Flood monitoring device, flood monitoring system, and flood monitoring method

Abstract

To provide a flood monitoring device, a flood monitoring system and a flood monitoring method with which it is possible to calculate the speed of seismic sea waves with good accuracy, without using expensive sensors.SOLUTION: The present invention comprises: an acquisition unit that acquires a captured image having been captured by an imaging device that captures the image of a buoy on the sea surface when seismic sea waves occur among buoy-type sensors having a buoy floating on the sea surface and an unwinding mechanism that is connected to the buoy by a connecting line and capable of unwinding and pulling back the connecting line, and that is fixed to the bottom or near the bottom of the sea; and a first calculation unit that derives, from the captured image, an apex height that is the height from the water surface of a section of the buoy appearing on the water surface, calculates buoyancy acting upon the buoy on the basis of the apex height, and calculates tension on the basis of a relationship of balance of the gravity and buoyance acting upon the buoy and a tension at the junction of the buoy and the connecting line, the first calculation unit further calculating the length of the connecting line from the tension in sequence of time, as the water depth from a position at which the buoy is afloat, and calculating the speed of the seismic sea waves from the water depth in sequence of time.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to a flood monitoring device, a flood monitoring system, and a flood monitoring method.

Background Art

[0002] In recent years, with the increase in natural disasters such as heavy rain and earthquakes, flood damage has occurred frequently due to inundation of seawater or river water caused by tsunamis or floods in areas near the sea or rivers.

[0003] As a technique for monitoring such floods, a method of measuring the river water level (water depth) by analyzing the difference from the normal monitoring image of the monitoring image of a river monitoring camera is disclosed (for example, Patent Document 1). In addition, a method of distributing actual flood information that changes every moment due to the influence of the water level, rainfall, etc. to promote evacuation is disclosed (for example, Patent Documents 2 and 3).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the conventional technology, although the water depth (water level) can be measured, the speed of the tsunami cannot be measured, and there is a problem that the information for predicting the flood area is insufficient and the accuracy of the prediction is not high. In addition, when a large number of expensive sensors for measuring the sea water level etc. are arranged in the sea, there is a problem that the cost increases.

[0006] The present invention has been made in view of the above, and aims to provide a flood monitoring device, a flood monitoring system, and a flood monitoring method that can accurately calculate the speed of a tsunami without using expensive sensors. [Means for solving the problem]

[0007] To solve the above-mentioned problems and achieve the objective, the present invention is characterized by comprising: an acquisition unit that acquires an image captured by an imaging device that images the buoy on the sea surface in the event of a tsunami, the buoy-type sensor having a buoy floating on the sea surface and an extension mechanism fixed to or near the seabed that is connected to the buoy by a connecting wire and is capable of extending and retracting the connecting wire, and the acquisition unit that acquires an image captured by an imaging device that images the buoy on the sea surface in the event of a tsunami, and a first calculation unit that derives the apex height, which is the height from the water surface of the portion of the buoy that is visible above the water surface, from the image captured, calculates the buoyancy acting on the buoy based on the apex height, calculates the tension based on the relationship between gravity acting on the buoy, the buoyancy, and the tension at the connection point between the buoy and the connecting wire, calculates the length of the connecting wire from the tension as the water depth from the position where the buoy is floating in a time series, and calculates the speed of the tsunami from the water depth in a time series. [Effects of the Invention]

[0008] According to the present invention, the speed of a tsunami can be calculated with high accuracy without using expensive sensors. [Brief explanation of the drawing]

[0009] [Figure 1] Figure 1 is a diagram illustrating the overall configuration of a flood monitoring system according to an embodiment. [Figure 2] Figure 2 illustrates the forces acting on the buoy. [Figure 3] Figure 3 illustrates the frequency, wavelength, and velocity of a tsunami. [Figure 4] Figure 4 shows an example of the hardware configuration of the predictive management server according to the embodiment. [Figure 5]Figure 5 shows an example of the hardware configuration of an information terminal according to the present invention. [Figure 6] Figure 6 shows an example of the configuration of the functional blocks of the predictive management server according to the embodiment. [Figure 7] Figure 7 is a flowchart showing an example of the water depth calculation process of the predictive management server according to the embodiment. [Figure 8] Figure 8 shows an example of a state in which evacuation routes are displayed on map information in an information terminal according to the embodiment. [Figure 9] Figure 9 shows an example of a state in which the predicted flood area and detour routes for evacuation are displayed on the map information of an information terminal according to the embodiment. [Modes for carrying out the invention]

[0010] Embodiments of the flood monitoring device, flood monitoring system, and flood monitoring method according to the present invention will be described in detail below with reference to the drawings. Furthermore, the present invention is not limited by the following embodiments, and the components in the following embodiments include those that are easily conceivable by those skilled in the art, substantially identical, and so-called equivalents. Moreover, various omissions, substitutions, modifications, and combinations of components can be made without departing from the spirit of the following embodiments.

