslide disaster zones) may also be uploaded to the front-end system 200.

[0037] The wearable terminal WT is an information processing terminal worn by a worker at a work site and may include a sensor capable of detecting vital sign information of the worker. The wearable terminal WT may provide the vital sign information of the worker to the front-end system 200 through API linkage via a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation: fifth generation mobile communication system).

[0038] The front-end system 200 may be configured with, for example, one or more server devices, but in this embodiment, it will be described as a single server device. Therefore, hereinafter, the front-end system 200 will be referred to as the display control device 200.

[0039] The display control device 200 executes front-end processing among the information processing according to the embodiment. The main front-end processing may be providing information to a user using a predetermined screen. For example, the display control device 200 may display, on the user's instruction device 400, information about the area where the sensor device 10 is installed, information indicating the occurrence of a landslide, information about the area where the landslide occurred, vital sign information of high urgency / importance when workers are in or near the area where the landslide occurred, and the like.

[0040] The user in the embodiment may be an organization U (specifically, personnel of the organization) that monitors the occurrence of landslides or is requested to respond when a landslide occurs, such as the police, fire department, or administrative agency (local government). The user may also include a management company M that is responsible for building and managing the overall system Sy.

[0041] Next, the flying object FO, the instruction device 400, and the flying object control device 500 will be described as other devices included in the overall system Sy.

[0042] The air vehicle FO may be, for example, a drone. The air vehicle FO may be used by a user. The air vehicle FO may also be equipped with a positioning module that measures the position of the air vehicle itself. The air vehicle FO may also be equipped with, for example, a sensor device 10 as a device including a positioning module. That is, the air vehicle FO may acquire corrected position information indicating the position of the air vehicle itself by RTK calculation using correction information. The RTK calculation may be performed using a conventionally known method.

[0043] Furthermore, the flying object FO and the sensor device 10 may be separate devices. That is, a user may retrofit the sensor device 10 to a ready-made flying object FO, causing the flying object FO to measure its own position. On the other hand, the flying object FO and the sensor device 10 may be an integrated device. That is, a user may cause the flying object FO, which has one function similar to that of the sensor device 10, to measure its own position.

[0044] Furthermore, the air vehicle FO may be equipped with a point cloud data generation module having a LiDAR (Light Detection and Ranging) function. That is, the air vehicle FO may use positioning data obtained by the RTK positioning function (positioning module) to identify its own position when generating point cloud data (three-dimensional point cloud data).

[0045] The flying object FO and the point cloud data generation module may also be separate devices. That is, a user may retrofit a point cloud data generation module to a ready-made flying object FO, causing the flying object FO to generate point cloud data. On the other hand, the flying object FO and the point cloud data generation module may also be integrated into one device. That is, a user may cause an flying object FO that has the same functions as the point cloud data generation module to generate point cloud data.

[0046] The instruction device 400 is an information processing terminal used to give flight instructions to the flying object FO according to weather information, etc., or to instruct the flying object FO before or during flight on the position of an object from which point cloud data should be acquired. The instruction device 400 may be, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, or a PDA (Personal Digital Assistant).

[0047] The instruction device 400 inputs instruction information received from a user to the aircraft control device 500. Here, the user who gives flight instructions to the aircraft FO or indicates the location of the target from which point cloud data should be acquired may be the above-mentioned organization U or management company M. In FIG. 1, instruction device 400-1 is shown as an example of an instruction device 400 used by organization U, and instruction device 400-2 is shown as an example of an instruction device 400 used by management company M.

[0048] The flying object control device 500 may be, for example, a server device. The flying object control device 500 controls the flight of the flying object FO according to the input instruction information. For example, the flying object control device 500 may control the flying object FO to fly along a flight path defined by the instruction information. Since the flying object FO is equipped with a positioning module, it may fly while comparing its own position calculated by RTK calculation with information on the flight path.

[0049] Furthermore, the air vehicle control device 500 controls the air vehicle FO to generate point cloud data for the position of the target defined by the instruction information. The air vehicle FO is equipped with a point cloud data generation module (e.g., a LiDAR function), and therefore generates three-dimensional point cloud data for the position of the target defined by the instruction information based on its own position determined by RTK calculation. For example, the air vehicle FO can generate first three-dimensional point cloud data for a first period (e.g., before a landslide occurs) and second three-dimensional point cloud data for a second period (e.g., after a landslide occurs).

[0050] In addition, the flying object control device 500 may acquire three-dimensional point cloud data from the flying object FO and transmit the acquired three-dimensional point cloud data to the information processing device 100.

[0051] [3. Obtaining location information] When detecting the occurrence of a landslide disaster, the information processing device 100 acquires position information of each sensor device 10. Specifically, the information processing device 100 acquires corrected position information corrected by RTK calculation from the sensor device 10. Acquisition of corrected position information will now be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of a position information acquisition process.

[0052] 2 shows a scene in which multiple sensor devices 10 are installed on the slope of a mountain in an area AR included in a special landslide warning zone, and corrected position information is acquired from each sensor device 10. A reference station 20 is also installed in the area AR. Note that the number of sensor devices 10 and reference stations 20 in the area AR is not limited to the example in FIG. 2.

[0053] The sensor device 10 may calculate location information indicating its own location (installed location) by GNSS positioning based on the GNSS signals. The location information may be rough location information (approximate location information) that indicates a location within a range of several meters around the actual location of the sensor device 10. The sensor device 10 may transmit the approximate location information together with information on the received GNSS signals to the broadcasting device 30 (step S21).

[0054] The broadcasting device 30 may select a target reference station 20 from among the reference stations 20 based on the approximate location information received from the sensor device 10. For example, the broadcasting device 30 may select a target reference station 20 that is located in an area corresponding to the location indicated by the approximate location information.

[0055] In the above example, the sensor device 10 calculates the approximate location information by GNSS positioning, but the broadcasting device 30 may calculate the approximate location information of the sensor device 10. In this case, in step S21, the sensor device 10 only needs to transmit a GNSS signal, and the broadcasting device 30 may calculate the approximate location information of the sensor device 10 by GNSS positioning based on the GNSS signal received from the sensor device 10.

[0056] Next, the distribution device 30 may transmit a distribution request to the selected reference station 20 to request distribution of the GNSS signal (step S22). The reference station 20 may constantly receive the GNSS signal. That is, the reference station 20 to be processed may transmit information based on the received GNSS signal to the distribution device 30 when it receives the distribution request (step S23).

