Information processing device, program and information processing method

Abstract

To improve the efficiency of processing related to an insurance claim.SOLUTION: An information processing device 1 according to an embodiment of the present disclosure, includes: a generation unit 102 for generating flood damage information 140 on a situation of flood damage in a prescribed region 7 on the basis of first image information generated by an imaging device 2 for photographing the region 7 from the sky; a position information acquisition unit 100b for acquiring position information 141 on a position of a feature 3 of the region 7; an estimation unit 106 for estimating damage having been caused in the feature 3 by the flood damage on the basis of the flood damage information 140 and the position information 141; a declaration information acquisition unit 100f for acquiring declaration information 136 on a declaration of the damage having been caused in the feature 3 by the flood damage; and a determination unit 107 for determining consistency between an estimation result by the estimation unit 106 and the declaration information 136.SELECTED DRAWING: Figure 2

Description

[Technical field]

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

[0002] Patent document 1 describes a technology that determines whether a photograph submitted for application is an image corresponding to a disaster based on information (e.g., the date and time of shooting, the location of shooting) added to the photograph regarding an area affected by the disaster. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 7123285 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technique described in Patent Document 1 does not sufficiently improve the efficiency of processing related to insurance claims.

[0005] In view of the above problems, an object of the present invention is to improve the efficiency of insurance claim processing. [Means for solving the problem]

[0006] An information processing device according to one embodiment of the present disclosure includes a generation unit that generates flood information regarding the flood situation in a region based on first image information generated by an imaging device that photographs a specified region from the sky, a location information acquisition unit that acquires location information regarding the locations of features in the region, an estimation unit that estimates damage caused to the features due to flood based on the flood information and the location information, a declaration information acquisition unit that acquires declaration information regarding declarations of damage actually caused to the features due to flood, and a determination unit that determines the consistency between the estimation result by the estimation unit and the declaration information.

[0007] A program according to another aspect of the present disclosure causes a computer to function as a generation means for generating flood information regarding the flood situation in a region based on first image information generated by an imaging device that photographs a specified region from the air, a location information acquisition means for acquiring location information regarding the locations of features in the region, an estimation means for estimating damage caused to features by flood based on the flood information and the location information, a declaration information acquisition means for acquiring declaration information regarding declarations of damage actually caused to features by flood, and a determination means for determining the consistency between the estimation result by the estimation means and the declaration information.

[0008] An information processing device according to another aspect of the present disclosure causes a computer to execute the following steps: a generation step of generating flood information regarding the flood situation in a region based on first image information generated by an imaging device that photographs a specified region from the air; a location information acquisition step of acquiring location information regarding the positions of features in the region; an estimation step of estimating damage caused to features due to flood based on the flood information and the location information; a declaration information acquisition step of acquiring declaration information regarding declarations of damage actually caused to features due to flood; and a determination step of determining the consistency between the estimation result by the estimation step and the declaration information. Effect of the Invention

[0009] The present invention can streamline the processing of insurance claims. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram showing an overview of a system according to an embodiment of the present invention; [Diagram 2] 1 is a diagram showing an overview of a system according to an embodiment of the present invention; [Diagram 3] 1 is a functional block diagram of an information processing device according to an embodiment of the present invention. [Figure 4] FIG. 2 is a hardware configuration diagram of the information processing device according to the embodiment. [Diagram 5] 10 is a flowchart illustrating an example of an operation of the information processing device according to the present embodiment. [Figure 6] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 7] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 8] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 9] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 10] 10 is a flowchart illustrating an example of an operation of the information processing device according to the present embodiment. [Figure 11] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 12] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 13] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 14] FIG. 2 is a diagram for explaining an example of an operation of the information processing device according to the embodiment. [Figure 15] FIG. 2 is a diagram for explaining an example of a display screen of the information processing device according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] A preferred embodiment of the present invention (hereinafter, referred to as the present embodiment) will be described with reference to the accompanying drawings. In each drawing, the same reference numerals denote the same or similar configurations.

[0012] In the present invention, "part," "means," "apparatus," and "system" do not simply mean physical means, but also include cases where the functions of the "part," "means," "apparatus," and "system" are realized by software. Also, the functions of one "part," "means," "apparatus," and "system" may be realized by two or more physical means, devices, and software, and the functions of two or more "parts," "means," "apparatus," and "system" may be realized by one physical means, device, and software.

[0013] <1. System Overview> The system according to this embodiment includes an information processing device 1 that estimates flood damage to a feature 3 based on flood information 140 indicating the flood situation and location information 141 of the feature 3. The information processing device 1 acquires report information 136 regarding a report of damage caused to the feature 3 by flood from a user who has made an insurance contract (hereinafter referred to as the "insured person"). Then, the information processing device 1 determines the consistency between the damage estimated for the feature 3 and the damage reported in the report information 136. The feature 3 is, for example, a building such as a house or a commercial facility.

[0014] An overview of the operation of the system according to this embodiment will be described with reference to FIGS.

[0015] Fig. 1 is a diagram showing an outline of the operation of an information processing device 1 when estimating damage caused to a feature 3. The system in Fig. 1 includes the information processing device 1 and an imaging device 2. In this example, the imaging device 2 is an artificial satellite.

[0016] First, the imaging device 2, which is an artificial satellite, captures an image of a specific area 7 from above, thereby generating first image information 138, which is a satellite image of the area 7 (S1). In the area 7, there are features 3 (e.g., forests, rivers, seas, buildings, etc.) and vehicles, etc. Furthermore, flood damage (e.g., inundation, flooding, high tides, heavy rains, inundation, submergence, tsunami, etc.) has occurred.

[0017] Next, the information processing device 1 receives the first image information 138 from the imaging device 2 (S2).

[0018] Next, the information processing device 1 generates flood information 140 based on the first image information 138 (S3). The flood information 140 is information indicating the status of a flood (typically, when, where, and to what extent a flood has occurred).

[0019] Next, the information processing device 1 acquires the location information 141 indicating the coordinates of the feature 3 (S4). Note that the information processing device 1 may acquire the location information 141 from, for example, a database in which the address of the insured person is recorded.

[0020] Next, the information processing device 1 estimates damage caused to the feature 3 based on the flood information 140 and the position information 141 (S5). The information processing device 1 typically estimates damage caused to the feature 3 by comparing the coordinates of the feature 3 at a certain point in time with the flood depth at that point in time and at those coordinates. For example, according to the position information 141, the coordinates of the feature 3 are [X, Y]. According to the flood information 140, the flood depth at the coordinates [X, Y] is approximately 55 cm based on the ground level. Furthermore, the feature 3 is a building, and the floor height based on the ground level is 45 cm. In this case, the information processing device 1 estimates that flooding above the floor level of approximately 10 cm has occurred in the feature 3.

[0021] 2 is a diagram showing an outline of the operation of the information processing device 1 when determining whether there is a consistency between the estimation result by S1-S5 and the reported information 136. The information processing device 1 receives the reported information 136 from the terminal device 5 of the insured person (S6). The reported information 136 includes, for example, information related to an insurance claim made by the insured person to an insurance company.

[0022] Next, the information processing device 1 determines the consistency between the estimation result and the declared information 136 (S7). Typically, the information processing device 1 determines that there is consistency when the difference between the estimation result and the declared information 136 is small, and determines that there is no consistency when the difference between the estimation result and the declared information 136 is large.

[0023] The information processing device 1 can determine with high accuracy the validity of insurance claims for features 3 over a wide area. This is because the flood information 140 for estimating damage caused to the features 3 is generated based on image information generated by an imaging device that captures images of the area 7 from the sky. As a result, the processing related to insurance claims at insurance companies becomes more efficient.

[0024] In the following, the flood depth included in the flood information 140 will be referred to as the "estimated flood depth," the actual flood depth in area 7 as the "measured flood depth," and the flood depth included in the reporting information 136 as the "reported flood depth." Note that the estimated flood depth and the measured flood depth are typically based on the ground level. In contrast, the reported flood depth may be based on the ground level or the floor level, depending on the input method used by the insured person.

[0025] <2. System Functional Configuration> An example of the functional configuration of the system according to this embodiment will be described with reference to FIG.