[0011] Computer software refers to programs related to the operation of a computer, and other information used for computer processing that is similar to a program (hereinafter, computer software is referred to as "software"). Application software is a general term for software used to perform specific tasks, within the classification of software. On the other hand, an operating system (OS) is software that controls the computer and enables application software and other programs to utilize computer resources. The operating system performs basic computer management and control, such as input / output control, management of hardware such as memory and hard disks, and process management. Application software operates by utilizing the functions provided by the operating system. A program is a set of instructions for a computer, combined to produce a specific result. Something similar to a program is something that cannot be called a program because it is not a direct instruction to the computer, but has similar properties to a program in that it defines the processing of the computer. For example, a data structure (the logical structure of data, represented by the interrelationships between data elements) falls under the category of something similar to a program.

[0012] (Overall configuration of the flood monitoring system) Figure 1 is a diagram illustrating the overall configuration of the flood monitoring system according to this embodiment. The overall configuration of the flood monitoring system 1 according to this embodiment will be described with reference to Figure 1.

[0013] The flood monitoring system 1 shown in Figure 1 is a system that calculates the water depth of the sea and the velocity of tsunamis to predict the area of ​​inundation caused by floods in the event of a flood. In this embodiment, the operation of the flood monitoring system 1 in which it calculates the water depth and the velocity of tsunamis in the sea and predicts the area of ​​inundation in the event of a flood will be described. As shown in Figure 1, the flood monitoring system 1 includes a prediction management server 10 (flood monitoring device), multiple buoy-type sensors 20 installed in rivers and the sea, and a monitoring camera 30.

[0014] The prediction management server 10 is a server device that calculates the sea depth and the speed of a tsunami based on the captured image of the buoy-type sensor 20 captured by the surveillance camera 30, and predicts the inundation area due to flooding when flooding occurs.

[0015] A plurality of buoy-type sensors 20 are installed in the sea, and by being imaged by the surveillance camera 30, they contribute to the calculation of the sea depth and the speed of the tsunami by the prediction management server 10. As shown in FIG. 1, the buoy-type sensor 20 includes a buoy 21, a wire pay-out mechanism 22, and a wire 23 (connection line).

[0016] The buoy 21 is a buoy that is connected to a wire pay-out mechanism 22 installed on the seabed or the like via the wire 23 and is floated on the sea surface. On the surface of the buoy 21, as shown in FIG. 1, marks 21a such as characters, figures, or symbols for deriving the inclination or the like of the buoy 21 are attached.

[0017] The wire pay-out mechanism 22 includes a reel containing a clock spring around which the wire 23 is wound, and is connected to the buoy 21 via the wire 23 drawn out from the reel. In response to the force received from the buoy 21 due to the movement of the buoy 21 on the water surface, the wire 23 is payed out from the reel, and as a result, the force for pulling back the wire 23 generated by the clock spring is used to generate tension in the wire 23. The wire pay-out mechanism 22 is fixedly installed, for example, on the seabed or a bridge near the seabed.

[0018] Wire 23 is a connecting wire that connects the buoy 21 and the wire feeding mechanism 22, and transmits the tension generated by the wire feeding mechanism 22 to the buoy 21. For example, an elastic body such as a coil spring is connected to one part of wire 23, and the elastic body stretches by a predetermined length according to the spring constant of the elastic body and the tension generated by the wire feeding mechanism 22. Therefore, the length of wire 23 and the tension generated in wire 23 (the combined force of the tension generated by the wire feeding mechanism 22 and the tension from the elastic body connected to one part of wire 23) are related by a predetermined relational equation, and if one is determined, the other can be derived. The relationship between the length of wire 23 and the tension generated in wire 23 may be obtained experimentally in advance. In principle, the longer the length of wire 23, the greater the tension. Note that wire 23 is not limited to metal, but may be made of resin, for example.