[0057] After receiving the distribution request, the target reference station 20 may continue to transmit the GNSS signal to the distribution device 30. Alternatively, the reference station 20 may constantly push the GNSS signal to the distribution device 30. That is, the reference station 20 may transmit the GNSS signal to the distribution device 30 even without receiving a distribution request from the distribution device 30. In this case, the distribution device 30 may store the received GNSS signal.

[0058] The broadcasting device 30 may generate correction information based on the GNSS signal received from the target reference station 20 (step S24). For example, the broadcasting device 30 may calculate the position coordinates of the reference station 20 by GNSS positioning based on the GNSS signal received from the target reference station 20, and generate the correction information by calculating the difference between the calculated position coordinates and known coordinates of the reference station 20 (for example, stored in advance in the broadcasting device 30). The correction information is used to correct the approximate position information of the sensor device 10 in real time.

[0059] In the above example, the broadcasting device 30 calculates its position coordinates using GNSS positioning, but the target reference station 20 may calculate its own position coordinates. In this case, in step S23, the target reference station 20 may transmit information indicating its own position coordinates to the broadcasting device 30 together with information based on the GNSS signal.

[0060] The broadcasting device 30 may transmit the generated correction information to the sensor device 10 that transmitted the approximate position information (step S25).

[0061] The sensor device 10 may perform a correction calculation to correct the approximate location information based on the correction information received from the broadcasting device 30 (step S26). Specifically, the sensor device 10 may calculate corrected location information by correcting the approximate location information through RTK calculation using the correction information.

[0062] The sensor device 10 may transmit the corrected position information to the management device 40 (step S27). When the management device 40 receives the corrected position information from the sensor device 10, the management device 40 may transmit the received corrected position information to the information processing device 100 (step S28). As a result, the information processing device 100 can acquire the position information of the sensor device (specifically, the corrected position information) via the management device 40.

[0063] 4. Configuration of the sensor device The sensor device 10 according to the embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the configuration of the sensor device 10 according to the embodiment. As shown in Fig. 3, the sensor device 10 may include a communication unit 11, a GNSS module M, a storage unit 12, and a control unit 13.

[0064] (Regarding the communication unit 11 and the GNSS module M) The communication unit 11 may be realized by, for example, a network interface card (NIC). The communication unit 11 may be connected to a network via a wired or wireless connection. The communication unit 11 may transmit and receive information between, for example, the distribution device 30, the management device 40, and the information processing device 100 via the network. The GNSS module M can receive GNSS signals. That is, the GNSS module M may be configured with any components for receiving GNSS signals.

[0065] (Regarding the storage unit 12) The storage unit 12 may be realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 12 may store, for example, the approximate position information calculated by the approximate position calculation unit 13b, the correction information received from the broadcasting device 30, and the corrected position information obtained by RTK calculation using the correction information.

[0066] (Regarding the control unit 13) The control unit 13 may be realized by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an MPU (Micro Processing Unit), or the like, executing various programs stored in a storage device inside the sensor device 10 using RAM as a work area. The control unit 13 may also be realized by an integrated circuit, such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0067] The control unit 13 may have a first receiving unit 13a, an approximate position calculating unit 13b, a first transmitting unit 13c, a second receiving unit 13d, a correcting unit 13e, and a second transmitting unit 13f. Note that the internal configuration of the control unit 13 is not limited to the configuration shown in Fig. 3 and may have other configurations as long as they perform the information processing described below. Furthermore, the connection relationship between the processing units included in the control unit 13 is not limited to the connection relationship shown in Fig. 3 and may be other connection relationships.

[0068] (Regarding the first receiving unit 13a) The first receiving unit 13a corresponds to a GNSS receiver and antenna that supports RTK and may receive GNSS signals. The first receiving unit 13a may output the received GNSS signals to the approximate position calculating unit 13b.

[0069] (Regarding the approximate position calculation unit 13b) The approximate position calculation unit 13b may calculate position information indicating the position of the device itself by GNSS positioning based on the GNSS signals received by the first receiving unit 13a. That is, the approximate position calculation unit 13b may calculate the approximate position information by GNSS positioning based on the GNSS signals. Furthermore, the approximate position calculation unit 13b may store the approximate position information in the storage unit 12.

[0070] (Regarding the first transmitting unit 13c) The first transmitter 13c may transmit to the broadcasting device 30 the approximate position information calculated by the approximate position calculator 13b.

[0071] (Regarding the second receiving unit 13d) The second receiving unit 13d may receive the correction information transmitted from the distribution device 30. The second receiving unit 13d may also cause the storage unit 12 to store the correction information.

[0072] (Regarding the correction unit 13e) The corrector 13e may perform a correction calculation to correct the approximate position information calculated by the approximate position calculator 13b based on the correction information received by the second receiver 13d. That is, the corrector 13e may correct the approximate position information by RTK calculation using the correction information. The corrector 13e may store the corrected position information (corrected position information) obtained by the correction calculation in the storage unit 12.

[0073] (Regarding the second transmitting unit 13f) The second transmission unit 13f may transmit corrected position information obtained by the RTK calculation by the correction unit 13e. For example, the second transmission unit 13f may transmit the corrected position information to the management device 40. Note that the second transmission unit 13f may transmit the corrected position information directly to the information processing device 100.

[0074] 5. Configuration of Information Processing Device The information processing device 100 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Fig. 4, the information processing device 100 may include a communication unit 110, a storage unit 120, and a control unit 130.

[0075] (Regarding the communication unit 110) The communication unit 110 is realized by, for example, a NIC etc. For example, the communication unit 110 is connected to a network by wire or wirelessly, and transmits and receives information to and from the sensor device 10, the management device 40, the display control device 200, the instruction device 400, and the aircraft control device 500.

[0076] (Regarding the storage unit 120) The storage unit 120 may be realized by, for example, a semiconductor memory element such as RAM or flash memory, or a storage device such as a hard disk or optical disk. The storage unit 120 may store, for example, information necessary for landslide detection processing, information necessary for generating alert information indicating the occurrence of a landslide, etc. The storage unit 120 may also store a program that causes the information processing device 100 to execute information processing according to the embodiment.

[0077] (Regarding the control unit 130) The control unit 130 may be realized by a CPU, a GPU, an MPU, or the like executing various programs stored in a storage device inside the information processing device 100 using RAM as a work area. The control unit 130 may also be realized by an integrated circuit such as an ASIC or an FPGA.

[0078] The control unit 130 may include an acquisition unit 131, a first calculation unit 132, a second calculation unit 133, a determination unit 134, an estimation unit 135, and a notification unit 136. The internal configuration of the control unit 130 is not limited to the configuration shown in Fig. 4 and may be other configurations as long as they perform the information processing described below. Furthermore, the connection relationship between the processing units included in the control unit 130 is not limited to the connection relationship shown in Fig. 4 and may be other connection relationships.