[0026] The system according to this embodiment includes an information processing device 1, an imaging device 2, a terminal device 5, an external storage device 4, and a communication network 6. The devices are capable of communicating with each other via the communication network 6. Note that the system may include at least some of the imaging device 2, the terminal device 5, and the external storage device 4 in multiple units.

[0027] [Information processing device 1] The information processing device 1 includes a control unit 10, a storage unit 14, and a network interface unit 18. The control unit 10, the storage unit 14, and the network interface unit 18 are electrically connected via a bus 16.

[0028] [Control unit 10] The control unit 10 executes various programs stored in the memory unit 14 to function as an acquisition unit 100, a generation unit 102, an extraction unit 104, an estimation unit 106, a judgment unit 107, a decision unit 108, a display unit 110, and a notification unit 112.

[0029] [Acquisition part 100] -Image information acquisition unit 100a- The acquisition unit 100 acquires various pieces of information from the imaging device 2 and the external storage device 4. In this embodiment, acquiring information includes making the information processable by the control unit 10. Acquiring information includes, for example, receiving the information from another device and reading the information from the storage unit 14.

[0030] The acquiring unit 100 acquires the first image information 138 generated by the imaging device 2. The acquiring unit 100 may acquire the first image information 138 from the imaging device 2, or may acquire the first image information 138 stored by the imaging device 2 in the external storage device 4. The acquiring unit 100 may also be referred to as an image information acquiring unit 100a. As described later, the imaging device 2 is, for example, an artificial satellite, an airplane, a drone (also called an unmanned aerial vehicle), or a camera mounted on a vehicle.

[0031] The first image information 138 acquired by the acquisition unit 100 is stored in the storage unit 14. The first image information 138 is information related to an image. The first image information 138 is typically information that can be read by the computer 30 described later to display an image related to the first image information 138 on the display device 310. The first image information 138 may be stored in a file format such as JPEG, PNG, GIF, BMP, and TIFF in the storage unit 14. The first image information 138 may be information related to a satellite image, an aerial image, and an image generated by a drive recorder of the feature 3. The first image information 138 is not limited to a still image, and may be information related to a video.

[0032] The first image information 138 may include metadata about the image (e.g., the time and place when the image was taken, etc.). The first image information 138 may also be information (e.g., features) generated by appropriately processing other first image information 138.

[0033] The first image information 138 may include aerial image information generated by photographing the area 7 from the sky, and vehicle image information generated by a vehicle photographing the area 7. The aerial image information is generated by, for example, an artificial satellite, an airplane, a drone, or the like. The range of the area 7 may be set arbitrarily, for example, a place where flood damage is occurring, a place where heavy rain or a typhoon is occurring, or any city, ward, town, or village.

[0034] -Location information acquisition unit 100b- The acquiring unit 100 also acquires location information 141 related to the coordinates of the feature 3. The acquiring unit 100 may acquire the location information 141 from a database in which the address of the insured who is the owner of the feature 3 is recorded, may acquire the location information 141 from an IoT device or the like equipped in the feature 3, or may acquire the location information 141 of the feature 3 from a terminal (e.g., a smartphone or the like) held by the insured who is the owner of the feature 3. The acquiring unit 100 may also be referred to as a location information acquiring unit 100b.

[0035] - Feature information acquisition section 100c - The acquiring unit 100 also acquires feature information 142 relating to the flood conditions of other features 3 for which the flood conditions are already known. The acquiring unit 100 may acquire the feature information 142 from a terminal (e.g., a flood detection device and a surveillance camera) attached to the other feature 3, may acquire the feature information 142 from an external storage device 4 (e.g., a server device that records flood reports of buildings), or may acquire the feature information 142 from a terminal of the owner of the other feature 3. The acquiring unit 100 can also be referred to as a feature information acquiring unit 100c.

[0036] The feature information 142 acquired by the acquisition unit 100 is stored in the memory unit 14. The feature information 142 may include the coordinates of other features 3, the measured flood depth at those coordinates, and images and videos of the surroundings of the other features 3.

[0037] -SNS information acquisition department 100d- The acquisition unit 100 also acquires SNS information 143 related to multiple posts on a social network service (hereinafter referred to as "SNS"). The acquisition unit 100 may acquire the SNS information 143 from a terminal of a user who posted on the SNS, or may acquire the SNS information 143 from the external storage device 4. The acquisition unit 100 may also be referred to as an SNS information acquisition unit 100d.

[0038] The SNS information 143 acquired by the acquisition unit 100 is stored in the storage unit 14. The SNS information 143 may include the posting date and time of the post, the coordinates at which the post was made, media information included in the post (e.g., text information, audio information, image information, video information, etc.), and user registration information of the SNS.

[0039] -Map information acquisition unit 100e- The acquiring unit 100 also acquires map information 144 related to a map of the area 7. The acquiring unit 100 may acquire the map information 144 from, for example, a server device owned by the Geospatial Information Authority of Japan. The acquiring unit 100 may also be referred to as a map information acquiring unit 100e.

[0040] The map information 144 acquired by the acquisition unit 100 is stored in the storage unit 14. The map information 144 is typically information in which one or more coordinates are associated with features of the features at the coordinates. That is, the map information 144 is information indicating where and what exists. Features of features include, for example, the name, shape, color, and height of the feature. The map information 144 may relate to a map of any format. The map format may be, for example, a general map, a land use map, a geological map, a weather map, a bird's-eye view map, a relief map, etc.

[0041] --Declaration information acquisition unit 100f-- The acquisition unit 100 also acquires report information 136 related to reports of damage caused to the feature 3 by flooding. The acquisition unit 100 may acquire the report information 136 from the terminal device 5, or may acquire the report information 136 stored by the terminal device 5 in the external storage device 4. As described above, the report information 136 includes, for example, information related to an insurance claim made by the insured to an insurance company. The report information 136 includes, for example, information related to the reported flood depth, the insurance contract number, the time when the flooding occurred, the location and design of the feature 3 (for example, the floor height based on the ground level), the cause of the flooding, the details of the damage caused by the flooding, images of the damaged area, etc. The acquisition unit 100 can also be called a report information acquisition unit 100f.

[0042] The report information 136 may include second image information generated by photographing a reference object indicating the flood situation and the feature 3. The second image information is, for example, information on an image showing both a 2L plastic bottle and a water mark (i.e., a mark indicating the height of the water surface at the time of flooding) on ​​the feature 3. According to such second image information, the height of the water mark can be calculated based on the height of the 2L plastic bottle. Specifically, second image information related to an image showing a water mark at a position twice the height of a 2L plastic bottle (generally about 30 cm high) is a basis for indicating that the feature 3 was flooded to a depth of about 60 cm. Note that the type of the reference object indicating the flood situation can be any object as long as its height is generally known (for example, A4 paper, a milk carton, a soccer ball, Tokyo Skytree, etc.).

[0043] --Calibration information acquisition unit 100g-- The acquisition unit 100 also acquires calibration information 146 obtained by calibrating errors contained in the flood information 140. The acquisition unit 100 can also be called a calibration information acquisition unit 100g.

[0044] The flood information 140 is generated based on first image information generated by an imaging device 2 that captures an image of an area 7 from the sky. At this time, errors may occur in the flood information 140 depending on the imaging environment near the imaging device 2. Furthermore, if topographical data (e.g., elevation data) is referenced when generating the flood information 140, errors in the topographical data also affect the flood information 140.

[0045] Such errors in the flood information 140 due to the shooting environment, topographical data, etc. do not occur randomly at each coordinate in the area 7, but may occur approximately uniformly throughout the area 7. In other words, if it is possible to grasp the actual flood situation at any one coordinate in the area 7, it may be possible to calculate the error contained in the flood information 140 and calibrate the flood information 140 based on the calculated error. For example, according to the flood information 140, the estimated flood depths at the coordinates L1 and L2 are 50 cm and 40 cm, respectively, while the measured flood depth at the coordinate L1 is 45 cm, it can be estimated that the flood information 140 for the coordinate L2 contains an error of "+5 cm" similar to that of the coordinate L1. In other words, according to the calibration information 146 obtained by calibrating the error from the flood information 140, the estimated flood depth at the coordinate L2 is 35 cm.