[0019] The surveillance camera 30 is an imaging device that captures images of multiple buoys 21 floating on the sea surface. The surveillance camera 30 wirelessly transmits the captured images to the information terminal 40. Examples of wireless communication standards include 3G, LTE (Long Term Evolution), 4G, 5G, or Wi-Fi (registered trademark) (Wireless Fidelity).

[0020] The information terminal 40 is an information processing device such as a smartphone, tablet, or PC (Personal Computer) on which an application (hereinafter sometimes simply referred to as "the app") is installed that receives information such as predicted flood areas predicted by the prediction management server 10 and displays it on the map information. The app installed on the information terminal 40 may be either a native app or a web app.

[0021] (Regarding the forces acting on the buoy, etc.) Figure 2 illustrates the forces acting on the buoy. The forces acting on buoy 21 will be explained with reference to Figure 2.

[0022] First, let's explain the forces acting on buoy 21. Since buoy 21 has a known mass, we can consider that a downward gravitational force G acts on its center of gravity (the hatched "x" mark in Figure 2). As mentioned above, since the mass of buoy 21 is known, the value of the gravitational force G is also a known constant. The reason why the center of gravity of buoy 21 and the center (the filled "x" mark in Figure 2) are offset is that a weight 21b is built into the fulcrum 21c (connection point) where buoy 21 and wire 23 are connected, in order to suppress the swaying of buoy 21.

[0023] Furthermore, since buoy 21 is a floating buoy on the water surface, there is a portion of its volume that is submerged below the water surface (submerged volume), and a vertically upward buoyant force U acts on this submerged portion due to the water pressure difference. Specifically, the buoyant force U is calculated as the product of the submerged volume, the density of water, and the acceleration due to gravity. In Figure 1, this buoyant force U is illustrated as a force acting on the center of buoy 21. Here, the height from the water surface of the portion of buoy 21 that is above the water surface is defined as the apex height Δh.

[0024] Furthermore, since buoy 21 is a floating buoy in the sea, it can be assumed that there is approximately no horizontal water flow, and the force due to such water flow can be ignored. Therefore, the horizontal force acting on buoy 21 can be ignored, and it can be assumed that buoy 21 has no horizontal displacement at sea level.

[0025] Furthermore, as described above, since the buoy 21 is connected to the wire feeding mechanism 22 by the wire 23, it receives a tension T in the direction of the wire 23 at the fulcrum 21c, corresponding to the wire length L.

[0026] The following explains the relationships between the variables and constants mentioned above. Here, the depth of the sea that the prediction management server 10 calculates is denoted as water depth d, and the speed at which the tsunami propagates is denoted as tsunami velocity V.

[0027] The vertex height Δh can be derived from the image captured by the surveillance camera 30. Alternatively, the position of the mark 21a on the surface of the buoy 21 may be used to derive the vertex height Δh from the image. For example, if the buoy 21 is spherical and its volume is known, the submerged volume of the buoy 21 can be calculated by deriving the vertex height Δh. Then, as described above, the buoyancy U can be calculated by the product of the submerged volume, the density of water, and the acceleration due to gravity. That is, since the buoyancy U is a function of the vertex height Δh, it shall be denoted as U(Δh) when specifically indicated.

[0028] Furthermore, as described above, the wire length L of the wire 23 and the tension generated in the wire 23 are related by a predetermined relational equation, and if one is determined, the other can be derived. Therefore, the tension T is a function of the wire length L, and when this is specifically indicated, it shall be written as T(L).

[0029] Furthermore, the vertical forces acting on buoy 21 are related by the equilibrium equation shown in equation (1) below.

[0030] U(Δh)=G+T(L) ···(1)

[0031] In other words, the buoyancy U is equal to the resultant force of gravity G and tension T. Also, as mentioned above, since there is no displacement of the buoy 21 in the horizontal plane, the direction of the wire 23 coincides with the vertical direction. Therefore, if the size of the buoy 21 is sufficiently small compared to the water depth d and can be ignored, the wire length L coincides with the water depth d, i.e., L=d. Thus, in equation (1) above, if the buoyancy U is calculated, T(L) can be calculated, and its inverse function, the wire length L, i.e., the water depth d, can be calculated.

[0032] (Regarding the frequency, wavelength, and speed of tsunamis) Figure 3 illustrates the frequency, wavelength, and velocity of a tsunami. Referring to Figure 3, the method for calculating the frequency, wavelength, and velocity of a tsunami based on the behavior of buoy 21 will be explained.