[0079] (Regarding the acquisition unit 131) The acquisition unit 131 may acquire position information detected by each of the sensor devices 10 present in a predetermined area. Specifically, the acquisition unit 131 may acquire corrected position information obtained by correcting the approximate position information of the sensor devices 10 present in a predetermined area through RTK calculation. For example, the acquisition unit 131 may acquire corrected position information obtained through RTK calculation by each of the first sensor device 10-1, the second sensor device 10-2, the third sensor device 10-3, ..., the n-th sensor device 10-n.

[0080] For example, the first sensor device 10-1, the second sensor device 10-2, the third sensor device 10-3, ..., the n-th sensor device 10-n calculates corrected position information at a predetermined period by performing RTK calculation at a predetermined period. Therefore, the acquisition unit 131 may sequentially acquire the corrected position information of each sensor device 10 in response to the calculation of the corrected position information at the predetermined period.

[0081] The acquisition unit 131 may also acquire other information. For example, the acquisition unit 131 may acquire three-dimensional point cloud data. For example, the acquisition unit 131 may acquire three-dimensional point cloud data generated by the flying object FO using a LiDAR function.

[0082] The corrected location information acquired by the acquisition unit 131 may be three-dimensional location information including information on longitude, latitude, and altitude. The predetermined area may be, for example, an area AR included in a special landslide warning zone.

[0083] (Regarding the first calculation unit 132) The first calculation unit 132 may calculate, based on the corrected position information, the relative distance between two different sensor devices 10. For example, the first calculation unit 132 may calculate the relative distance between two different sensor devices 10 for all possible combination patterns of two different sensor devices 10 (i.e., in a brute force search), based on the corrected position information of each of the two different sensor devices 10.

[0084] Specifically, the first calculation unit 132 may calculate a first relative distance between the first sensor device 10-1 and the second sensor device 10-2, a second relative distance between the first sensor device 10-1 and the third sensor device 10-3, and a third relative distance between the second sensor device 10-2 and the third sensor device 10-3.

[0085] More specifically, the first calculation unit 132 may calculate a first relative distance between the first sensor 10-1 and the second sensor 10-2 based on the corrected position information (initial value of the position information) at the time the first sensor 10-1 was installed and the current corrected position information (current value of the position information) of the second sensor 10-2. The first calculation unit 132 may calculate a second relative distance between the first sensor 10-1 and the third sensor 10-3 based on the corrected position information (initial value of the position information) at the time the first sensor 10-1 was installed and the current corrected position information (current value of the position information) of the third sensor 10-3. The first calculation unit 132 may calculate a third relative distance between the second sensor 10-2 and the third sensor 10-3 based on the corrected position information (initial value of the position information) at the time the second sensor 10-2 was installed and the current corrected position information (current value of the position information) of the third sensor 10-3.

[0086] The first calculation unit 132 may sequentially calculate the relative distance between two different sensor devices 10 in response to the sequential acquisition of corrected position information by the acquisition unit 131. Furthermore, the first calculation unit 132 may calculate the relative distance as a straight-line distance based on three-dimensional position information.

[0087] (Regarding the second calculation unit 133) The second calculation unit 133 may calculate values ​​related to the relative distances. For example, the second calculation unit 133 may calculate a value related to the first relative distance, a value related to the second relative distance, and a value related to the third relative distance.

[0088] For example, the second calculation unit 133 may calculate a standard deviation value as the value related to the relative distance. Note that the second calculation unit 133 may calculate a value other than a standard deviation value as the value related to the relative distance. For example, the second calculation unit 133 may calculate, as the value related to the first relative distance, the difference between a first relative distance calculated at a certain time point and a first relative distance calculated at a subsequent time point, or may calculate the proportion of the difference. Furthermore, the second calculation unit 133 may calculate, as the value related to the second relative distance, the difference between a second relative distance calculated at a certain time point and a second relative distance calculated at a subsequent time point, or may calculate the proportion of the difference. Furthermore, the second calculation unit 133 may calculate, as the value related to the third relative distance, the difference between a third relative distance calculated at a certain time point and a third relative distance calculated at a subsequent time point, or may calculate the proportion of the difference.

[0089] The second calculation unit 133 may sequentially calculate a value related to the relative distance in response to the acquisition unit 131 sequentially acquiring the corrected position information.

[0090] (Regarding the determination unit 134) The determination unit 134 may detect the occurrence of an event. For example, the determination unit 134 may detect the occurrence of a landslide disaster. For example, the determination unit 134 may determine whether a value related to the relative distance exceeds a predetermined threshold, and if the value related to the relative distance exceeds the predetermined threshold, determine that a landslide disaster has occurred in a predetermined area. For example, the determination unit 134 may determine whether any of the value related to the first relative distance, the value related to the second relative distance, and the value related to the third relative distance exceeds a threshold.

[0091] (Regarding the estimation unit 135) The estimation unit 135 may estimate an occurrence area where an event has occurred. For example, the estimation unit 135 may estimate an occurrence area where a landslide has occurred. For example, the estimation unit 135 may estimate the occurrence area where a landslide has occurred based on the difference between the corrected position information of each sensor device 10 after the determination unit 134 has determined that a landslide has occurred and the position information of each sensor device 10 before it has been determined that a landslide has occurred.

[0092] Furthermore, the information processing device 100 may calculate the volume of sediment by matching the relative positional relationship of point cloud data based on first three-dimensional point cloud data from a first period (e.g., before the occurrence of a landslide disaster) and second three-dimensional point cloud data from a second period (e.g., after the occurrence of a landslide disaster). In this case, the estimation unit 135 may also estimate the type and number of equipment required to remove sediment from an area affected by the volume of sediment (a geographical area newly covered by sediment due to the landslide disaster).

[0093] (Regarding the notification unit 136) When it is determined that an event has occurred, the notification unit 136 may notify information related to the event that has occurred. For example, when it is determined that a landslide has occurred, the notification unit 136 may notify one or more devices not included in the backend system 100 of alert information including at least information indicating the occurrence of the landslide and information on the area where the landslide has occurred. For example, the notification unit 136 may output the alert information to the display control device 200 so that the alert information is notified to a user. The notification unit 136 may also notify the instruction device 400 of the alert information.

[0094] Furthermore, the notification unit 137 may output information on a geographical area that has been newly covered by sediment due to a landslide (landslide area) to the display control device 200 so that the information is notified to the user.

