JP7778124B2 - Information processing system, program and system - Google Patents

Description

The present invention relates to an information processing system, a program, and a system.

In recent years, technologies have been proposed to monitor the occurrence of natural disasters.

For example, Patent Document 1 discloses a system that monitors slope displacement based on GPS (Global Positioning System) data output by a reference station installed outside the slope and GPS data output by a GPS station installed inside the slope.

Japanese Patent Application Laid-Open No. 2004-144623

There is a need to improve the accuracy of detecting event occurrences.

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.

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

Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Note that in this specification and drawings, components having substantially the same functional configuration will be assigned the same reference numerals, and redundant explanations will be omitted.

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

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.

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

The inventors of the present invention therefore believed that by installing multiple sensor devices on land where landslides are likely to occur (such as 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.

In other words, the information processing related to the proposed technology of the present invention (hereinafter referred to as "information processing related to an 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, the standard deviation of the difference calculation results obtained by the brute-force calculation is found, and if the standard deviation value changes to or exceeds a threshold value, a landslide is detected as having occurred.

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 with 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.

Figure 1 also shows the overall system Sy, which includes 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.

First, we will explain the first system Sy1. The first system Sy1 corresponds to the 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 backend system 100.

The sensor device 10 may be a portable information processing terminal that can be installed anywhere 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 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 fixed and installed in a location depending on the user's purpose.

The sensor device 10 may also receive satellite signals. Specifically, the sensor device 10 may receive GNSS (Global Navigation Satellite System) signals from 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.

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 GNSS signals. Then, the sensor device 10 may receive correction information distributed from the distribution device 30, which will be 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. In other words, 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 performing RTK calculation. The RTK calculation may be performed using a conventional method.

Furthermore, to realize the information processing according to the embodiment, multiple 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 multiple sensor devices 10. When there is no need 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 such. Note that time synchronization may be performed to match the time among the multiple sensor devices 10.

The reference station 20 may function as a reference station in the 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.

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 distribution 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, etc.

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 installed appropriately at any location (for example, a location within the area where the sensor device 10 is installed) by any operator or the like.

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 signals received by the reference station 20. The broadcasting device 30 may generate correction information for correcting errors in positioning by the sensor device 10 based on the information on the known coordinates and GNSS signals of the reference station 20 to be processed. The correction information may include, for example, information on the known coordinates of the reference station 20 and information on the phase of the carrier wave from the GNSS satellite.

The distribution 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 optionally include information necessary for the RTK calculation by the sensor device 10.

Here, we will explain positioning using RTK calculations that use correction information. First, the sensor device 10 may acquire rough position information (approximate position information) of its own device through positioning based on GNSS signals. The broadcasting device 30 may generate correction information that includes 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 through RTK calculations that use the correction information. In other words, the sensor device 10 may calculate information (corrected position information) that corrects the approximate position information using the correction information through RTK calculations.

The sensor device 10 may transmit the corrected location information to the management device 40. The management device 40 may also transmit the corrected location information to the backend system 100.

The management device 40 may act as an intermediary in the transmission and reception of 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).

The first system Sy1 does not need to have a management device 40, and the corrected location information may be sent directly from the sensor device 10 to the backend system 100. Alternatively, a configuration may be adopted in which the sensor device 10 sends the corrected location information to the distribution device 30, and the distribution device 30 sends the corrected location information to the backend system 100.

The backend system 100 corresponds to the information processing system according to the embodiment. The backend system 100 may be composed of, for example, 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 the information processing device 100.

The information processing device 100 executes back-end processing among the information processing according to the embodiment. The main back-end processing may include landslide detection processing that detects the occurrence of landslides in real time based on position information acquired from the sensor device 10, and processing 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 three-dimensional point cloud data via the air vehicle control device 500.

Furthermore, when the information processing device 100 detects the occurrence of a landslide, it may notify the front-end system 200 or the indicating device 400 of alert information indicating the occurrence of the landslide. The alert information may include at least information indicating the occurrence of the landslide and information about the area in which the landslide occurred.