[0046] - Height information acquisition unit 100h - The acquiring unit 100 also acquires height information 145 related to the height of the floor of the feature 3, which is a building, based on the ground level. The acquiring unit 100 may acquire the height information 145 by, for example, referring to a database of insurance policyholders. The acquiring unit 100 may also acquire the height information 145 based on the declared information 136. The acquiring unit 100 may also be referred to as a height information acquiring unit 100h.

[0047] The height information 145 is important information for estimating damage caused to the feature 3. For example, if the flood information 140 indicates that flooding of 47 cm has occurred relative to the ground level at both coordinates L3 and L4, and the floor height of the feature 3 at coordinate L3 relative to the ground level is 45 cm, and the floor height of the feature 3 at coordinate L4 relative to the ground level is 50 cm, it can be estimated that the feature 3 at coordinate L3 has been flooded above the floor by 2 cm, and the feature 3 at coordinate L4 has not been flooded above the floor.

[0048] [Generation unit 102] The generating unit 102 generates flood information 140 regarding the flood situation in the area 7 based on the first image information 138 generated by the imaging device 2. The generating unit 102 may detect the coordinates where the flood occurs by detecting a difference between image information showing the flood situation in the area 7 at time T1 and image information showing the flood situation in the area 7 at time T2 different from time T1, and generate the flood information 140. The generating unit 102 may also detect the coordinates where the flood occurs by applying image recognition to the first image information 138, and generate the flood information 140.

[0049] The generating unit 102 may generate the flood information 140 based on the feature information 142, the SNS information 143, etc., in addition to the first image information 138. The generating unit 102 may generate the flood information 140 mainly based on the aerial image information included in the first image information 138, and may supplementarily use the vehicle image information, the feature information 142, the SNS information 143, etc. This is because, from the viewpoint of uniformly estimating damage caused to multiple features 3 in the area 7, it may be possible to provide efficient compensation by preferentially using the aerial image information including information over a wide range.

[0050] The flood information 140 generated by the generation unit 102 is stored in the storage unit 14. The flood information 140 is typically information in which one or more coordinates are associated with the flood situation at the coordinates (e.g., estimated flood depth, precipitation amount, water flow speed, etc.). In this embodiment, the flood information 140 is information in which one or more coordinates are associated with the estimated flood depth at the coordinates. In other words, the flood information 140 is information on estimated values ​​of where and to what extent flooded.

[0051] The flood information 140 may include information on the state of flooding at each of one or more points in time. That is, the flood information 140 may include information on changes over time in estimated flood depth at each of one or more coordinates.

[0052] [Extraction part 104] The extraction unit 104 extracts posts related to the flood situation in region 7 from multiple posts on the SNS by pattern recognition. Pattern recognition includes extracting characteristics of predetermined information and classifying the category of the information. Pattern recognition includes, for example, text analysis, image analysis (e.g., character recognition, graphic recognition, object recognition, etc.), voice analysis, speaker recognition, etc. The extraction unit 104 may extract posts related to the flood situation in region 7 from each of the multiple posts by the methods listed below.

[0053] 1) Performing text analysis on the text information associated with a post The extraction unit 104 may extract, from a plurality of posts, posts associated with text information including words related to the flood situation (for example, "flooding," "submersion," and "heavy rain," etc.).

[0054] 2) Perform image analysis on image information associated with posts. The extraction unit 104 may extract, from multiple posts, posts associated with image information regarding images showing flood conditions (e.g., images of submerged features 3, images of flooded buildings, and images of overflowing rivers, etc.).

[0055] 3) Performing voice analysis on any voice information associated with your posts The extraction unit 104 may extract from multiple posts posts those posts associated with audio information regarding audio indicating the flood situation (for example, the audio of a SNS user saying "submerged," the audio of heavy rain hitting the ground, the audio of flowing water, etc.).

[0056] [Estimation section 106] The estimation unit 106 estimates damage caused to the feature 3 based on the flood information 140 and the position information 141. The damage caused to the feature 3 estimated by the estimation unit 106 may be the depth of flooding above the floor of the feature 3. The damage caused to the feature 3 estimated by the estimation unit 106 may be the estimated flood depth at the coordinates of the feature 3. The estimation unit 106 may use the calibration information 146 as the flood information 140.

[0057] Furthermore, the damage caused to the feature 3 estimated by the estimation unit 106 may be a damaged portion of the feature 3 that is further estimated based on the estimated flood depth at the coordinates of the feature 3. For example, when the estimated flood depth at the coordinates where the feature 3 exists is 5 cm according to the flood information 140 and the position information 141, the estimation unit 106 may estimate that no damage has occurred to the feature 3. Alternatively, when the estimated flood depth at the coordinates where the feature 3 exists is 40 cm according to the flood information 140 and the position information 141, the estimation unit 106 may estimate that a certain degree of damage has occurred to the feature 3 (for example, flooding of insulation material arranged under the floor of the feature 3, etc.). Alternatively, when the estimated flood depth at the coordinates where the feature 3 exists is 1 m according to the flood information 140 and the position information 141, the estimation unit 106 may estimate that serious damage has occurred to the feature 3 (for example, failure of electrical equipment or kitchen equipment provided in the feature 3).

[0058] The estimation unit 106 may estimate the damage caused to the feature 3 further based on the height information 145. For example, if the height information 145 indicates that the floor height of the feature 3 based on the ground level is 45 cm, and the flood information 140 and the position information 141 indicate that the estimated flood depth at the coordinates of the feature 3 is 55 cm, it can be estimated that the feature 3 has been flooded 10 cm above the floor.

[0059] Furthermore, if the flood information 140 includes snapshot information on the estimated flood depth at the position of the feature 3 at the first time point, the estimation unit 106 may estimate the damage caused to the feature 3 at the second time point based on the snapshot information and the relationship between the first time point and the second time point. At this time, weather information (e.g., precipitation amount, etc.) on the weather in the area 7 may be referenced. For example, if the estimated flood depth at the position of the feature 3 at the first time point is 20 cm, and very heavy rain of 50 mm / hour falls from the first time point to the second time point one hour later, the estimated flood depth at the position of the feature 3 at the second time point can be estimated to be, for example, about 30 cm. Note that the first time point can also be said to be the time point at which the first image information 138 was generated by the imaging device 2.

[0060] [Judgment unit 107] The determination unit 107 determines the consistency between the estimation result by the estimation unit 106 and the declaration information 136 acquired by the acquisition unit 100. Determining the consistency typically means determining the presence or absence of consistency. In this case, the consistency is output as a binary value (i.e., "yes" or "no"), but the consistency may also be output as a continuous value (e.g., probability, stages, points, etc.).

[0061] When the difference between the estimation result and the reporting information 136 is small (for example, when the estimation result indicates that about 10 cm of flooding has occurred above the floor level at feature 3, and the insured's reporting included in the reporting information 136 indicates that 11 cm of flooding has occurred above the floor level), it is determined that there is consistency between the estimation result and the reporting information 136. In such a case, since it is assumed that there is no error in the insurance claim, it may be decided, for example, to omit the attendance of the damage situation and to provide compensation corresponding to the insured's reporting. When there is consistency between the estimation result and the reporting information 136, it can be said that the insurance claim is highly valid.

[0062] On the other hand, if there is a large difference between the estimation result and the declaration information 136 (for example, the estimation result indicates that flooding occurred 10 cm above the floor level at feature 3, but the insured's declaration included in the declaration information 136 indicates that flooding occurred 100 cm above the floor level), it is determined that there is no consistency between the estimation result and the declaration information 136. In such a case, it is estimated that there is an error in the insurance claim, and it is necessary to confirm the actual damage by, for example, witnessing the damage situation. If there is no consistency between the estimation result and the declaration information 136, it can be said that the insurance claim is of low validity.