[0095] [6. Overview of landslide detection logic] Next, we will explain the logic of the landslide detection process executed by the information processing device 100. Fig. 5 is a diagram showing an outline of the landslide detection logic. Fig. 5 shows a scene in which, in a case where ten sensor devices 10 are installed on the slope of a mountain in an area AR included in a special landslide warning zone, the occurrence of a landslide is detected based on the position information (corrected position information) acquired from each sensor device 10.

[0096] In Figure 5, the 10 sensor devices 10 are specifically a first sensor device 10-1, a second sensor device 10-2, a third sensor device 10-3, a fourth sensor device 10-4, a fifth sensor device 10-5, a sixth sensor device 10-6, a seventh sensor device 10-7, an eighth sensor device 10-8, a ninth sensor device 10-9, and a tenth sensor device 10-10.

[0097] As shown in FIG. 5, the corrected position information (longitude, latitude, altitude) at time t0 when these ten sensor devices 10 are installed is set as the initial value of the position information, and the corrected position information (longitude, latitude, altitude) at the current time tx, which is subsequently acquired sequentially in time series, is set as the current value of the position information. In this case, the first calculation unit 132 may calculate the relative distance for every combination of two different sensor devices 10 based on the initial value of the position information and the current value of the position information. More specifically, the first calculation unit 132 may calculate the relative distance between two different sensor devices 10 for every possible combination pattern of two different sensor devices 10 based on the initial value of the position information of one sensor device 10 and the current value of the position information of the other sensor device.

[0098] Furthermore, since the relative distance is calculated by the first calculation unit 132 for each current time tx according to the time series, the second calculation unit 133 may calculate the standard deviation value at the current time tx from the relative distance for each current time tx according to the time series.

[0099] [7. Specific examples of landslide detection logic] Next, the logic of the landslide disaster detection process will be explained in detail using Figures 6 and 7. An example of calculating the standard deviation value in the logic of the landslide disaster detection process will be explained in Figures 6 and 7. Figure 6 is a diagram (1) showing a specific example of the landslide disaster detection logic.

[0100] 6, the current value of the position information of each sensor device 10 at time t1 (an example of the current time tx) is acquired by the acquisition unit 131. In this case, as shown in FIG. 6, the first calculation unit 132 may calculate the relative distance in a brute force manner for all combinations (some omitted) of two different sensor devices 10 based on the initial value of the position information at time t0 and the current value of the position information at time t1.

[0101] 6, in one example, the first calculation unit 132 may calculate a relative distance D1-2 between the first sensor 10-1 and the second sensor 10-2 at time t1 based on an initial value PT1 of the position information of the first sensor 10-1 and a current value PT2 of the position information of the second sensor 10-2. In another example, the first calculation unit 132 may calculate a relative distance D2-3 between the second sensor 10-2 and the third sensor 10-3 at time t1 based on an initial value PT2 of the position information of the second sensor 10-2 and a current value PT3 of the position information of the third sensor 10-3.

[0102] Once the relative distances are calculated in this manner, the second calculation unit 133 may calculate a standard deviation value of the relative distances from each relative distance. In the example of Fig. 6, the second calculation unit 133 may calculate a standard deviation value SD1 of the relative distances from each relative distance calculated at the current time t1 for every combination of two different sensor devices 10.

[0103] Similar processing may be performed for time t2 (an example of the current time tx) and time t3 (an example of the current time tx), and Figure 6 shows an example in which the second calculation unit 133 calculates the standard deviation value SD2 at time t2 and the standard deviation value SD3 at time t3.

[0104] While FIG. 6 conceptually shows location information such as an initial value PT1 of the location information and a current value PT2 of the location information, FIG. 7 shows an example of actual values ​​for the initial value of the location information, the current value of the location information, and the standard deviation value. FIG. 7 is a diagram (2) showing a specific example of landslide detection logic. FIG. 7 shows an example focusing on a situation in which, for every combination of two different sensor devices 10, the relative distance between two different sensor devices 10 at time t3 is calculated based on the initial value of the location information (initial values ​​of longitude, latitude, and altitude) of one sensor device 10 at time t0 and the current value of the location information of the other sensor device at time t3 (current values ​​of longitude, latitude, and altitude).

[0105] FIG. 7 shows an example in which the second calculation unit 133 calculates "16.58200952" as the standard deviation value SD3 of the relative distances from the relative distances calculated at the current time t3.

[0106] As explained above, the position information of the sensor device 10 is sequentially acquired according to the time series since its installation. As a result, the standard deviation value at the current time tx is sequentially calculated from the relative distance for each current time tx according to the time series. Therefore, when a landslide does not occur, there is little change in the position information, and it is considered that there is little difference between the relative distances at each time tx. On the other hand, if a landslide occurs at a certain timing, there may be a large change in the position information of the sensor device 10 installed near the location where the landslide occurred, and therefore, there may also be a large change in the relative distance of the group including this sensor device 10. As a result, the standard deviation value at the time tx when the landslide occurs will be significantly different from the standard deviation values ​​at each time tx before the landslide. Therefore, the determination unit 134 determines whether the standard deviation value exceeds a predetermined threshold. If the standard deviation value exceeds the predetermined threshold, it can be determined that a landslide has occurred. In other words, the determination unit 134 can detect the occurrence of a landslide. This point will be explained using FIG. 8.

[0107] Fig. 8 explains an example of detecting the occurrence of a landslide disaster in the logic of the landslide disaster detection process. Fig. 8 is a diagram (3) showing a specific example of the landslide disaster detection logic. Fig. 8 shows an example focusing on a scene in which, for every combination of two different sensor devices 10, the relative distance between two different sensor devices 10 at time t4 is calculated based on the initial values ​​(initial values ​​of longitude, latitude, and altitude) of the position information of one sensor device 10 at time t0 and the current values ​​(current values ​​of longitude, latitude, and altitude) of the position information of the other sensor device at time t4.

[0108] In the example of FIG. 7, the second calculation unit 133 calculates "30.35902763" as the standard deviation SD4 of the relative distances from the relative distances calculated at the current time t4.

[0109] Here, for example, it is assumed that the predetermined threshold value is set to "20." In this case, the determination unit 134 may determine that the standard deviation value SD4 exceeds the predetermined threshold value and determine that a landslide disaster has occurred in the area AR where 10 sensor devices 10 are installed. The determination unit 134 may also determine that a landslide disaster has occurred at time t4.