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

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 via API integration over the Internet.

Special landslide disaster area information DA2 is information indicating areas of land that are deemed to pose a risk to the lives or bodies of residents in the event of a landslide, and may be provided by local governments. Special landslide disaster area information DA2 may be provided to the front-end system 200 from an external device belonging to each local government via API integration via the Internet.

In addition, although not shown in Figure 1, information on no-entry areas that exist in various locations (for example, information on no-entry areas in special landslide disaster zones) may also be uploaded to the front-end system 200.

The wearable device WT is an information processing terminal worn by a worker at a work site, and may be equipped with a sensor capable of detecting the worker's vital signs. The wearable device WT may also provide the worker's vital signs to the front-end system 200 through API integration via a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation: fifth generation mobile communication system).

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

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 the user using a specified screen. For example, the display control device 200 may display on the user's instruction device 400 information on the area where the sensor device 10 is installed, information indicating the occurrence of a landslide, information on 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.

Note that the user in this 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.

Next, we will explain the other devices included in the overall system Sy: the flying object FO, the instruction device 400, and the flying object control device 500.

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 that includes a positioning module. In other words, the air vehicle FO may obtain corrected position information indicating the position of its own air vehicle through RTK calculation using correction information. The RTK calculation may be performed using a conventionally known method.

The air vehicle FO and the sensor device 10 may also be separate devices. That is, a user may retrofit a sensor device 10 to a pre-made air vehicle FO, causing the air vehicle FO to measure its own position. On the other hand, the air vehicle FO and the sensor device 10 may also be integrated into one device. That is, a user may cause an air vehicle FO that has one function similar to that of the sensor device 10 to measure its own position.

Furthermore, the air vehicle FO may be equipped with a point cloud data generation module with LiDAR (Light Detection and Ranging) functionality. In other words, the air vehicle FO may use positioning data obtained by the above-mentioned RTK positioning function (positioning module) to determine its own position when generating point cloud data (three-dimensional point cloud data).

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 pre-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 functionality as the point cloud data generation module to generate point cloud data.

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

The instruction device 400 inputs instruction information received from the user into the aircraft control device 500. Here, the user who issues flight instructions to the aircraft FO or indicates the location of the target for which point cloud data should be acquired may be the organization U or management business operator M described above. Figure 1 shows instruction device 400-1 as an example of an instruction device 400 used by organization U, and instruction device 400-2 as an example of an instruction device 400 used by management business operator M.

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 input instructions. 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 flight path information.

The aircraft control device 500 also controls the aircraft FO to generate point cloud data for the position of the target defined in the instruction information. The aircraft FO is equipped with a point cloud data generation module (e.g., LiDAR functionality), and therefore generates three-dimensional point cloud data for the position of the target defined in the instruction information based on its own position determined by RTK calculation. For example, the aircraft 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).

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

[3. Acquisition of location information]
When detecting the occurrence of a landslide disaster, the information processing device 100 acquires the 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. Here, the acquisition of the corrected position information will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the position information acquisition process.

Figure 2 shows a scene in which corrected position information is acquired from each sensor device 10 when multiple sensor devices 10 are installed on the slope of a mountain within an area AR included in a special landslide warning zone. A reference station 20 is also installed within 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 Figure 2.

The sensor device 10 may calculate location information indicating its own location (installed location) using GNSS positioning based on the GNSS signals. This 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. The sensor device 10 may transmit the approximate location information along with information about the received GNSS signals to the broadcasting device 30 (step S21).

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

In the above example, the sensor device 10 calculates the approximate location information using GNSS positioning, but the distribution device 30 may also 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 distribution device 30 may calculate the approximate location information of the sensor device 10 using GNSS positioning based on the GNSS signal received from the sensor device 10.

Next, the distribution device 30 may transmit a distribution request to the selected reference station 20 requesting distribution of the GNSS signal (step S22). The reference station 20 may constantly receive GNSS signals. In other words, 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).