[0033] As described above, the prediction management server 10 can calculate the water depth d at the location where buoy 21 is floating by deriving the vertex height Δh of buoy 21 from the captured image. Furthermore, for buoy 21 that moves up and down (oscillates vertically) during a tsunami, etc., the prediction management server 10 can obtain a time-series value of the water depth d by deriving the vertex height Δh from the captured image. From this change in water depth d, the prediction management server 10 can calculate the oscillation frequency f of the vertical oscillation of buoy 21.

[0034] Furthermore, the prediction management server 10 derives the wavelength λ of the tsunami from the vertical oscillation of multiple buoys 21 derived from the captured images. For example, the prediction management server 10 can identify two buoys 21 whose vertical oscillations are synchronized, as determined from the change in water depth d in the captured images, and derive the wavelength λ of the tsunami by deriving the distance between these two buoys 21.

[0035] The prediction management server 10 then calculates the tsunami velocity V by multiplying the calculated frequency f by the wavelength λ of the tsunami.

[0036] Furthermore, the prediction management server 10 can calculate the tsunami wave height H from the difference between the highest value (the crest of the tsunami) and the lowest value (the trough of the tsunami) for the water depth d calculated for a specific buoy 21, and can calculate the wave volume based on this wave height H. Based on the tsunami velocity V and the wave volume, the prediction management server 10 can then predict the inundation area caused by the tsunami spreading from the shoreline.

[0037] (Hardware configuration of the predictive management server) Figure 4 shows an example of the hardware configuration of the predictive management server according to this embodiment. The hardware configuration of the predictive management server 10 according to this embodiment will be described with reference to Figure 4.

[0038] As shown in Figure 4, the predictive management server 10 includes a CPU (Central Processing Unit) 501, a ROM (Read Only Memory) 502, a RAM (Random Access Memory) 503, an auxiliary storage device 505, a network interface 508, a display 509, a keyboard 511, and a mouse 512.

[0039] The CPU 501 is a processing unit that controls the overall operation of the predictive management server 10. The ROM 502 is a non-volatile memory device that stores programs for the predictive management server 10. The RAM 503 is a volatile memory device used as the work area for the CPU 501.

[0040] The auxiliary storage device 505 is a storage device such as an HDD (Hard Disk Drive) or SSD (Solid State Drive) that stores various data and programs.

[0041] Network I / F 508 is an interface for wirelessly transmitting data between the surveillance camera 30 and the information terminal 40. Standards for wireless communication include 3G, LTE, 4G, 5G, or Wi-Fi (registered trademark).

[0042] The display 509 is a display device composed of liquid crystal or organic EL, etc., which displays various information such as cursors, menus, windows, characters, or images.

[0043] The keyboard 511 is an input device for selecting characters, numbers, various instructions, and moving the cursor. The mouse 512 is an input device for selecting and executing various instructions, selecting the object to be processed, and moving the cursor.

[0044] The CPU 501, ROM 502, RAM 503, auxiliary storage device 505, network interface 508, display 509, keyboard 511, and mouse 512 described above are connected to each other via bus lines 510, such as an address bus and a data bus, enabling communication between them.

[0045] Note that the hardware configuration of the predictive management server 10 shown in Figure 4 is just one example, and it is not necessary to include all of the components shown in Figure 4, or other components may be included.

[0046] (Hardware configuration of information terminals) Figure 5 shows an example of the hardware configuration of an information terminal according to this embodiment. The hardware configuration of the information terminal 40 according to this embodiment will be described with reference to Figure 5.

[0047] As shown in Figure 5, the information terminal 40 includes a CPU 401, a ROM 402, a RAM 403, an EEPROM (Electrically Erasable Programmable Read Only Memory) 404, an imaging unit 405, an imaging interface 406, an acceleration / direction sensor 407, and a GPS (Global Positioning System) receiver 408.

[0048] The CPU 401 is a processing unit that controls the operation of the entire information terminal 40. The ROM 402 is a non-volatile memory device that stores programs used to drive the CPU 401, such as the IPL (Initial Program Loader). The RAM 403 is a volatile memory device used as the work area of ​​the CPU 401. The EEPROM 404 is a non-volatile memory device that stores programs and various other data.

[0049] The imaging unit 405 is a built-in imaging device that, under the control of the CPU 401, captures images of a subject using an image sensor such as a CCD (Charge-Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor) to obtain image data. The imaging I / F 406 is an interface for controlling the operation of the imaging unit 405.

[0050] The accelerometer / directional sensor 407 is a combination of various sensors, including an electronic magnetic compass for detecting the Earth's magnetic field, a gyrocompass, and an accelerometer.