[0110] Furthermore, the estimation unit 135 may compare the current value of the position information at time t3 as the position information before the landslide disaster occurred with the current value of the position information at time t4 as the position information after the landslide disaster occurred, and calculate the difference in the position information between the same sensor device 10 before and after the disaster.The estimation unit 135 may then estimate that the vicinity of the location where the sensor device 10 is installed, for which a difference exceeding a predetermined threshold has been calculated, is the area where the landslide disaster occurred.

[0111] For example, when comparing the example of Fig. 7 (before the landslide disaster occurred) with the example of Fig. 8 (after the landslide disaster occurred), it is assumed that the position information of the sixth sensor device 10-6 has changed and the difference in the position information exceeds a predetermined threshold. In this case, the estimation unit 135 may estimate that the area AR near the location where the sixth sensor device 10-6 is installed is the area where the landslide disaster occurred.

[0112] 8. Configuration of the display control device A display control device 200 according to an embodiment will be described with reference to Fig. 9. Fig. 9 is a diagram showing an example of the configuration of the display control device 200 according to an embodiment. As shown in Fig. 9, the display control device 200 may include a communication unit 210, a storage unit 220, and a control unit 230.

[0113] (Regarding the communication unit 210) The communication unit 210 is realized by, for example, a NIC etc. For example, the communication unit 210 is connected to a network via a wired or wireless connection, and transmits and receives information to and from the information processing device 100, the instruction device 400, and the wearable terminal WT.

[0114] (Regarding the storage unit 220) The storage unit 220 may be realized by, for example, a semiconductor memory element such as RAM or flash memory, or a storage device such as a hard disk or optical disk. The storage unit 220 may store, for example, information necessary for generating alert information indicating the occurrence of a landslide, information on the geographical area newly covered by sediment due to a landslide (landslide area), etc. The storage unit 120 may also store a program that causes the information processing device 100 to execute information processing according to the embodiment.

[0115] (Regarding the control unit 230) The control unit 230 may be realized by a CPU, a GPU, an MPU, or the like executing various programs stored in a storage device inside the display control device 200 using RAM as a work area. The control unit 230 may also be realized by an integrated circuit such as an ASIC or an FPGA, for example.

[0116] The control unit 230 may have a first receiving unit 231, a second receiving unit 232, and a display control unit 233. The internal configuration of the control unit 230 is not limited to the configuration shown in Fig. 9, and may have another configuration as long as it is configured to perform information processing described below. Furthermore, the connection relationship between the processing units included in the control unit 230 is not limited to the connection relationship shown in Fig. 9, and may be another connection relationship.

[0117] (Regarding the first receiving unit 231) The first receiving unit 231 may receive information about an event and information about an area where the event occurred from the information processing device 100. For example, the first receiving unit 231 may receive information indicating the occurrence of a landslide disaster and information about the area where the landslide disaster occurred from the information processing device 100.

[0118] The first receiving unit 231 may also receive information on landslide disaster areas and a three-dimensional map generated based on the three-dimensional point cloud data from the information processing device 100. Furthermore, the first receiving unit 231 may receive vital sign information of workers from the wearable device WT.

[0119] (Regarding the second receiving unit 232) The second receiving unit 232 may receive information that has been made into open data. For example, the second receiving unit 232 may receive weather information DA1 that includes rainfall data measured by a rainfall sensor, or landslide disaster special zone information DA2 from an external device. The second receiving unit 232 may also receive information on no-entry areas that exist in various locations.

[0120] (Regarding the display control unit 233) The display control unit 233 may notify (provide / transmit) to the user the information received by the first receiving unit 231 and the second receiving unit 232. Specifically, the display control unit 233 may control the display so that the information received by the first receiving unit 231 and the second receiving unit 232 is displayed on the user's instruction device 400. For example, the display control unit 233 may display the information received by the first receiving unit 231 and the second receiving unit 232 together with map data.

[0121] The map data may be an aerial image captured by an air vehicle FO or the like, or a three-dimensional map obtained based on three-dimensional point cloud data generated by the air vehicle FO.

[0122] [9. Display Control Screen] The display control unit 233 may cause the instruction device 400 to display the information received by the first receiving unit 231 and the second receiving unit 232 via the screen G1 shown in Fig. 10. The display control unit 233 may cause the instruction device 400 to display the information received by the first receiving unit 231 and the second receiving unit 232 via the screen G1 shown in Fig. 10 in a state where the information received by the first receiving unit 231 and the second receiving unit 232 is embedded in a display frame included in the screen G1.

[0123] Fig. 10 is a diagram showing an example of a display control screen. According to the example of Fig. 10, a plurality of display frames may be provided on the screen G1. As an example, six display frames, namely, display frames G11 to G16, may be provided on the screen G1.

[0124] 10, the name of the area designated by the user may be displayed in the display frame G11. The weather information for the area designated by the user may be displayed in the display frame G12. The map data for the area designated by the user may be displayed in the display frame G13. The area referred to here may be, for example, a designated area designated by the user from among areas AR included in the special landslide warning zone.

[0125] If a worker is in the area specified by the user, the display frame G14 may display the worker's vital signs. If a worker is in the area specified by the user, the display frame G15 may display the worker's location information (location information of the wearable device WT worn by the worker). The display frame G16 may display various information related to the occurrence of a landslide disaster as event information.

[0126] Here, screen G1 may display information corresponding to both before and after the occurrence of an event. For example, screen G1 may display information corresponding to the state before a landslide disaster occurs when no landslide disaster has occurred, and may display information corresponding to the state after a landslide disaster occurs when a landslide disaster has occurred. An example of the display content corresponding to each state will be described below.

[0127] First, an example of the display content before a landslide disaster occurs will be described. Fig. 11 is a diagram showing an example of the display content before a landslide disaster occurs. Fig. 11 shows an example of the display content before a landslide disaster occurs when a user specifies an area called "Mount Takao Area #1" from among the areas AR assigned on the map data.

[0128] In this case, the display frame G11 may display "Mount Takao Area #1" as the area name. Furthermore, the display frame G12 may display current weather information (before the landslide occurred) for the "Mount Takao Area #1," and FIG. 11 shows an example in which "Sunny" is displayed. The display frame G12 may also display current rainfall data for the "Mount Takao Area #1."

[0129] Display frame G13 may display current map data (before the landslide disaster occurred) of the "Mount Takao Area #1." For example, if the aircraft FO is currently flying over the "Mount Takao Area #1," an aerial image captured by the aircraft FO may be displayed as map data. On the other hand, for example, if the aircraft FO is currently flying over the "Mount Takao Area #1," a three-dimensional map obtained from three-dimensional point cloud data generated by the aircraft FO may be displayed as map data. In addition, some external organizations (e.g., local governments) may be working to make three-dimensional point cloud data open data. For this reason, a three-dimensional map generated from three-dimensional point cloud data provided by an external organization may be displayed as map data.