[0063] [Decision Unit 108] ―Compensation determination unit 108a― The determination unit 108 determines the content of compensation based on the reporting information 136. Typically, the determination unit 108 determines the content of compensation when the determination unit 107 determines that there is consistency, and does not determine the content of compensation when the determination unit 107 determines that there is no consistency. The determination unit 108 can also be called a compensation determination unit 108a.

[0064] Compensation includes money and services provided by the insurance company to cover the damage. The content of compensation includes, for example, the amount of insurance money paid to the owner of the feature 3, arrangements for repairs of the feature 3, etc. The determination unit 108 may determine the content of compensation further based on the content of the contract between the insured, who is the owner of the feature 3, and the insurance company.

[0065] The determination unit 108 may determine the compensation content by referring to compensation information 137 in which the compensation content is associated with the declared inundation depth of the feature 3. The compensation information 137 may be a data table in which the compensation content corresponding to each of a plurality of stages related to the declared inundation depth is associated with the stage. The compensation information 137 is, for example, a data table in which the expected repair content of the feature 3 at each stage is associated with a stage in which the declared inundation depth based on the floor surface is 1 cm to 5 cm, a stage in which the declared inundation depth based on the floor surface is 5 cm to 25 cm, and a stage in which the declared inundation depth based on the floor surface is 25 cm to 50 cm.

[0066] -Error determination unit 108b- The determination unit 108 also determines the range of error of the estimated value of the estimated flood depth included in the flood damage information 140. The determination unit 108 can also be referred to as an error determination unit 108b.

[0067] As described above, the flood information 140 typically includes errors. When the errors occur almost uniformly throughout the region 7, the errors can be calibrated by the calibration information acquisition unit 100g, but this is not the case when the errors occur randomly for each coordinate. In such a case, the determination unit 108 may determine the error that may be included in the estimated flood depth based on the difference between the measured flood depth at multiple coordinates in the region 7 and the estimated flood depth at the multiple coordinates. For example, when the average of the measured flood depth at multiple coordinates is 50 cm and the average of the estimated flood depth at the multiple coordinates based on the flood information 140 is 52 cm, the determination unit 108 determines that the estimated flood depth includes an error of about 2 cm. In this case, the determination unit 107 may determine that the flood information 140 and the report information 136 are consistent when the reported flood depth related to the report information 136 is 50 cm to 52 cm.

[0068] The determination unit 108 may also determine the error of the estimated value based on the standard deviation or standard error of the estimated flood depth at multiple coordinates. For example, if the estimated flood depth at the multiple coordinates based on the flood information 140 follows a normal distribution with an average of 50 cm and a standard deviation of 5 cm, the determination unit 107 may determine that the flood information 140 and the report information 136 are consistent when the reported flood depth based on the ground level is 45 cm to 55 cm (i.e., average-standard deviation to average+standard deviation).

[0069] [Display section 110] The display unit 110 displays the flood situation in the area 7 and the coordinates of the feature 3 based on the flood information 140 and the position information 141. The display unit 110 may also display the flood situation in the area 7 and the coordinates of the feature 3 by superimposing them on a map of the area 7. In other words, the display unit 110 may display on the map where and to what extent the feature 3 is affected by the flood.

[0070] Furthermore, the display unit 110 may display the consistency determined by the determination unit 107 so that a person in charge of determining the contents of compensation (hereinafter, simply referred to as a "person in charge") can confirm it. This can assist the person in charge in processing the insurance claim.

[0071] [Notification section 112] When the determination unit 107 determines that there is no consistency, the notification unit 112 notifies the person in charge. The notification is typically displayed on the display screen of the terminal device 5. The notification unit 112 can also be called a transmission unit that transmits the notification, or a display control unit that controls to display the notification.

[0072] [Storage section 14] The memory unit 14 stores various programs executed by the control unit 10 as well as various information used for the operation of the information processing device 1. The memory unit 14 stores, for example, declaration information 136, compensation information 137, first image information 138, flood information 140, location information 141, feature information 142, SNS information 143, map information 144, height information 145, and calibration information 146.

[0073] [Network Interface Section 18] The network interface unit 18 realizes communication with the imaging device 2, the external storage device 4, and the terminal device 5 via the communication network 6. The communication by the network interface unit 18 may be realized in accordance with various communication standards.

[0074] [Imaging device 2] The imaging device 2 is a device capable of generating the first image information 138. The imaging device 2 is, for example, a camera mounted on an artificial satellite, an airplane, a drone (also called an unmanned aerial vehicle), or a vehicle. The imaging device 2 may store the generated first image information 138 in its own device, or may store it in the external storage device 4.

[0075] [Terminal device 5] The terminal device 5 is a device used by the insured person who is the owner of the feature 3. The terminal device 5 is, for example, a smartphone, a personal computer, a smart watch, a tablet terminal, or the like.

[0076] [External storage device 4] The external storage device 4 is an external device that the information processing device 1 accesses to acquire various information. The external storage device 4 may be, for example, a device installed in a data center. The external storage device 4 may store first image information 138, flood information 140, location information 141, feature information 142, SNS information 143, and map information 144. The external storage device 4 may receive information from the information processing device 1, the imaging device 2, and the feature 3, and store the information.

[0077] The external storage device 4 may store information about an external service. Specifically, the information processing device 1, the imaging device 2, and the feature 3 are typically included in a system owned by an insurance company, while the external storage device 4 may be, for example, a device of an SNS provider.

[0078] The external storage device 4 is not limited to being a standalone device, and may be a storage unit included in any device.

[0079] <3. Hardware configuration of information processing device 1> 4, an example of a hardware configuration in which the above-described information processing device 1 is realized by a computer 30 will be described. Note that the functions of each device can also be realized by dividing them into a plurality of devices.

[0080] As shown in FIG. 4, the computer 30 includes a processor 300, a storage device 302, an input I / F 304, a data I / F 306, a communication I / F 308, and a display device 310.

[0081] The processor 300 controls various processes in the computer 30 by executing programs stored in the storage device 302. For example, each functional unit included in the control unit 10 of the information processing device 1 can be realized by the processor 300 executing the programs stored in the storage device 302.

[0082] The storage device 302 is a storage medium such as a random access memory (RAM), etc. The RAM temporarily stores the program code of the program executed by the processor 300 and data required when the program is executed.

[0083] The storage device 302 may also be a non-volatile storage medium such as a hard disk drive (HDD) or a flash memory. The storage device 302 stores an operating system and various programs for implementing the above-mentioned configurations. The storage medium storing the various programs may be a non-transitory computer readable medium. In addition, the storage device 302 may store a table for registering various information such as business information, and a DB for managing the table. Such programs and data are loaded into the storage device 302 as necessary, and are referred to by the processor 300.

[0084] The input I / F 304 is a device for receiving input from a user. Specific examples of the input I / F 304 include a camera, a button, a microphone, a keyboard, a mouse, a touch panel, various sensors, a wearable device, etc. The input I / F 304 may be connected to the computer 30 via an interface such as a Universal Serial Bus (USB).

[0085] The data I / F 306 is a device for inputting data from outside the computer 30. A specific example of the data I / F 306 is a drive device for reading data stored in various storage media. The data I / F 306 may be provided outside the computer 30. In that case, the data I / F 306 is connected to the computer 30 via an interface such as a USB.

[0086] The communication I / F 308 is a device for performing data communication with an external device of the computer 30 via the communication network 6 in a wired or wireless manner. The communication I / F 308 may be provided outside the computer 30. In that case, the communication I / F 308 is connected to the computer 30 via an interface such as a USB.

[0087] The display device 310 is a device for displaying various types of information. Specific examples of the display device 310 include a liquid crystal display, an organic EL (Electro-Luminescence) display, and a display of a wearable device. The display device 310 may be provided outside the computer 30. In that case, the display device 310 is connected to the computer 30 via, for example, a display cable. In addition, when a touch panel is adopted as the input I / F 304, the display device 310 can be configured integrally with the input I / F 304.

[0088] The components of the information processing device 1 described in the above embodiment are assumed to realize a predetermined process in cooperation with other hardware by the processor 300 executing a program stored in the storage device 302. In other words, these components are assumed to be software or firmware, and also corresponding hardware, and in both concepts, they are also described as "functions," "means," "parts," "processing circuits," "units," or "modules," and can be interpreted as each of these.