[0051] The GPS receiver 408 is a receiving device that receives GPS signals from GPS satellites. It is not limited to GPS; other GNSS (Global Navigation Satellite System) systems may also be used.

[0052] Furthermore, as shown in Figure 5, the information terminal 40 also includes a long-range communication circuit 410, an antenna 410a, a short-range communication circuit 411, an antenna 411a, a microphone 412, a speaker 413, an audio input / output interface 414, a display 415, an external device connection interface 416, a vibrator 417, and a touch panel 418.

[0053] The long-distance communication circuit 410 is a communication circuit that wirelessly communicates with other devices via antenna 410a using standards such as Wi-Fi (registered trademark).

[0054] The short-range communication circuit 411 is a communication circuit that performs short-range wireless communication with other devices via antenna 411a using standards such as NFC (Near Field Communication) or Bluetooth (registered trademark).

[0055] Microphone 412 is a built-in sound collection device that converts sound into electrical signals. Speaker 413 is a built-in acoustic device that converts electrical signals into physical vibrations to output sound such as music or speech. Sound input / output interface 414 is an interface that processes the input and output of sound signals between microphone 412 and speaker 413 according to the control of CPU 401.

[0056] Display 415 is a display device such as a liquid crystal display or an organic EL (Electro-Luminescence) display that displays images of the subject, various icons, etc. External device connection I / F 416 is an interface conforming to standards such as USB (Universal Serial Bus) for connecting various external devices.

[0057] The vibrator 417 is a device that generates physical vibrations according to the control of the CPU 401.

[0058] The touch panel 418 is an input device that allows users to activate various functions of the information terminal 40 by touching the display 415.

[0059] The CPU 401, ROM 402, RAM 403, EEPROM 404, imaging interface 406, acceleration / direction sensor 407, GPS receiver 408, long-range communication circuit 410, short-range communication circuit 411, sound input / output interface 414, display 415, external device connection interface 416, vibrator 417, and touch panel 418 are all connected to each other via bus lines 409, such as an address bus and a data bus, enabling communication between them.

[0060] Note that the hardware configuration of the information terminal 40 shown in Figure 5 is just one example, and it is not necessary to have all of the components, nor is it necessary to have other components.

[0061] (Configuration and operation of the functional blocks of the predictive management server) Figure 6 shows an example of the configuration of the functional blocks of the predictive management server according to this embodiment. The configuration and operation of the functional blocks of the predictive management server 10 according to this embodiment will be described with reference to Figure 6.

[0062] As shown in Figure 6, the prediction management server 10 includes an acquisition unit 101, a first calculation unit 102, a prediction unit 103, a second calculation unit 104, and a display control unit 105.

[0063] The acquisition unit 101 is a functional unit that acquires images of the buoy 21 captured by multiple buoy-type sensors 20 via the network I / F 508.

[0064] The first calculation unit 102 is a functional unit that calculates the ocean depth d, tsunami velocity V, wave height H, and wave volume based on the image captured by the acquisition unit 101. Details of these calculation methods will be described later in Figure 7.

[0065] The prediction unit 103 is a functional unit that predicts, in the event of a flood caused by a tsunami, the inundation area spreading from the shoreline, based on pre-prepared map information, the tsunami velocity V calculated by the first calculation unit 102, and the wave volume, in a time series. In this case, the map information includes, for example, topographic information such as land elevation, road information, and information on the size and location of buildings.

[0066] The second calculation unit 104 is a functional unit that calculates an evacuation route that bypasses the flooded area (predicted flooded area) predicted by the prediction unit 103, and the evacuation time when using that evacuation route. For example, the second calculation unit 104 calculates the shortest route that bypasses the predicted flooded area as an evacuation route from the user's home to a designated evacuation shelter on the information terminal 40.

[0067] The display control unit 105 is a functional unit that controls the display operation of the information terminal 40, for example, on which a web application is running, via the network interface 508. The display control unit 105, for example, overlays the predicted flood area predicted by the prediction unit 103 onto the map information displayed on the display 415 of the information terminal 40, and also overlays the evacuation route and evacuation time calculated by the second calculation unit 104 onto the map information.

[0068] The acquisition unit 101, the first calculation unit 102, the prediction unit 103, the second calculation unit 104, and the display control unit 105 described above are implemented by the execution of a program by the CPU 501 shown in Figure 4. At least a portion of these functional units may be implemented by hardware circuits such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application Specific Integrated Circuits).