The reference station 20 to be processed may continue to transmit GNSS signals to the distribution device 30 after receiving a distribution request. The reference station 20 may also constantly push GNSS signals to the distribution device 30. In other words, the reference station 20 may transmit GNSS signals 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 signals.

The distribution device 30 may generate correction information based on the GNSS signal received from the reference station 20 to be processed (step S24). For example, the distribution device 30 may calculate the position coordinates of the reference station 20 by GNSS positioning based on the GNSS signal received from the reference station 20 to be processed, and generate correction information by determining the difference between the calculated position coordinates and known coordinates of the reference station 20 (e.g., stored in advance in the distribution device 30). The correction information is used to make real-time corrections to the approximate position information of the sensor device 10.

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

The distribution device 30 may transmit the generated correction information to the sensor device 10 that transmitted the approximate location information (step S25).

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

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

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.

(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.

(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.

(Regarding the control unit 13)
The control unit 13 may be realized by a central processing unit (CPU), a graphics processing unit (GPU), a micro processing unit (MPU), 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 application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

The control unit 13 may have a first receiving unit 13a, an approximate position calculation unit 13b, a first transmitting unit 13c, a second receiving unit 13d, a correction 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 be other configurations as long as they perform the information processing described below. Furthermore, the connection relationships between the processing units of the control unit 13 are not limited to the connection relationships shown in FIG. 3 and may be other connection relationships.

(Regarding the first receiving unit 13a)
The first receiver 13a may correspond to a GNSS receiver and antenna compatible with RTK and may receive GNSS signals. The first receiver 13a may output the received GNSS signals to the approximate position calculator 13b.

(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.

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

(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 store the correction information in the storage unit 12.

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

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

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.

(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 via a wired or wireless connection, and transmits and receives information between the sensor device 10, the management device 40, the display control device 200, the instruction device 400, and the aircraft control device 500.

(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.

(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.

The control unit 130 may have 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. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 4, and may have other configurations as long as they perform the information processing described below. Furthermore, the connection relationships between the processing units of the control unit 130 are not limited to the connection relationships shown in FIG. 4, and may be other connection relationships.

(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 the 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.

For example, the first sensor device 10-1, the second sensor device 10-2, the third sensor device 10-3, ..., the nth sensor device 10-n calculates corrected position information at a predetermined cycle by performing RTK calculations at a predetermined cycle. 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 cycle.

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 air vehicle FO using a LiDAR function.

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

(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.

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.

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

The first calculation unit 132 may sequentially calculate the relative distance between two different sensor devices 10 in response to the successive 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.

(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 a first relative distance, a value related to a second relative distance, and a value related to a third relative distance.

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 point in time and a first relative distance calculated at a subsequent point in time, or may calculate the proportion of that 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 point in time and a second relative distance calculated at a subsequent point in time, or may calculate the proportion of that 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 point in time and a third relative distance calculated at a subsequent point in time, or may calculate the proportion of that difference.

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

(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.

(Regarding the estimation unit 135)
The estimation unit 135 may estimate an occurrence area in which an event has occurred. For example, the estimation unit 135 may estimate an occurrence area in which a landslide has occurred. For example, the estimation unit 135 may estimate the occurrence area in which 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 was determined that a landslide has occurred.

Furthermore, according to the information processing device 100, the volume of sediment may be calculated 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 landslide disaster occurred) and second three-dimensional point cloud data from a second period (e.g., after the landslide disaster occurred). In this case, the estimation unit 135 may also estimate the type and number of equipment required to remove sediment from areas affected by the volume of sediment (geographical areas newly covered by sediment due to the landslide disaster).

(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.

The notification unit 137 may also output information about the geographical area newly covered by sediment due to a landslide (landslide area) to the display control device 200 so that the user is notified.

