JP6874196B1 - Information processing device and information processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing apparatus and an information processing method capable of determining whether or not the inundation depth is equal to or more than a reference depth based on an index according to a business attribute.
An information processing system 1 observes a business attribute acquisition unit 131 that acquires a business attribute that is information indicating a business purpose, a determination model determination unit 132 that determines a determination model associated with the business attribute, and an observation. By applying the plurality of provisional judgment results obtained by analyzing each of the plurality of satellite images having different frequencies to the judgment model determined by the determination unit, the inundation depth for the contractor is equal to or greater than the reference depth. It includes a determination result generation unit 134 that generates a determination result indicating the above, and an output unit that outputs the determination result generated by the determination result generation unit 134.
[Selection diagram] Fig. 1

Description

The present invention relates to an information processing device and an information processing method for determining whether or not the inundation depth of a non-life insurance policyholder for a flood disaster is equal to or greater than a reference depth.

Traditionally, in the operation of non-life insurance, when a flood such as heavy rain or torrential rain due to a typhoon occurs, a large number of investigators dispatched to the site conduct a field survey to confirm the degree of the flood. ing. In this regard, from the viewpoint of reducing the burden of investigation and improving efficiency, a technique for estimating the degree of disaster at each point using satellite images has been proposed (for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2005-78566

There are a wide variety of tasks for which it is necessary to calculate the predicted value of inundation depth in the event of a flood, but the important indicators for each task are not necessarily the same. For example, in the work of identifying a flood disaster area, the "recall rate", which indicates how much the contractors who actually suffered a flood disaster can be captured, is emphasized. On the other hand, for example, in the business of calculating the damage amount of each contractor, the "compliance rate" indicating how many contractors who were predicted to have suffered a flood disaster actually suffered a flood disaster is included. It is emphasized.

Therefore, the present invention provides an information processing apparatus and an information processing method capable of determining whether or not the inundation depth is equal to or greater than the reference depth based on an index according to the attributes of the business. With the goal.

The information processing device according to one aspect of the present invention associates a business attribute, which is information indicating a business purpose, with a business attribute acquisition unit acquired from another information processing device and a business attribute acquired by the business attribute acquisition unit. The inundation depth for the non-life insurance policyholders related to flood disasters obtained by analyzing each of the judgment model determination unit that determines the judgment model and the multiple satellite images with different observation frequencies is greater than or equal to the standard depth. By applying the provisional judgment result acquisition unit that acquires a plurality of provisional judgment results indicating the presence or absence and the judgment model determined by the determination unit, the inundation depth of the contractor is used as a reference. It includes a determination result generation unit that generates a determination result indicating whether or not the depth is greater than or equal to the depth.

According to the present invention, it is possible to provide an information processing apparatus and an information processing method capable of determining whether or not the inundation depth is equal to or greater than the reference depth based on an index according to the attribute of business. Can be done.

It is a figure which shows an example of the structure of the information processing system 1. It is a figure which shows an example of the data structure of the contractor data table. It is a figure which shows an example of the data structure of the judgment model table. It is a figure which shows the specific example of the determination result by the information processing system 1. It is a figure which showed an example of the operation sequence of the information processing system 1. It is a figure which shows an example of the mapping image.

Preferred embodiments of the present invention will be described with reference to the accompanying drawings. (In each figure, those having the same reference numerals have the same or similar configurations.)

(1) Configuration (1-1) Information processing system 1
FIG. 1 is a diagram showing an example of the configuration of the information processing system 1 according to the present embodiment. The information processing system 1 according to the present embodiment is a system for determining whether or not the inundation depth is equal to or greater than the reference depth for each non-life insurance policyholder (insurance policyholder) related to flood disasters. Here, the reference depth may be the depth that determines the necessity of payment of insurance money in the insurance contract. In other words, in the insurance contract, insurance payment is required when the inundation depth is equal to or greater than the standard depth, and insurance payment is not required when the inundation depth is less than the standard depth. Will be.

As shown in FIG. 1, the information processing system 1 according to the present embodiment includes, for example, a server device 10, a client terminal 20, a plurality of satellite image analysis systems 30, and an SNS information DB 40. The server device 10, the client terminal 20, the plurality of satellite image analysis systems 30, and the SNS information DB 40 are connected to each other so as to be able to communicate with each other via a communication network such as the Internet.

Each satellite image analysis system 30 acquires a satellite image generated at a predetermined observation frequency from a predetermined artificial satellite and analyzes it to calculate the inundation depth at each point included in the satellite image. Each policyholder determines whether or not the inundation depth is equal to or greater than the reference depth, and transmits the determination result to the server device 10 as a provisional determination result. The reference depth can be arbitrarily set according to the contract contents, but may be, for example, 45 cm.