[0069] It should be noted that the functional units of the predictive management server 10 shown in Figure 6 are conceptual representations of their functions and are not limited to this configuration. For example, multiple functional units shown as independent functional units in the predictive management server 10 in Figure 6 may be configured as a single functional unit. Alternatively, the functions of a single functional unit in the predictive management server 10 shown in Figure 6 may be divided into multiple functions and configured as multiple functional units.

[0070] (Flowchart of the water depth calculation process on the prediction management server) Figure 7 is a flowchart showing an example of the water depth calculation process of the predictive management server according to this embodiment. The water depth calculation process by the predictive management server 10 according to this embodiment will be explained with reference to Figure 7.

[0071] <Step S11> The acquisition unit 101 of the predictive management server 10 acquires images of the buoy 21 from multiple buoy-type sensors 20 captured by the surveillance camera 30 via the network interface 508. The first calculation unit 102 of the predictive management server 10 derives the vertex height Δh of the buoy 21 of the buoy-type sensor 20 from the images acquired by the acquisition unit 101. The first calculation unit 102 may use the position of the mark 21a on the surface of the buoy 21 to derive the vertex height Δh from the images. Then, the process proceeds to step S12.

[0072] <Step S12> The first calculation unit 102 then calculates the submerged volume of the buoy 21 from the apex height Δh, and calculates the buoyancy U by product of the submerged volume, the density of water, and the acceleration due to gravity. Then, it proceeds to step S13.

[0073] <Step S13> The first calculation unit 102 then calculates the buoyancy U determined from gravity G and the apex height Δh, as well as the tension T that the buoy 21 receives from the wire 23 at the support point 21c, based on equation (1) described above. Then, the process proceeds to step S14.

[0074] <Step S14> The first calculation unit 102 then calculates the wire length L, which is the inverse function of the tension T, as the water depth d.

[0075] Following the steps S11 to S14 described above, the water depth calculation process is performed by the prediction management server 10.

[0076] Furthermore, the prediction management server 10 calculates the tsunami velocity V, wave height H, and wave volume as follows:

[0077] The first calculation unit 102 calculates the frequency f of the vertical oscillation of the buoy 21 based on the time-series value of the calculated water depth d. The first calculation unit 102 also derives the wavelength λ of the tsunami from the vertical oscillation movements of multiple buoys 21 derived from the captured images. For example, the prediction management server 10 can identify two buoys 21 whose vertical oscillations are synchronized, as determined from the change in water depth d in the captured images, and derive the wavelength λ of the tsunami by deriving the distance between these two buoys 21.

[0078] The first calculation unit 102 then calculates the tsunami velocity V by multiplying the calculated frequency f by the wavelength λ of the tsunami.

[0079] Furthermore, the first calculation unit 102 can calculate the tsunami wave height H based on the difference between the highest value (tsunami crest) and the lowest value (tsunami trough) for the water depth d calculated for a specific buoy 21, and calculate the wave volume based on this wave height H.

[0080] (Display operation of predicted flood area, evacuation routes, and evacuation times on information terminals) Figure 8 shows an example of a state in which evacuation routes are displayed on the map information in an information terminal according to the embodiment. Figure 9 shows an example of a state in which the predicted flood area and detour routes for evacuation are displayed on the map information in an information terminal according to the embodiment. Referring to Figures 8 and 9, the display operation of the predicted flood area, evacuation routes, and evacuation time on the map information of the information terminal 40 will be explained.

[0081] In the example shown in Figure 8, when no tsunami has occurred, the display control unit 105 displays the evacuation route and evacuation time calculated by the second calculation unit 104 superimposed on the map information on the display 415 of the information terminal 40. Specifically, in Figure 8, the evacuation route LT1 from the user's home to the evacuation shelter and the evacuation time are displayed superimposed on the map information on the display 415 of the information terminal 40.

[0082] Next, in the example shown in Figure 9, when a tsunami occurs, the display control unit 105 overlays the predicted flooded area FA at a specific time, predicted by the prediction unit 103, and the evacuation route LT2 and evacuation time that bypass the predicted flooded area FA, calculated by the second calculation unit 104, onto the map information on the display 415 of the information terminal 40.

[0083] Furthermore, the information terminal 40 may allow the user to select how many minutes from the current time the predicted flooded area FA is. In this case, the predicted flooded area after the selected time has elapsed is predicted again by the prediction unit 103, and the second calculation unit 104 calculates an evacuation route and evacuation time that bypasses the predicted flooded area.