[0089] <4. Operation of the information processing device 1> An example of the operation of the information processing device 1 will be described with reference to FIG.

[0090] First, the information processing device 1 acquires the first image information 138 including aerial image information (S100).

[0091] 6(A) shows an example of first image information 138 acquired by the information processing device 1. Fig. 6(A) is a conceptual diagram of aerial image information generated by an imaging device 2, which is an artificial satellite, photographing an area 7 from the sky. The aerial image information includes information on an image showing the state of flood damage in the area 7.

[0092] Next, the information processing device 1 generates flood information 140 based on the aerial image information included in the first image information 138 (S102).

[0093] 6(B) shows an example of flood information 140 generated by the information processing device 1. n ,Y m 6(A) and 6(B) are conceptual diagrams of flood information 140 in which the estimated flood depth at each coordinate is associated with n (where n and m are integers between 1 and 6). FIG. 6(B) shows, in different colors, coordinates where the estimated flood depth was recognized to be approximately 55 cm based on aerial image information, coordinates where the estimated flood depth was recognized to be approximately 70 cm, and coordinates where the estimated flood depth was recognized to be approximately 90 cm. The coordinates in FIG. 6(A) and the coordinates in FIG. 6(B) may be associated according to any mapping rule.

[0094] Next, the information processing device 1 acquires position information 141 of the feature 3 (S104). In this embodiment, the information processing device 1 is described as acquiring position information 141 of the feature 3a (coordinates [X1, Y1]), feature 3b (coordinates [X6, Y6]), feature 3c (coordinates [X1, Y4]), feature 3d (coordinates [X3, Y4]), and feature 3e (coordinates [X5, Y3]). Hereinafter, unless otherwise distinguished, the features 3a to 3e will be collectively referred to as "feature 3."

[0095] Next, the information processing device 1 acquires height information 145 (S105). In this embodiment, it is assumed that height information 145 indicating that the floor height of the feature 3a, feature 3b, and feature 3e based on the ground level is 45 cm, and that the floor height of the feature 3d based on the ground level is 50 cm is acquired. Note that it is assumed that information regarding the floor height of the feature 3c based on the ground level has not been acquired.

[0096] Next, the information processing device 1 estimates the damage caused to the feature 3 based on the flood information 140, the position information 141, and the height information 145 (S106). Note that in this embodiment, it is assumed that the estimated flood depth may include an error of about 5 cm. The correspondence relationship between each piece of information is shown with reference to Fig. 7.

[0097] In this embodiment, according to the flood information 140, the estimated flood depth at the coordinates of features 3a and 3b is about 55 cm. Furthermore, the floor height of features 3a and 3b relative to the ground level is 45 cm. Therefore, it can be estimated that above-floor flooding of about 10 cm occurred in features 3a and 3b (see the rows for "feature 3a" and "feature 3b" in Figure 7). Furthermore, taking into account possible errors in the estimated flood depth, if the reported flood depth is within the range of 5 cm to 15 cm, the reported information 136 and the estimation result are determined to be consistent.

[0098] Furthermore, in this embodiment, according to the flood information 140, the estimated flood depth at the coordinates of the feature 3d is approximately 90 cm. Furthermore, the floor height of the feature 3d relative to the ground level is 50 cm. Therefore, it can be estimated that above-floor flooding of approximately 40 cm occurred in the feature 3d (see the row "feature 3d" in Figure 7). Furthermore, taking into account possible errors in the estimated flood depth, if the reported flood depth is within the range of 35 cm to 45 cm, the reported information 136 and the estimation result are determined to be consistent.

[0099] Furthermore, in this embodiment, according to the flood information 140, the estimated flood depth at the coordinates of feature 3e is approximately 70 cm. Furthermore, the floor height of feature 3e relative to the ground level is 45 cm. Therefore, it can be estimated that above-floor flooding of approximately 25 cm occurred in feature 3e (see the row for "feature 3e" in Figure 7). Furthermore, taking into account possible errors in the estimated flood depth, if the reported flood depth is within the range of 20 cm to 30 cm, the reported information 136 and the estimation result are determined to be consistent.

[0100] In this embodiment, the flood damage information 140 indicates that the estimated flood depth at the coordinates of the feature 3c is approximately 70 cm. Information regarding the floor height of the feature 3 relative to the ground level has not been acquired. In such a case, the damage may be estimated by assuming that the floor height relative to the ground level is a predetermined value (e.g., 45 cm). For example, if the floor height of the feature 3c relative to the ground level is assumed to be 45 cm, it can be estimated that the feature 3c has experienced flooding above the floor level of approximately 25 cm (see the row for "feature 3c" in FIG. 7). Furthermore, taking into account possible errors in the estimated flood depth, if the reported flood depth is within the range of 20 cm to 30 cm, the reported information 136 and the estimation result are determined to be consistent.

[0101] Next, the information processing device 1 acquires the reporting information 136 (S108). In this embodiment, the reported flood depth for the feature 3a is 10 cm based on the floor surface. The reported flood depth for the feature 3b is 25 cm based on the floor surface. The reported flood depth for the feature 3c is 20 cm based on the floor surface. The reported flood depth for the feature 3d is 90 cm based on the ground surface. The reported flood depth for the feature 3e is 5 cm based on the floor surface.

[0102] Next, the information processing device 1 determines the consistency between the estimation result and the declared information 136 (S110). In this embodiment, the information processing device 1 determines that the estimation result and the declared information 136 are consistent when the declared flood depth based on the floor surface is within a predetermined range that takes into account the error that may be included in the estimated flood depth (see the column "Consistent range of declared flood depth" in Figure 7). In other words, the information processing device 1 determines that the estimation result and the declared information 136 are consistent when the difference between the estimated flood depth and the declared flood depth is within the error range. Referring to Figure 8, the correspondence between each piece of information is shown.

[0103] In this embodiment, the declared flood depth for the feature 3a (approximately 10 cm from the floor) is within the range of consistent declared flood depths (approximately 5 cm to 15 cm). Therefore, the information processing device 1 determines that the estimation result and the declared information 136 for the feature 3a are consistent (see the row for "feature 3a" in FIG. 8).

[0104] In this embodiment, the declared flood depth for feature 3b (approximately 25 cm from the floor) exceeds the range of consistent declared flood depths (approximately 5 cm to 15 cm). Therefore, the information processing device 1 determines that there is no consistency between the estimation result and the declared information 136 for feature 3b (see the row for "feature 3b" in FIG. 8).

[0105] In this embodiment, the declared flood depth for feature 3c (about 20 cm based on the floor surface) is within the range of consistent declared flood depths (about 20 cm to 30 cm). Therefore, the information processing device 1 determines that there is consistency between the estimation result and the reported information 136 for feature 3b (see the row for "feature 3c" in Fig. 8). However, since the information processing device 1 estimates above-floor flooding for feature 3c by assuming that the floor height is 45 cm based on the ground surface, although it determines there is consistency, it may further associate a caution flag.

[0106] For the feature 3d, the declared inundation depth based on the ground surface is acquired. The information processing device 1 may calculate the declared inundation depth based on the floor surface based on the floor height based on the ground surface and the declared inundation depth based on the ground surface. In this embodiment, the declared inundation depth of the feature 3d based on the ground surface is 90 cm, and the floor height based on the ground surface is 50 cm, so the information processing device 1 can calculate that the declared inundation depth based on the floor surface is 40 cm. The declared inundation depth of the feature 3d (about 40 cm based on the floor surface) is included in the range of the declared inundation depth that is consistent (about 35 cm to 45 cm). Therefore, the information processing device 1 determines that the estimation result and the declared information 136 related to the feature 3d are consistent (see the row of "feature 3d" in FIG. 8).

[0107] In this embodiment, the declared flood depth for feature 3e (approximately 5 cm from the floor) is below the range of consistent declared flood depths (20 cm to 30 cm). Therefore, the information processing device 1 determines that there is no consistency between the estimation result and the declared information 136 for feature 3e (see the row for "feature 3e" in FIG. 8).