[0130] Furthermore, as shown in FIG. 11, the map data in the display frame G13 may be displayed in association with the location where the sensor device 10 is installed, indicating that there is no abnormality in the position change of the sensor device 10 and that the change is normal (i.e., no landslide has occurred).

[0131] Display frame G14 may display the current vital signs of a worker in "Mount Takao Area #1," and FIG. 11 shows an example in which "Vital signs check normal." Display frame G15 may display the current location information of the worker in "Mount Takao Area #1" (the location information of the wearable device WT worn by the worker). Furthermore, if there is a no-entry area near the worker's current location, information about the no-entry area may also be displayed in display frame G15, as shown in FIG. 11.

[0132] The display frame 16 may display alert information indicating the occurrence of a landslide disaster, but in the example of FIG. 11 before the landslide disaster occurs, no display may be displayed.

[0133] Next, an example of the display content after a landslide disaster occurs will be described. Fig. 12 is a diagram showing an example of the display content after a landslide disaster occurs. Fig. 12 shows an example of the display content after a landslide disaster occurs when a user specifies an area called "Mount Takao Area #1" from among the areas AR assigned on the map data.

[0134] In this case, the display frame G11 may display "Mount Takao Area #1" as the area name. Furthermore, the display frame G12 may display current weather information (after the landslide disaster occurred) for the "Mount Takao Area #1," and FIG. 12 shows an example in which "Rain" is displayed. The display frame G12 may also display current rainfall data for the "Mount Takao Area #1."

[0135] Display frame G13 may display current (post-landslide) map data for "Mount Takao Area #1." For example, if the aircraft FO is currently flying over "Mount Takao Area #1," an aerial image captured by the aircraft FO may be displayed as map data. On the other hand, for example, if the aircraft FO is currently flying over "Mount Takao Area #1," a three-dimensional map obtained from three-dimensional point cloud data generated by the aircraft FO may be displayed as map data.

[0136] 12, the map data in the display frame G13 may display information indicating that there is an abnormality in the position change of the sensor device 10 (i.e., that a landslide may have occurred) in association with the location where the sensor device 10 is installed. Here, FIG. 7 shows an example in which the estimation unit 135 estimates that the vicinity of the location where the sixth sensor device 10-6 is installed in the area AR as an occurrence area where a landslide has occurred. Following this example, information indicating that there is an abnormality may be displayed for the installation location of the sensor device 10 corresponding to the occurrence area.

[0137] Display frame G14 may display the current vital signs of a worker in "Mount Takao Area #1," and FIG. 12 shows an example in which "Vital signs check normal." If, for example, a worker is caught in a landslide and some kind of physical abnormality occurs (for example, blood pressure drops due to bleeding), "Vital signs check abnormal" will be displayed in display frame G14. In this case, the user can use the instruction device 400 to request, for example, the dispatch of a rescue team or an ambulance.

[0138] Display frame G15 may display the current location information of the worker in "Mount Takao Area #1" (location information of the wearable device WT worn by the worker). Furthermore, if there is a no-entry area near the worker's current location, display frame G15 may also display information about the no-entry area, as shown in FIG.

[0139] Alert information indicating the occurrence of a landslide may be displayed in the display frame 16. For example, the display frame 16 may display alert information including information indicating the occurrence of a landslide and information about the area where the landslide occurred.

[0140] Furthermore, suppose that the information processing device 100 calculates the volume of sediment caused by the landslide that occurred in the "Mount Takao Area #1" and estimates the type and number of equipment required to remove the sediment from the landslide-affected area that has been newly covered by the landslide. In such a case, the display frame 16 may further display information on the sediment volume, information on the landslide-affected area, and the type and number of equipment required to remove the sediment.

[0141] 10. Operational Procedure of Information Processing Device Next, an operation procedure of the information processing device 100 in the landslide disaster detection process will be described. Fig. 13 is a flowchart showing the operation procedure of the information processing device 100. In the example of Fig. 13, it is assumed that the position information of the sensor device 10 is corrected position information based on RTK positioning.

[0142] The control unit 130 may determine whether or not an area has been designated among the areas AR in which the sensor device 10 is installed (for example, areas AR included in special landslide warning areas) (step S1301). If no area has been designated (step S1301; No), the control unit 130 may wait until an area is designated.

[0143] When an arbitrary area is specified (step S1301; Yes), the acquisition unit 131 may acquire location information (initial value of location information) at the time t0 when the sensor device 10 was installed in that area (step S1302).

[0144] The acquiring unit 131 may also determine whether or not the location information at the current time tx has been acquired from all of the sensor devices 10 installed in the area specified by the user (step S1303). While the acquiring unit 131 has not been able to acquire the location information at the current time tx from all of the sensor devices 10 (step S1303; No), the acquiring unit 131 may wait until the location information at the current time tx has been acquired from all of the sensor devices 10.

[0145] Note that the determination unit 134 may perform a predetermined determination process when a state in which location information (current location of location information) at the current time tx cannot be obtained from all sensor devices 10 continues for a certain period of time, for example, when a state in which location information cannot be obtained from some of the sensor devices 10 installed in an area specified by a user continues for a certain period of time. For example, the determination unit 134 may determine that some of the sensor devices 10 are malfunctioning, or may determine that a landslide may have occurred near some of the sensor devices 10. Furthermore, the notification unit 136 may notify the user of this determination result.

[0146] Returning to the explanation of Figure 13, when location information at the current time tx has been acquired from all sensor devices 10 (step S1303; Yes), the first calculation unit 132 may calculate the relative distance based on the initial value and the current value for all combination patterns that are possible as combinations of two different sensor devices 10 (step S1304).

[0147] The second calculation unit 133 may calculate the standard deviation value at the current time tx based on the relative distance at the current time tx calculated in step S1304 (step S1305).

[0148] The determination unit 134 may determine whether the standard deviation value at the current time tx exceeds the threshold value (step S1306). If the determination unit 134 determines that the standard deviation value at the current time tx does not exceed the threshold value (step S1306; No), the process may return to step S1303.

[0149] If the determination unit 134 determines that the standard deviation value at the current time tx exceeds the threshold value (step S1306; Yes), it may detect that a landslide disaster has occurred.

[0150] [11. System Processing Procedures] Next, the operation procedure of the overall system Sy will be described. Fig. 14 is a sequence diagram showing an example of the flow of information on landslide disasters being provided to users in the overall system Sy.