[0084] As described above, in the prediction management server 10 according to this embodiment, the acquisition unit 101 acquires images captured by a surveillance camera 30 that images the buoy 21 on the sea surface in the event of a tsunami, which is a buoy-type sensor 20 having a buoy 21 floating on the sea surface and a wire feed mechanism 22 fixed to or near the sea surface that is connected to the buoy 21 by a wire 23 and allows the wire 23 to be fed out and retracted, and the first calculation unit 102 calculates from the captured images the buoy 2 The method involves deriving the apex height Δh, which is the height from the water surface of the portion of buoy 21 that is visible above the water surface, calculating the buoyancy U acting on buoy 21 based on the apex height Δh, calculating the tension T based on equation (1) of the balance between gravity G acting on buoy 21, buoyancy U, and tension T at the fulcrum 21c between buoy 21 and wire 23, calculating the wire length L from the tension T as the water depth d from the position where buoy 21 is floating, and calculating the tsunami velocity V from the water depth d in the time series. As a result, since no power is required to send or receive any signals or information for buoy 21, the tsunami velocity V can be calculated accurately without using expensive sensors.

[0085] Furthermore, in the prediction management server 10 according to this embodiment, the first calculation unit 102 calculates the wave height H of the tsunami from the time-series water depth d, and calculates the wave volume from the wave height H. The prediction unit 103 predicts the inundation area caused by the tsunami in a time series based on predetermined map information and the tsunami velocity V and wave volume calculated by the first calculation unit 102. The second calculation unit 104 calculates evacuation routes and evacuation times that bypass the inundation area predicted by the prediction unit 103. The display control unit 105 overlays the inundation area predicted by the prediction unit 103, as well as the evacuation routes and evacuation times calculated by the second calculation unit 104, onto the map information and displays them on the information terminal 40. As a result, the user of the information terminal 40 can confirm the inundation area with high prediction accuracy, and can also confirm evacuation routes and evacuation times that bypass the inundation area, making it possible to safely evacuate to a shelter even if flooding occurs.

[0086] Furthermore, each function of the embodiment described above can be realized by one or more processing circuits. Here, "processing circuit" includes processors programmed to execute each function by software, such as processors implemented by electronic circuits, as well as devices such as ASICs (Application Specific Integrated Circuits), DSPs (Digital Signal Processors), FPGAs (Field Programmable Gate Arrays), and conventional circuit modules designed to execute each of the functions described above.

[0087] Furthermore, the program executed by the predictive management server 10 in the above-described embodiment may be configured to be pre-installed and provided in ROM or the like.

[0088] Furthermore, the program executed by the predictive management server 10 in the above-described embodiment may be configured to be provided as a computer program product by recording it in an installable or executable file format onto a computer-readable recording medium such as a CD-ROM (Compact Disc Read Only Memory), a flexible disk (FD), a CD-R (Compact Disc-Recordable), or a DVD (Digital Versatile Disc).

[0089] Furthermore, the program executed by the predictive management server 10 of the above-described embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Alternatively, the program executed by the predictive management server 10 of the above-described embodiment may be provided or distributed via a network such as the Internet.

[0090] Furthermore, the program executed by the predictive management server 10 in the above-described embodiment has a modular configuration that includes each of the functional units described above. In actual hardware, the CPU 501 (processor) reads the program from the ROM 502 or auxiliary storage device 505 and executes it, thereby loading each of the functional units onto the RAM 503 (main memory), and creating each functional unit on the RAM 503. [Explanation of Symbols]

[0091] 1. Flood monitoring system 10 Predictive Management Server 20 Buoy-type sensors 21 V 21a Mark 21b Weight 21c fulcrum 22 Wire feeding mechanism 23 wires 30 surveillance cameras 40 Information terminals 101 Acquisition Department 102 First Calculation Unit 103 Prediction Section 104 Second Calculation Unit 105 Display Control Unit 401 CPU 402 ROM 403 RAM 404 EEPROM 405 Imaging Unit 406 IMAGING I / F 407 Acceleration and compass sensor 408 GPS receiver 409 Bus Line 410 Telecommunications circuit 410a antenna 411 Near field communication circuit 411a antenna 412 Mike 413 Speakers 414 Audio Input / Output Interface 415 displays 416 External device connection interface 417 Vibrator 418 Touch Panel 501 CPU 502 ROM 503 RAM 505 Auxiliary storage 508 Network Interface 509 Display 510 Bus Line 511 keyboard 512 mice d water depth f frequency FA predicted flood area G gravity H wave height L Wire Length LT1, LT2 Evacuation Routes T tension U buoyancy V Tsunami speed λ wavelength Δh vertex height