[0108] If it is determined that there is a consistency between the estimation result and the declaration information 136, at least a part of one or more processes for providing compensation to the insured person may be omitted. For example, the presence of an insurance company representative when determining the damage caused to the feature 3 may be omitted.

[0109] <5. Other operations of the information processing device 1> So far, a description has been given of an example in which the information processing device 1 generates the flood damage information 140 based on the aerial image information included in the first image information 138. Below, a description will be given of a method for estimating damage caused to features 3 with even higher accuracy.

[0110] Another example of the first image information 138 acquired by the information processing device 1 will be described with reference to Fig. 9(A). Fig. 9(A) is a conceptual diagram of aerial image information generated by an imaging device 2, which is an artificial satellite, photographing an area 7 from the sky. As shown in Fig. 9(A), when the weather in the area 7 is bad, it may not be possible to fully grasp the flood situation in the area 7 based only on the aerial image information.

[0111] An example of flood information 140 generated based on aerial image information such as that in Fig. 9(A) will be described with reference to Fig. 9(B). In Fig. 9(B), information on flood depth is not correctly associated with coordinates in region 7 that correspond to coordinates where the weather is bad (see "Unknown Area" in Fig. 9(B)). In other words, aerial image information such as that in Fig. 9(A) does not allow the flood situation to be grasped with sufficient accuracy.

[0112] With reference to Fig. 10, an example of a method for generating flood information 140 based on additional information (e.g., vehicle image information, feature information 142, and SNS information 143) in addition to the aerial image information included in the first image information 138, and estimating damage caused to the feature 3 will be described. Note that S100 and S104-S110 in Fig. 10 are similar to S100 and S104-S110 described with reference to Fig. 5, and therefore description thereof will be omitted below.

[0113] After acquiring the aerial image information, the information processing device 1 acquires additional information (S200). In this embodiment, the information processing device 1 acquires vehicle image information from a vehicle (hereinafter simply referred to as a "vehicle") equipped with a camera that is an imaging device 2, and acquires feature information 142 and SNS information 143 from the external storage device 4.

[0114] An example of vehicle image information acquired by the information processing device 1 will be described with reference to Fig. 11. The vehicle image information is information in which, for each of one or more vehicles (vehicles α and β in this example), the coordinates of the vehicle are associated with a vehicle image captured by the vehicle at the coordinates. In this embodiment, it is assumed that the vehicle image captured by vehicle α allows one to grasp that flooding of about 70 cm has occurred at coordinates [X4, Y4] based on the ground surface. It is also assumed that the vehicle image captured by vehicle β allows one to grasp that flooding of about 90 cm has occurred at coordinates [X4, Y2] based on the ground surface.

[0115] An example of the feature information 142 acquired by the information processing device 1 will be described with reference to Fig. 12. The feature information 142 is information in which, for each of one or more features for which flood damage has already been identified, the coordinates of the feature are associated with the flood depth at those coordinates. According to the feature information 142 in Fig. 12, it can be ascertained that the flood depths at the coordinates [X5, Y2], [X3, Y2], and [X5, Y3] are approximately 90 cm, 70 cm, and 70 cm, respectively, based on the ground level.

[0116] An example of the SNS information 143 acquired by the information processing device 1 will be described with reference to Fig. 13. The SNS information 143 is information in which, for each of one or more posts, the coordinates at which the post was made and the content of the post are associated with each other. Note that, for some posts, no coordinates are associated with each post.

[0117] The extraction unit 104 extracts posts related to the status of flood damage in the region 7 from the multiple posts in the SNS information 143. In this embodiment, the extraction unit 104 extracts posts that satisfy all of the following conditions from the multiple posts.

[0118] 1) The post contains information about flood conditions. The extraction unit 104 may extract a post including information related to the flood situation from the multiple posts. A post including information related to the flood situation is, for example, a post including words such as "flooding," "submersion," "evacuation," and "rescue" in text information associated with the post. Another example of a post including information related to the flood situation is a post including an image showing the flood situation associated with the post.

[0119] 2) The post contains information about coordinates, and those coordinates are within Region 7. The extraction unit 104 may extract posts associated with coordinates of the region 7 from the multiple posts.

[0120] In this embodiment, the extraction unit 104 extracts a post 500, a post 502, a post 506, a post 508, and a post 510 from the multiple posts shown in FIG. 13 based on the above conditions. Among these, the post 500, the post 502, and the post 510 are associated with the coordinates of the region 7, and include text information indicating the flood situation, such as "flooded" and "water". Although the post 506 is not directly associated with the coordinates, the text information includes information that can identify the coordinates, and the text information indicates the flood situation, such as "a car submerged in water". Although the post 508 does not include text information, an image indicating the flood situation is associated with it. It is assumed that the image associated with the post 508 is an image of an outdoor area flooded to a depth of about 70 cm based on the ground level.

[0121] In this embodiment, it is assumed that, according to post 500, it is possible to know that about 90 cm of flooding has occurred at coordinates [X4, Y3]. Furthermore, according to post 502, it is possible to know that about 70 cm of flooding has occurred at coordinates [X2, Y3]. Furthermore, according to post 506, it is possible to know that about 90 cm of flooding has occurred at coordinates [X3, Y3]. Furthermore, according to post 508, it is possible to know that about 70 cm of flooding has occurred at coordinates [X4, Y1]. Furthermore, according to post 510, it is possible to know that about 90 cm of flooding has occurred at coordinates [X5, Y1].

[0122] The flood situation that can be understood based on the additional information described with reference to Figures 11 to 13 can be summarized as follows. Coordinates [X2,Y3]: Flooding of about 70cm (from post 502 of SNS information 143) Coordinates [X3,Y2]: 70cm flooding (from building 410 of feature information 142) Coordinates [X3,Y3]: Flooding of about 90cm (from post 506 of SNS information 143) Coordinates [X4, Y1]: 70cm of flooding (from post 508 of SNS information 143) Coordinates [X4, Y2]: Flooding of about 90 cm (from vehicle image of vehicle α) Coordinates [X4,Y3]: Flooding of about 90cm (from post 500 of SNS information 143) Coordinates [X4, Y4]: 70cm of flooding (from vehicle image of vehicle β) Coordinates [X5, Y1]: Flooding of about 90 cm (from post 510 of SNS information 143) Coordinates [X5,Y2]: Flooding of about 90cm (from building 408 of feature information 142) Coordinates [X5,Y3]: Flooding of about 70cm (from building 412 of feature information 142)

[0123] After acquiring the additional information, the information processing device 1 generates flood information 140 based on the aerial image information and the additional information (S202).

[0124] An example of flood information 140 generated by the information processing device 1 will be described with reference to Fig. 14. Compared with the flood information 140 generated based on aerial image information shown in Fig. 9(B), the flood information 140 in Fig. 14 can be largely supplemented with additional information. By supplementing the flood information 140 in this way, the information processing device 1 can estimate damage to features 3 in the area 7 with high accuracy.

[0125] <6. Display screen example> The information processing device 1 may display the flood situation in a predetermined area and the position of the feature 3 on the display unit 110 based on the flood information 140 and the position information 141. The information processing device 1 may also acquire map information 144 related to a map of the area 7 using the acquisition unit 100, and display the flood situation in the area 7 and the position of the feature 3 by superimposing it on the map.

[0126] Fig. 15 is an example of a display screen in which the flood situation and the coordinates of feature 3 are superimposed on a map of region 7. Specifically, in Fig. 15, the flood situation is displayed on the map using a heat map (i.e., using colors according to the stages of flood depth), and the coordinates of feature 3 are superimposed. Furthermore, the display unit 110 may further superimpose and display feature information 142 and SNS information 143.

[0127] This allows, for example, an insurance company employee to intuitively grasp the flood situation in area 7 and the damage caused to feature 3, enabling more efficient compensation to be provided.