[0151] The sensor device 10 may transmit position information (corrected position information) to the information processing device 100 (step S1401). The information processing device 100 may receive the position information (step S1402).

[0152] The information processing device 100 may execute a landslide disaster detection process based on the received location information (step S1403). A specific example of the landslide disaster detection process has been described with reference to Fig. 13 and so forth, and therefore will not be repeated here.

[0153] When the information processing device 100 detects the occurrence of a landslide disaster, it may transmit alert information indicating the occurrence of the landslide disaster to the display control device 200 (step S1404). The display control device 200 may receive the alert information indicating the occurrence of the landslide disaster (step S1405).

[0154] The display control device 200 may transmit the alert information to the instruction device 400 (step S1406). The instruction device 400 may receive the alert information (step S1407).

[0155] Here, the user who has confirmed the alert information from the instruction device 400 may wish to check the details of the landslide disaster site. For example, the user may wish to check the details of the landslide disaster site via the alert screen and operate the instruction device 400.

[0156] In this case, the instruction device 400 may transmit a request to view the alert screen to the display control device 200 (step S1408).

[0157] The display control device 200 may receive a request to view an alert screen (step S1409), and upon receiving the request to view an alert screen, may perform processing to generate an alert screen in the following manner.

[0158] The alert screen generated when a landslide occurs may be the screen G1 described in Fig. 12. Therefore, the display control device 200 may acquire vital sign information from the wearable device WT (step S1410). For example, if a worker is present in the area where the landslide occurred, the display control device 200 may acquire the current vital sign information from the wearable device WT of the worker.

[0159] Furthermore, the display control device 200 may acquire weather information from the weather information DA1 (step S1411). For example, the display control device 200 may acquire current weather information for an area where a landslide has occurred.

[0160] The display control device 200 may generate an alert screen on which the alert information acquired in step S1405, the vital sign information acquired in step S1410, the weather information acquired in step S1411, etc. are displayed, and transmit the generated alert screen to the instruction device 400 (step S1412). Note that if the display control device 200 is able to further receive information on the volume of sediment, information on the landslide disaster area (no-entry zone), and the type and number of equipment required for sediment removal from the information processing device 100, it may generate an alert screen on which this information is further displayed.

[0161] The instruction device 400 may receive the alert screen and display the received alert screen on its own display screen (step S1413).

[0162] FIG. 15 is a sequence diagram showing an example of the flow in which a three-dimensional map, which is map data, is provided to a user in the overall system Sy. FIG. 15 shows a scene in which a three-dimensional map based on three-dimensional point cloud data of a location in accordance with a user's instruction is provided. For example, when a user receives information about a landslide disaster in the flow shown in FIG. 14, the user may want to know more about the situation at the site of the landslide disaster in order to request a dispatch for removal of the landslide. In such a case, the user may request a dispatch to send an air vehicle FO to the site of the landslide disaster in order to learn the situation at the site.

[0163] Therefore, the instruction device 400 may transmit a request to dispatch the air vehicle FO to the air vehicle control device 500 in accordance with the instruction content input by the user (step S1501). The instruction content may include, for example, flight instructions indicating the flight path of the air vehicle FO and acquisition instructions indicating the location to be scanned in order to acquire three-dimensional point cloud data.

[0164] When the aircraft control device 500 receives the dispatch request (step S1502), it may control the aircraft FO so that it operates in accordance with the instructions input by the user (step S1503).

[0165] In this case, the air vehicle FO may fly a flight path under the control of the air vehicle control device 500 and scan the location to be scanned from above the location. Then, the air vehicle FO may generate three-dimensional point cloud data of the location to be scanned and transmit the generated three-dimensional point cloud data to the air vehicle control device 500 (step S1504).

[0166] When receiving the three-dimensional point cloud data, the aircraft control device 500 may transmit the received three-dimensional point cloud data to the information processing device 100 (step S1505).

[0167] The information processing device 100 may receive the three-dimensional point cloud data (step S1506). Then, the information processing device 100 may generate a three-dimensional map from the received three-dimensional point cloud data and transmit the generated three-dimensional map to the display control device 200 (step S1507).

[0168] The display control device 200 may receive the three-dimensional map (step S1508). Furthermore, the display control device 200 may transmit the three-dimensional map to the instruction device 400 (step S5109). For example, the display control device 200 may transmit the screen G1 inserted into the display frame G13 to the instruction device 400.

[0169] Upon receiving the three-dimensional map, the instruction device 400 may display the received three-dimensional map on the display screen of the device itself (step S1510).

[0170] Here, the user can specify a measurement area on the three-dimensional map displayed in step S1510, thereby causing the information processing device 100 to calculate the volume of sediment within the measurement area. For example, the user can refer to the three-dimensional map and specify a measurement area that surrounds the location where the landslide occurred.

[0171] In such a case, the information processing device 100 may calculate the volume of sediment within the measurement area based on three-dimensional point cloud data (first three-dimensional point cloud data) of the scanned location before the landslide occurred and three-dimensional point cloud data (second three-dimensional point cloud data) generated by the air vehicle FO for the scanned location at the current time (i.e., the present time after the landslide occurred). For example, the information processing device 100 may match the relative positions of the first three-dimensional point cloud data and the second three-dimensional point cloud data, and calculate the difference between the topography before the landslide occurred and the topography after the landslide occurred based on the matching result. The information processing device 100 may then determine that the difference in topography is a sediment portion caused by the landslide, and calculate the volume of sediment corresponding to the sediment portion based on the three-dimensional point cloud data corresponding to the sediment portion.

[0172] In addition, the information processing device 100 may identify the geographical area that has been newly covered by sediment due to a landslide based on the three-dimensional point cloud data, and may estimate the type and number of equipment required to remove the sediment based on the geographical area and the volume of sediment.

[0173] [12. Hardware Configuration] An apparatus according to an embodiment (for example, an information processing apparatus 100 or a display control apparatus) may be realized by, for example, a computer 1000 configured as shown in Fig. 16. Fig. 16 is a hardware configuration diagram showing an example of a computer that realizes the functions of an apparatus according to an embodiment. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0174] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0175] The HDD 1400 stores programs executed by the CPU 1100, data used by these programs, etc. The communication interface 1500 receives data from other devices via a predetermined communication network and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network.

[0176] The CPU 1100 controls an output device such as a display and an input device such as a keyboard via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. The CPU 1100 also outputs generated data to the output device via the input / output interface 1600.

[0177] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1200. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1200 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0178] For example, when the computer 1000 functions as the information processing device 100 according to the embodiment, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200 to realize the functions of the control unit 130. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined communication network.