Claims

1. A buoy-type sensor having a buoy floating on the sea surface and an extension mechanism fixed to or near the sea surface, connected to the buoy by a connecting wire and capable of extending and retracting the connecting wire, wherein the sensor includes an acquisition unit that acquires an image captured by an imaging device that images the buoy on the sea surface in the event of a tsunami, A first calculation unit that, from the captured image, derives the apex height, which is the height from the water surface of the portion of the buoy that is visible above the water surface, calculates the buoyancy acting on the buoy based on the apex height, calculates the tension based on the relationship between gravity acting on the buoy, the buoyancy, and the tension at the connection point between the buoy and the connecting line, calculates the length of the connecting line from the tension as the water depth from the position where the buoy is floating in a time series, and calculates the tsunami velocity from the water depth in the time series, A flood monitoring device equipped with a flood monitoring system.

2. The first calculation unit is, The frequency of the vertical oscillation of the buoy is calculated from the changes in the water depth. Based on the vertical oscillation motion of the multiple buoys derived from the aforementioned captured images, the wavelength of the tsunami is derived. The flood monitoring device according to claim 1, which calculates the velocity of a tsunami by the product of the frequency and the wavelength of the tsunami.

3. The first calculation unit is, The submerged volume of the buoy is calculated from the aforementioned peak height, The flood monitoring device according to claim 1, which calculates the buoyancy acting on the buoy based on the submerged volume.

4. The buoy has a mark on its surface, The flood monitoring device according to claim 1, wherein the first calculation unit derives the peak height from the captured image based on the position of the mark on the buoy.

5. The first calculation unit is, From the aforementioned time-series water depth values, the wave height of the tsunami is calculated. A flood monitoring device according to any one of claims 1 to 4, which calculates the volume of water from the wave height.

6. The flood monitoring device according to claim 5, further comprising a prediction unit that predicts the area of ​​inundation caused by the tsunami based on predetermined map information and the tsunami velocity and wave volume calculated by the first calculation unit.

7. The flood monitoring device according to claim 6, further comprising a second calculation unit for calculating an evacuation route and evacuation time that bypasses the flooded area predicted by the prediction unit.

8. The flood monitoring device according to claim 7, further comprising a display control unit that superimposes the flooded area predicted by the prediction unit, and the evacuation route and evacuation time calculated by the second calculation unit onto the map information and displays them on an information terminal.

9. A buoy-type sensor having a buoy floating on the surface of the sea, and a deployment mechanism fixed to the seabed or near the seabed, which is connected to the buoy by a connecting wire and is capable of extending and retracting the connecting wire, An imaging device for imaging the buoy on the sea surface in the event of a tsunami, A flood monitoring device that calculates the speed of the tsunami based on the captured image captured by the aforementioned imaging device, Includes, The aforementioned flood monitoring device, An acquisition unit that acquires the captured image from the aforementioned imaging device, A first calculation unit that, from the captured image, derives the apex height, which is the height from the water surface of the portion of the buoy that is visible above the water surface, calculates the buoyancy acting on the buoy based on the apex height, calculates the tension based on the relationship between gravity acting on the buoy, the buoyancy, and the tension at the connection point between the buoy and the connecting line, calculates the length of the connecting line from the tension as the water depth from the position where the buoy is floating in a time series, and calculates the tsunami velocity from the water depth in the time series, A flood monitoring system equipped with a flood monitoring system.

10. A flood monitoring method performed by a flood monitoring device, A buoy-type sensor having a buoy floating on the sea surface and an extension mechanism fixed to or near the sea surface, connected to the buoy by a connecting wire and capable of extending and retracting the connecting wire, the process of acquiring an image captured by an imaging device that images the buoy on the sea surface in the event of a tsunami, The process involves deriving the apex height, which is the height from the water surface of the portion of the buoy that is visible above the water surface, from the captured image, calculating the buoyancy acting on the buoy based on the apex height, calculating the tension based on the relationship between gravity acting on the buoy, the buoyancy, and the tension at the connection point between the buoy and the connecting line, calculating the length of the connecting line from the tension as the water depth from the position where the buoy is floating in a time series, and calculating the tsunami velocity from the water depth in the time series, A flood monitoring method characterized by including the following:

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