[0128] <7. Effects> An information processing device 1 according to one embodiment of the present disclosure includes a generation unit 102 that generates flood information 140 regarding the flood situation in a specified area 7 based on first image information generated by an imaging device 2 that photographs a specified area 7 from the sky, a location information acquisition unit 100b that acquires location information 141 regarding the location of a feature 3 in the area 7, an estimation unit 106 that estimates damage caused to the feature 3 due to flood based on the flood information 140 and the location information 141, a declaration information acquisition unit 100f that acquires declaration information 136 regarding declarations of damage caused to the feature 3 due to flood, and a determination unit 107 that determines the consistency between the estimation result by the estimation unit 106 and the declaration information 136.

[0129] Generally, when a flood occurs, many insurance claims are made in a short period of time for multiple features 3 in a relatively small area. In response to this, the person in charge needs to check the validity of the accepted insurance claims. For example, the person in charge needs to check whether there are any mistakes in the input items of the insurance claim, whether the insurance claim is a fictitious claim, etc.

[0130] According to the information processing device 1, the validity of an insurance claim can be determined. This reduces the need for a person in charge to determine the validity of an insurance claim, thereby improving the efficiency of processing related to insurance claims.

[0131] In one embodiment, the declared information 136 includes second image information generated by photographing a reference object indicating the flood damage situation and the feature 3. The information processing device 1 calculates the declared flood depth of the feature 3 based on the second image information.

[0132] According to this configuration, the insured can file an insurance claim without measuring the declared flood depth by himself / herself, by transmitting the declaration information 136 including the second image information to the information processing device 1. As a result, the convenience of the insured when filing an insurance claim is improved.

[0133] In one embodiment, the feature 3 is a building, and the information processing device 1 further includes a height information acquisition unit 100h that acquires height information 145 related to the floor height of the feature 3, and the estimation unit 106 estimates the damage caused to the feature 3 due to flood damage based further on the height information 145.

[0134] According to this configuration, the information processing device 1 can grasp the degree of flooding above floor level in the feature 3 more accurately.

[0135] In one embodiment, the information processing device 1 further includes a compensation determination unit 108a that determines the content of compensation based on the declared information 136 when the determination unit 107 determines that there is consistency, and a notification unit 112 that notifies a person in charge of determining the content of compensation when the determination unit 107 determines that there is no consistency.

[0136] According to this configuration, the information processing device 1 typically automatically determines the contents of compensation if there is a match, and notifies the person in charge if there is no match. As a result, it is possible to achieve both speed and flexibility in processing insurance claims.

[0137] In one embodiment, the compensation determination unit 108a determines the details of compensation by referring to compensation information 137 in which the details of compensation are associated with the flood depth of the feature 3 (typically, the declared flood depth).

[0138] With this configuration, the information processing device 1 can determine the details of compensation without relying on information other than the reported flood depth (for example, the actual flood depth, details of flooded furniture and home appliances, the number of pillars to be repaired, etc.). As a result, the processing of insurance claims can be made more efficient.

[0139] In one embodiment, the flood information 140 includes an estimated value of the flood depth of the area 7, and the information processing device 1 further includes an error determination unit 108b that determines an error range of the estimated value, and the determination unit 107 determines the consistency based on the error range. In another embodiment, the flood information 140 includes an estimated value of the flood depth of the area 7, and the information processing device 1 further includes a calibration information acquisition unit 100g that acquires calibration information 146 in which an error included in the estimated value has been calibrated, and the estimation unit 106 uses the calibration information 146 as the flood information 140.

[0140] According to this configuration, the information processing device 1 can determine consistency more accurately. As described above, the flood information 140 may contain errors. If consistency is determined without taking these errors into consideration, the probability of erroneous determination (so-called false positives and false negatives) increases.

[0141] In one embodiment, the flood information 140 includes snapshot information on the flood depth at the position of the feature 3 at a first time point, and the estimation unit 106 estimates the damage caused to the feature 3 at a second time point based on the snapshot information and the relationship between the first time point and the second time point. Also, in one embodiment, the second time point is selected from a plurality of time points based on the change in flood depth over time.

[0142] The declared flood depth is typically the maximum flood depth among the actually measured flood depths that may change over time. This is because damage to the feature 3 typically occurs according to the maximum flood depth. In contrast, the flood information 140 does not necessarily reflect the flood situation at the time when the flood depth was at its maximum due to the influence of the shooting period of the imaging device 2, etc. This configuration makes it possible to prevent erroneous judgments caused by the difference between a first point in time (e.g., the time when the first image information 138 was generated) and a second point in time (e.g., the time when the flood depth reached its maximum).

[0143] <8. Variations> In the above embodiment, the information processing device 1 has been described as acquiring aerial image information from the imaging device 2 which is an artificial satellite, but this is not limited thereto. Specifically, the imaging device 2 may include a plurality of imaging devices 2 each capturing images from different altitudes, and the first image information 138 may include information on images generated by each of the plurality of imaging devices 2. In other words, the information processing device 1 may acquire aerial image information from each of an artificial satellite, an airplane, a drone, etc., and generate flood information 140 based on this.

[0144] This enables the information processing device 1 to generate more accurate flood information 140. As described with reference to Fig. 9(A), depending on the weather in the area 7, it may not be possible to adequately grasp the flood situation from an image captured from a specific altitude. In response to this, the information processing device 1 can obtain aerial image information from a plurality of imaging devices 2 that capture images from different altitudes, thereby obtaining a plurality of pieces of aerial image information that are complementary to each other.

[0145] For example, with a drone, even if there are clouds as in Figure 9(A), it is possible to grasp the flood situation in area 7 (at least partially). On the other hand, with an artificial satellite, it is possible to grasp the flood situation over a wide area, even if it is not possible to grasp the flood situation in the cloudy areas. In this way, by utilizing multiple imaging devices 2 that take images from different altitudes, it is possible to realize more efficient compensation provision.

[0146] <9. Other embodiments> The information processing device 1 may be a device made up of multiple devices, or may be a part of another device.

[0147] The technical matters described in the above embodiments can be rearranged, combined, or partially extracted for use based on the knowledge of those skilled in the art.

[0148] The following embodiments are also included in the present invention.

[0149] [Appendix 1] An information processing device 1 according to one embodiment of the present disclosure includes a generation unit 102 that generates flood information 140 regarding the flood situation in a specified area 7 based on first image information generated by an imaging device 2 that photographs a specified area 7 from the sky, a location information acquisition unit 100b that acquires location information 141 regarding the location of a feature 3 in the area 7, an estimation unit 106 that estimates damage caused to the feature 3 due to flood based on the flood information 140 and the location information 141, a declaration information acquisition unit 100f that acquires declaration information 136 regarding declarations of damage caused to the feature 3 due to flood, and a determination unit 107 that determines the consistency between the estimation result by the estimation unit 106 and the declaration information 136.

[0150] [Appendix 2] In the information processing device 1 described in Supplementary Note 1, the report information 136 may include second image information generated by photographing a reference object indicating the flood damage situation and the feature 3.

[0151] [Appendix 3] In the information processing device 1 described in Appendix 1 or Appendix 2, the feature 3 may be a building, and may further include a height information acquisition unit 100h that acquires height information 145 related to the floor height of the feature 3, and the estimation unit 106 may further estimate damage caused to the feature 3 due to flooding based on the height information 145.

[0152] [Appendix 4] The information processing device 1 described in any one of Supplementary Notes 1 to 3 may further include a compensation determination unit 108a that determines the content of compensation based on the declared information 136 when the determination unit 107 determines that there is consistency, and a notification unit 112 that notifies a person in charge of determining the content of compensation when the determination unit 107 determines that there is no consistency.

[0153] [Appendix 5] In the information processing device 1 described in Supplementary Note 4, the compensation determination unit 108a may determine the details of compensation by referring to compensation information 137 in which the details of compensation are associated with the flood depth of the feature 3.

[0154] [Appendix 6] In the information processing device 1 described in any one of Appendices 1 to 5, the flood information 140 may include an estimated value of the flood depth in the area 7, and the information processing device 1 may further include an error determination unit 108b that determines the error range of the estimated value, and the judgment unit 107 may judge the consistency based on the error range.

[0155] [Appendix 7] In an information processing device 1 described in any one of Appendices 1 to 6, the flood information 140 may include an estimated value of the flood depth in the area 7, and the information processing device 1 may further include a calibration information acquisition unit 100g that acquires calibration information 146 that calibrates the error contained in the estimated value, and the estimation unit 106 may use the calibration information 146 as the flood information 140.