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

In Figure 5, the 10 sensor devices 10 specifically refer to the first sensor device 10-1, second sensor device 10-2, third sensor device 10-3, fourth sensor device 10-4, fifth sensor device 10-5, sixth sensor device 10-6, seventh sensor device 10-7, eighth sensor device 10-8, ninth sensor device 10-9, and tenth sensor device 10-10.

As shown in FIG. 5 , the corrected position information (longitude, latitude, altitude) at time t0 when these 10 sensor devices 10 are installed is used 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 used 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.

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.

[7. Specific examples of landslide detection logic]
Next, the logic of the landslide disaster detection process will be described 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 described in Figures 6 and 7. Figure 6 is a diagram (1) showing a specific example of the landslide disaster detection logic.

In the example of FIG. 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.

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

Once the relative distances have been 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.

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.

While Figure 6 conceptually shows location information such as the initial value PT1 of the location information and the current value PT2 of the location information, Figure 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. Figure 7 is a diagram (2) showing a specific example of landslide detection logic. Figure 7 shows an example focusing on a situation in which, for all combinations 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).

Figure 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.

As explained above, the position information of the sensor device 10 is sequentially acquired according to the time series since the sensor device 10 was installed. 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 thought 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 a sensor device 10 installed near the location where the landslide occurred, and therefore a large change may also occur 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 occurred will be significantly different from the standard deviation values at each time tx before the landslide occurred. 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 Figure 8.

Figure 8 explains an example of detecting the occurrence of a landslide disaster in the logic of the landslide disaster detection process. Figure 8 is a diagram (3) showing a specific example of the landslide disaster detection logic. Figure 8 shows an example focusing on a scene in which, for all combinations 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.

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

Here, for example, suppose 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.

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

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

8. Configuration of display control device
The display control device 200 according to the 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 the 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.

(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 between the information processing device 100, the instruction device 400, and the wearable terminal WT.

(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 the 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.

(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 FPGA, for example.

The control unit 230 may have a first receiving unit 231, a second receiving unit 232, and a display control unit 233. Note that the internal configuration of the control unit 230 is not limited to the configuration shown in FIG. 9 and may have other configurations as long as they perform the information processing described below. Furthermore, the connection relationships between the processing units of the control unit 230 are not limited to the connection relationships shown in FIG. 9 and may be other connection relationships.

(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 and information about the area where the landslide occurred from the information processing device 100.

The first receiving unit 231 may also receive information on landslide areas and three-dimensional maps generated based on three-dimensional point cloud data from the information processing device 100. The first receiving unit 231 may also receive vital sign information of workers from the wearable device WT.

(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.

(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.

The map data may be aerial images captured by an air vehicle (FO), or a three-dimensional map obtained based on three-dimensional point cloud data generated by the air vehicle (FO).

[9. Display Control Screen]
The display control unit 233 may cause the indicating 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 indicating 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.

Figure 10 is a diagram showing an example of a display control screen. According to the example of Figure 10, screen G1 may be provided with multiple display frames. As an example, screen G1 may be provided with six display frames, G11 to G16.

In the example of FIG. 10, the display frame G11 may display the name of the area designated by the user. The display frame G12 may display weather information for the area designated by the user. The display frame G13 may display map data for the area designated by the user. The area here may be, for example, a designated area designated by the user from within the area AR included in the special landslide warning zone.

Display frame G14 may display vital signs of a worker who is present in the area designated by the user. Display frame G15 may display location information of a worker who is present in the area designated by the user (location information of the wearable device WT worn by the worker). Display frame G16 may display various information related to the occurrence of a landslide disaster, for example, as event information.

Here, screen G1 may display information corresponding to both before and after the occurrence of an event. For example, if no landslide has occurred, screen G1 may display information corresponding to the situation before the landslide, and if a landslide has occurred, screen G1 may display information corresponding to the situation after the landslide. Below, we will explain an example of the display content corresponding to each situation.