[0179] [13. Other] Furthermore, among the processes described in each of the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0180] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0181] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0182] Although some of the embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be implemented in other forms that include the aspects described in the "present invention" section and that have been modified and improved in various ways based on the knowledge of those skilled in the art. [Explanation of symbols]

[0183] 10 Sensor device 20 Reference station 30 Distribution Device 40 Management device 100 Information processing device 131 Acquisition Department 132 First Calculation Department 133 Second calculation part 134 Judgment section 135 Estimation Department 136 Notification Department 200 Display control device 231 First Receiving Unit 232 Second Receiving Unit 233 Display control unit 400 Indicating device 500 Aircraft control device FO flying vehicle Sy Whole System Sy1 First System Sy2 Second System

Claims

1. an acquisition unit that acquires position information detected by a first sensor device, a second sensor device, and a third sensor device present in a predetermined area; a first calculation unit that calculates a first relative distance between the first sensor device and the second sensor device, a second relative distance between the first sensor device and the third sensor device, and a third relative distance between the second sensor device and the third sensor device based on the acquired position information; a second calculation unit that calculates a value related to the first relative distance, a value related to the second relative distance, and a value related to the third relative distance; a determination unit that determines whether any one of the value related to the first relative distance, the value related to the second relative distance, and the value related to the third relative distance exceeds a predetermined threshold; Equipped with the acquisition unit sequentially acquires position information of each of the plurality of sensor devices, including the first sensor device, the second sensor device, and the third sensor device, in response to the position information of each of the plurality of sensor devices being calculated in time series; the first calculation unit calculates, for all combination patterns that are established as combinations of two different sensor devices among the plurality of sensor devices, a relative distance between the two sensor devices in time series based on the position information of each of the two sensor devices included in the combination pattern; one of the position information of each of the two sensor devices is an initial value indicating position information at a predetermined time point defined as the start of a time series, and the other of the position information of each of the two sensor devices is a current value indicating position information at a current time point that is later than the predetermined time point in the time series; the second calculation unit calculates values ​​related to the relative distance in time series based on the relative distances calculated for all of the combination patterns; the determination unit determines whether or not the value related to the relative distance exceeds the predetermined threshold value. Information processing system.

2. further comprising an event determination unit that determines whether an event has occurred; the acquisition unit acquires position information of each of the plurality of sensor devices as three-dimensional position information; the first calculation unit calculates the relative distance as a straight-line distance based on the three-dimensional position information, the event determination unit determines that an event has occurred in the predetermined area when the determination unit determines that the value related to the relative distance exceeds the predetermined threshold value; The information processing system according to claim 1 .

3. The value for the relative distance is a standard deviation value.

3. The information processing system according to claim 1.

4. an estimation unit that estimates an occurrence area where the event has occurred based on a difference between position information of each of the plurality of sensor devices after it has been determined by the event determination unit that the event has occurred and position information of each of the plurality of sensor devices before it has been determined that the event has occurred; The information processing system according to claim 2 .

5. a notification unit configured to, when it is determined that the event has occurred, notify one or more devices not included in the information processing system of information about the event that has occurred and information about the area where the event has occurred; The information processing system according to claim 4 .

6. the information processing system is communicably connected to a display control system that displays the occurrence of the event, The display control system includes: a first receiving unit that receives information about the event that has occurred and information about the event occurrence area from the information processing system; a second receiving unit that receives rainfall data measured by a rainfall sensor installed in an area corresponding to the occurrence area; a display control unit that displays information about the event that has occurred, information about the event occurrence area, and the rainfall data together with map data; Equipped with The information processing system according to claim 5 .

7. the acquiring unit acquires, as the position information, position information calculated by a real-time kinematic positioning method; The information processing system according to claim 1 .

8. an acquisition step of acquiring position information detected by each of a first sensor device, a second sensor device, and a third sensor device present in a predetermined area; a first calculation step of calculating a first relative distance between the first sensor device and the second sensor device, a second relative distance between the first sensor device and the third sensor device, and a third relative distance between the second sensor device and the third sensor device based on the acquired position information; a second calculation step of calculating a value related to the first relative distance, a value related to the second relative distance, and a value related to the third relative distance; a determination step of determining whether any one of the value related to the first relative distance, the value related to the second relative distance, and the value related to the third relative distance exceeds a predetermined threshold; on the computer, the acquiring step sequentially acquires position information of each of a plurality of sensor devices, including the first sensor device, the second sensor device, and the third sensor device, in response to position information of each of the plurality of sensor devices being calculated in time series; the first calculation step calculates, for all combination patterns that are established as combinations of two different sensor devices among the plurality of sensor devices, a relative distance between the two sensor devices in time series based on the position information of each of the two sensor devices included in the combination pattern; one of the position information of each of the two sensor devices is an initial value indicating position information at a predetermined time point defined as the start of a time series, and the other of the position information of each of the two sensor devices is a current value indicating position information at a current time point that is later than the predetermined time point in the time series; the second calculation step calculates values ​​related to the relative distance in time series based on the relative distances calculated for all of the combination patterns; the determining step determines whether the value relating to the relative distance exceeds the predetermined threshold value. program.

9. A system including a reference station corresponding to a predetermined area, a sensor device, and an information processing system, The sensor device includes: There are a plurality of such devices in the predetermined area, The information processing system includes: an acquisition unit that acquires, as position information detected by a plurality of sensor devices present in the predetermined area, position information calculated based on correction information including coordinate information of the reference station and information based on satellite signals received by the reference station; a first calculation unit that calculates a relative distance between two different sensor devices among the plurality of sensor devices; a second calculation unit that calculates a value related to the calculated relative distance; a determination unit that determines whether the calculated value related to the relative distance exceeds a predetermined threshold; Equipped with the acquiring unit sequentially acquires position information of each of the plurality of sensor devices, including a first sensor device, a second sensor device, and a third sensor device, in response to the position information of each of the plurality of sensor devices being calculated in time series; the first calculation unit calculates, for all combination patterns that are established as combinations of two different sensor devices among the plurality of sensor devices, a relative distance between the two sensor devices in time series based on the position information of each of the two sensor devices included in the combination pattern; one of the position information of each of the two sensor devices is an initial value indicating position information at a predetermined time point defined as the start of a time series, and the other of the position information of each of the two sensor devices is a current value indicating position information at a current time point that is later than the predetermined time point in the time series; the second calculation unit calculates values ​​related to the relative distance in time series based on the relative distances calculated for all of the combination patterns; the determination unit determines whether or not the value related to the relative distance exceeds the predetermined threshold value. system.

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