[0156] [Appendix 8] In the information processing device 1 described in any one of Appendices 1 to 7, the flood information 140 may include snapshot information regarding the flood depth at the position of the feature 3 at a first time point, and the estimation unit 106 may estimate the damage caused to the feature 3 at a second time point based on the snapshot information and the relationship between the first time point and the second time point.

[0157] [Appendix 9] In the information processing device 1 described in Supplementary Note 8, the second point in time may be selected from a plurality of points in time based on changes in flood depth over time.

[0158] [Appendix 10] In the information processing device 1 described in any one of Supplementary Notes 1 to 10, the imaging device 2 may include a plurality of imaging devices 2 each capturing images from different altitudes, and the first image information may include information regarding images generated by each of the plurality of imaging devices 2.

[0159] [Appendix 11] In an information processing device 1 described in any one of Appendices 1 to 10, there may be other features 3 in the vicinity of a feature 3 in an area 7, the information processing device 1 may be able to access information regarding the actual flood situation of the other features 3, and the generation unit 102 may generate flood information 140 further based on the information regarding the actual flood situation of the other features 3.

[0160] [Appendix 12] The information processing device 1 described in any one of Appendices 1 to 11 may be capable of accessing multiple posts on a social networking service, and may further include an extraction unit 104 that extracts posts related to the flood situation in area 7 from the multiple posts by pattern recognition, and the generation unit 102 may generate flood information 140 further based on the posts extracted by the extraction unit 104.

[0161] [Appendix 13] The information processing device 1 according to any one of Supplementary Note 1 to Supplementary Note 12 may further include a display unit 110 that displays the flood situation in the area 7 and the position of the feature 3 based on the flood information 140 and the position information 141.

[0162] [Appendix 14] The information processing device 1 described in Appendix 13 may further include a map information acquisition unit 100e that acquires map information regarding a map of the area 7, and the flood situation in the area 7 and the position of the feature 3 may be displayed superimposed on the map of the area 7 by the display unit 110.

[0163] [Appendix 15] A program according to another embodiment of the present disclosure causes a computer 30 to function as a generation means for generating flood information 140 regarding the flood situation in a specified area 7 based on first image information generated by an imaging device 2 that photographs a specified area 7 from the sky, a location information 141 acquisition means for acquiring location information 141 regarding the location of a feature 3 in the area 7, an estimation means for estimating damage caused to the feature 3 by flood based on the flood information 140 and the location information 141, a declaration information 136 acquisition means for acquiring declaration information 136 regarding the declaration of damage actually caused to the feature 3 by flood, and a determination means for determining the consistency between the estimation result by the estimation means and the declaration information 136.

[0164] [Appendix 16] An information processing method according to another embodiment of the present disclosure causes a computer 30 to execute the following steps: a generation step of generating flood information 140 regarding the flood situation in a specified area 7 based on first image information generated by an imaging device 2 that photographs a specified area 7 from the sky; a location information 141 acquisition step of acquiring location information 141 regarding the location of a feature 3 in the area 7; an estimation step of estimating damage caused to the feature 3 due to flood based on the flood information 140 and the location information 141; a declaration information 136 acquisition step of acquiring declaration information 136 regarding a declaration of damage actually caused to the feature 3 due to flood; and a determination step of determining the consistency between the estimation result from the estimation step and the declaration information 136. [Explanation of symbols]

[0165] 1...information processing device, 2...imaging device, 3...feature, 5...terminal device, 6...communication network, 7...area, 10...control unit, 14...storage unit, 30...computer, 100...acquisition unit, 100a...image information acquisition unit, 100b...location information acquisition unit, 100c...feature information acquisition unit, 100d...SNS information acquisition unit, 100e...map information acquisition unit, 100f...declaration information acquisition unit, 100g...calibration information acquisition unit, 100g...calibration information acquisition means, 100h...information acquisition unit, 102...generation unit, 104...extraction unit, 106...estimation unit, 107...judgment unit, 108...determination unit, 108a...compensation determination unit, 108b...error determination unit, 110...display unit, 112...notification unit

Claims

1. a generation unit that generates flood information regarding a flood situation in a predetermined area based on first image information generated by an imaging device that photographs the predetermined area from the sky; a location information acquisition unit that acquires location information relating to the locations of features in the area; an estimation unit that estimates damage caused to the feature by the flood based on the flood information and the position information; a reporting information acquisition unit that acquires reporting information regarding reporting of damage caused to the feature by the flood; a determination unit that determines a consistency between an estimation result by the estimation unit and the declared information; An information processing device comprising:

2. The information processing apparatus according to claim 1 , wherein the reporting information includes second image information generated by photographing a reference object indicating the flood damage situation and the feature.

3. The feature is a building, a height information acquisition unit for acquiring height information relating to a floor height of the feature; The information processing device according to claim 1 , wherein the estimation unit estimates damage caused to the feature by the flood disaster further based on the height information.

4. a compensation determination unit that determines the content of compensation based on the declared information when the determination unit determines that the consistency exists; a notification unit that notifies a person in charge of determining the content of the compensation when the determination unit determines that there is no consistency; The information processing device according to claim 1 , further comprising:

5. The information processing device according to claim 4 , wherein the compensation determination unit determines the content of the compensation by referring to compensation information in which the content of the compensation is associated with the flood depth of the feature.

6. The flood information includes an estimated flood depth of the area; An error determination unit for determining a range of error of the estimated value, The information processing apparatus according to claim 1 , wherein the determination unit determines the consistency based on the range of error.

7. The flood information includes an estimated flood depth of the area; a calibration information acquisition unit that acquires calibration information obtained by calibrating an error included in the estimated value, The information processing device according to claim 1 , wherein the estimation unit uses the calibration information as the flood damage information.

8. The flood information includes snapshot information regarding flood depth at the location of the feature at a first time point; The information processing apparatus according to claim 1 , wherein the estimation unit estimates the damage caused to the feature at a second time point based on the snapshot information and a relationship between the first time point and the second time point.

9. The information processing device according to claim 8 , wherein the second time point is selected from a plurality of time points based on a change in flood depth over time.

10. The imaging device includes a plurality of imaging devices each of which captures images from different altitudes, The information processing apparatus according to claim 1 , wherein the first image information includes information on images generated by each of the plurality of imaging devices.

11. The area includes other features around the feature, having access to information regarding actual flood conditions of said other features; The information processing device according to claim 1 , wherein the generating unit generates the flood information further based on information regarding actual flood conditions of the other features.

12. Access to multiple posts from social networking services; An extraction unit that extracts posts related to the flood situation in the area from the plurality of posts by pattern recognition, The information processing device according to claim 1 , wherein the generation unit generates the flood information further based on the posts extracted by the extraction unit.

13. The information processing apparatus according to claim 1 , further comprising a display unit that displays a flood situation in the area and the positions of the features based on the flood information and the position information.

14. a map information acquisition unit for acquiring map information relating to a map of the area; The information processing device according to claim 13 , wherein the display unit displays the flood situation in the area and the positions of the features in a superimposed manner on a map of the area.

15. Computer, a generation means for generating flood information relating to a flood situation in a predetermined area based on first image information generated by an imaging device that photographs the area from the sky; A location information acquisition means for acquiring location information relating to the locations of features in the area; an estimation means for estimating damage caused to the feature by the flood based on the flood information and the position information; a reporting information acquisition means for acquiring reporting information regarding reporting of damage caused to the feature by the flood; A determination means for determining consistency between an estimation result by the estimation means and the declared information; A program that functions as a

16. On the computer, A generation step of generating flood information regarding a flood situation in a predetermined area based on first image information generated by an imaging device that photographs the predetermined area from the sky; a position information acquisition step of acquiring position information relating to the positions of features in the area; an estimation step of estimating damage caused to the feature by the flood based on the flood information and the position information; a declaration information acquisition step of acquiring declaration information regarding a declaration of damage caused to the feature by the flood; a determination step of determining consistency between an estimation result by the estimation step and the declared information; An information processing method.

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