First, we will explain an example of the display content before a landslide occurs. Figure 11 is a diagram showing an example of the display content before a landslide occurs. Figure 11 shows an example of the display content before a landslide occurs when a user specifies an area called "Mount Takao Area #1" from the areas AR assigned on the map data.

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 "Mount Takao Area #1," with FIG. 11 showing an example in which "Sunny" is displayed. Furthermore, the display frame G12 may also display current rainfall data for "Mount Takao Area #1."

Display frame G13 may display current (pre-landslide) map data for "Mount Takao Area #1." For example, if the aircraft FO is currently flying over "Mount Takao Area #1," aerial footage 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. 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.

Furthermore, as shown in FIG. 11, the map data in the display frame G13 may display, in association with the location where the sensor device 10 is installed, that there are no abnormalities in the positional changes of the sensor device 10 and that the changes are normal (i.e., no landslides have occurred).

Display frame G14 may display the current vital signs of a worker in "Mount Takao Area #1", and Figure 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" (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 Figure 11.

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

Next, we will explain an example of the display content after a landslide occurs. Figure 12 is a diagram showing an example of the display content after a landslide occurs. Figure 12 shows an example of the display content after a landslide occurs when a user specifies an area called "Mount Takao Area #1" from the areas AR assigned on the map data.

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," with FIG. 12 showing an example in which "Rain" is displayed. Furthermore, the display frame G12 may also display current rainfall data for the "Mount Takao Area #1."

Display frame G13 may display current (post-landslide) map data for the "Mount Takao Area #1." For example, if the aircraft FO is currently flying over the "Mount Takao Area #1," aerial footage 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.

Furthermore, as shown in FIG. 12, the map data in the display frame G13 may display an abnormality in the position change of the sensor device 10 (i.e., a possibility that a landslide has 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 area AR near the location where the sixth sensor device 10-6 is installed is the occurrence area where a landslide has occurred. Following this example, information indicating an abnormality may be displayed for the installation location of the sensor device 10 corresponding to the occurrence area.

Display frame G14 may display the current vital signs of a worker in "Mount Takao Area #1," and Figure 12 shows an example in which "No abnormalities in vital signs check" is displayed. For example, if a worker is caught in a landslide and some kind of physical abnormality occurs (for example, a drop in blood pressure due to bleeding), "Abnormalities in vital signs check" will be displayed in display frame G14. In this case, the user can use the instruction device 400 to request the dispatch of, for example, a rescue team or an ambulance.

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, display frame G15 may also display information about the no-entry area, as shown in FIG. 12.

Display frame 16 may display alert information indicating the occurrence of a landslide. For example, display frame 16 may display alert information including information indicating the occurrence of a landslide and information about the area in which the landslide occurred.

Also, assume 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 with sediment due to 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.

10. Operation Procedure of Information Processing Device
Next, the 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.

The control unit 130 may determine whether any area has been designated within the area AR in which the sensor device 10 is installed (e.g., an area AR included in a special landslide warning zone) (step S1301). If no area has been designated (step S1301; No), the control unit 130 may wait until an area is designated.

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

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

The determination unit 134 may perform a predetermined determination process if it has been unable to obtain location information (current location of location information) at the current time tx from all sensor devices 10 for a certain period of time, for example, if it has been unable to obtain location information from some of the sensor devices 10 installed in an area specified by the user for a certain period of time. For example, the determination unit 134 may determine that some of the sensor devices 10 are malfunctioning, or that a landslide may have occurred near some of the sensor devices 10. The notification unit 136 may notify the user of this determination result.

Returning to the explanation of Figure 13, if position 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).

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).

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.

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.

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 providing information on landslide disasters to users in the overall system Sy.

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).

The information processing device 100 may then execute landslide detection processing based on the received location information (step S1403). Specific examples of landslide detection processing have been described in Figure 13 and elsewhere, so they will not be repeated here.

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

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).

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.

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

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

The alert screen generated when a landslide occurs may be screen G1 described in FIG. 12. The display control device 200 may then 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 worker's current vital sign information from the worker's wearable device WT.

The display control device 200 may also acquire weather information from the weather information DA1 (step S1411). For example, the display control device 200 may acquire current weather information for the area where a landslide has occurred.

The display control device 200 may generate an alert screen that displays the alert information acquired in step S1405, the vital signs information acquired in step S1410, the weather information acquired in step S1411, etc., 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 landslide disaster areas (restricted zones), and the type and number of equipment required for sediment removal from the information processing device 100, it may generate an alert screen that further displays this information.

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

Figure 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. Figure 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 instructions is provided. For example, if a user receives information about a landslide disaster in the flow shown in Figure 14, they 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 will 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.

The instruction device 400 may then send a request to the aircraft control device 500 to dispatch the aircraft FO in accordance with the instructions entered by the user (step S1501). The instructions may include, for example, flight instructions indicating the flight path of the aircraft FO, and acquisition instructions indicating the location to be scanned in order to acquire three-dimensional point cloud data.

When the aircraft control device 500 receives a dispatch request (step S1502), it may control the aircraft FO to operate in accordance with the instructions entered by the user (step S1503).

In this case, the air vehicle FO may fly along a flight path under the control of the air vehicle control device 500 and perform a scan of the location to be scanned from above the location. The air vehicle FO may then 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).

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

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).

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

When the instruction device 400 receives the three-dimensional map, it may display the received three-dimensional map on the display screen of its own device (step S1510).

Here, the user can specify a measurement area on the three-dimensional map displayed in step S1510, 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.

In such cases, 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) at the scanned location before the landslide occurred and three-dimensional point cloud data (second three-dimensional point cloud data) generated by the airborne 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 results. 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.

The information processing device 100 may also identify the geographical area newly covered by sediment due to a landslide based on the three-dimensional point cloud data, and estimate the type and number of equipment required to remove the sediment based on the geographical area and the volume of sediment.

12. Hardware Configuration
An apparatus according to an embodiment (e.g., 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, a HDD 1400, a communication interface (I/F) 1500, an input/output interface (I/F) 1600, and a media interface (I/F) 1700.

The CPU 1100 operates based on programs stored in the ROM 1300 or HDD 1400, and controls each component. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, as well as programs that depend on the computer 1000's hardware.

HDD 1400 stores programs executed by CPU 1100 and data used by such programs. Communication interface 1500 receives data from other devices via a specified communication network and sends it to CPU 1100, and transmits data generated by CPU 1100 to other devices via a specified communication network.

The CPU 1100 controls output devices such as displays and input devices such as keyboards via the input/output interface 1600. The CPU 1100 acquires data from input devices via the input/output interface 1600. The CPU 1100 also outputs generated data to output devices via the input/output interface 1600.

Media interface 1700 reads programs or data stored on recording medium 1800 and provides them to CPU 1100 via RAM 1200. CPU 1100 loads the programs from recording medium 1800 onto RAM 1200 via media interface 1700 and executes the loaded programs. 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.

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 specified communications network.

[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.

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

Furthermore, the above embodiments can be combined as appropriate to the extent that the processing content is not contradictory.

The above describes in detail some of the embodiments of the present application based on the drawings, but these are merely examples, and the present invention can be implemented in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the aspects described in the "present invention" section.

REFERENCE SIGNS LIST 10 Sensor device 20 Reference station 30 Distribution device 40 Management device 100 Information processing device 131 Acquisition unit 132 First calculation unit 133 Second calculation unit 134 Determination unit 135 Estimation unit 136 Notification unit 200 Display control device 231 First receiving unit 232 Second receiving unit 233 Display control unit 400 Instruction device 500 Aircraft control device FO Aircraft Sy Overall system Sy1 First system Sy2 Second system

Claims (9)

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 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 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. 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 . The value for the relative distance is a standard deviation value.
3. The information processing system according to claim 1. 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 . 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 . 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;
The information processing system according to claim 5 , comprising: 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 . 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 . 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 .