The analysis method by each satellite image analysis system 30 is not particularly limited, but for example, a tentative determination result may be generated by applying the satellite image generated by the imaging device to a predetermined learning model. At that time, for example, a digital elevation model in which the position information and the altitude are associated with each other, a land use map in which the position information and the land usage mode are associated with each other, and the like may be referred to. In addition, each satellite image analysis system 30 may acquire learning data in which the accident reception status and the insurance claim payment status, which will be described later, are given as correct answer labels from the client terminal 20 or the like, and update the learning model with the learning data. ..

The information processing system 1 according to the present embodiment includes a visible light satellite image analysis system 30A and a SAR satellite image analysis system 30B as an example of the satellite image analysis system 30. Here, the visible light satellite image analysis system 30A generates a tentative determination result by analyzing a visible light satellite image which is a satellite image generated by visible light (that is, having a visible light region as an observation frequency). , This is supplied to the server device 10.

Further, the SAR satellite image analysis system 30B is a satellite image generated by microwaves that can transmit clouds and the like (that is, the observation frequency is microwaves) used by a synthetic aperture radar (SAR). By analyzing the satellite image, a tentative determination result is generated and supplied to the server device 10. The satellite image to be analyzed by the satellite image analysis system 30 may be a satellite image other than the visible light satellite image or the SAR satellite image (satellite image generated by an observation frequency other than visible light or microwave). ..

The SNS information DB 40 stores a plurality of text information input by the user at any social networking site (SNS). Here, the text information may be information including arbitrary text such as a writing or a comment input by the user, for example. The SNS information DB 40 may store the text information in association with bibliographic information about the user such as a user ID, information indicating the time when the text information is input, and the like. Further, the SNS information DB 40 may store the text information in the SNS information DB 40 by the user associating the text information with the user's position information. The user's position information may be acquired by, for example, an information processing device used by the user to input the text information.

(1-2) Server device 10
The server device 10 is an information processing device that performs various analyzes related to flood disasters based on information acquired from the satellite image analysis system 30, the SNS information DB 40, and the like. For example, the server device 10 acquires a provisional determination result described later from the satellite image analysis system 30, and based on the provisional determination result, determines whether the inundation depth is equal to or greater than the reference depth for each policyholder. Generate the final judgment result and output it. Further, the server device 10 acquires, for example, a plurality of text information from the SNS information DB 40, generates disaster information described later based on the plurality of text information, and outputs the damage information. Further, the server device 10 generates, for example, inundation information described later based on the generated damage information, corrects the above-mentioned determination result based on the inundation information, and outputs the inundation information. The server device 10 has a communication unit 11, a storage unit 12, and a processing unit 13.

The communication unit 11 has a communication interface circuit for connecting the server device 10 to the client terminal 20, the satellite image analysis system 30, and the like. The communication unit 11 supplies the data received from the client terminal 20, the satellite image analysis system 30, and the like to the processing unit 13. Further, the communication unit 11 transmits the data supplied from the processing unit 13 to the client terminal 20, the satellite image analysis system 30, and the like.

The storage unit 12 has, for example, at least one of a semiconductor memory, a magnetic disk device, and an optical disk device. The storage unit 12 stores a driver program, an operating system program, an application program, data, and the like used for processing by the processing unit 13. For example, the storage unit 12 stores a communication device driver program or the like that controls the communication unit 11 as a driver program. The various programs may be installed in the storage unit 12 from a computer-readable portable recording medium such as a CD-ROM or a DVD-ROM using a known setup program or the like. The storage unit 12 stores the contractor data table, the determination model table, and the like as data. Further, the storage unit 12 may temporarily store temporary data related to a predetermined process.

FIG. 2 is a diagram showing an example of the data structure of the contractor data table. The policyholder data table is a table for managing the contract details for each policyholder, as well as the status of accident reception and the status of insurance payments. The contractor data table may include, for example, a contractor ID, a contractor's name and address, contract details, an accident reception status, an insurance claim payment status, and the like. The contractor ID is identification information (ID) for identifying the contractor. The contract content is not particularly limited as long as it is the contract content related to the insurance contract, and may include, for example, the subject of compensation, the content of compensation, the insurance amount, the insurance period, and the like. The accident reception status is information indicating whether or not the policyholder has contacted the insurance company regarding the flood disaster, the content of the contact, and the like. The insurance claim payment status is information indicating whether or not the insurance claim has been paid to the policyholder.

FIG. 3 is a diagram showing an example of the data structure of the determination model table. The judgment model table is a table that defines the correspondence between the judgment model and the business attribute. Here, the business attribute is information indicating the purpose of each business. The types of business attributes are not particularly limited and can be set arbitrarily. For example, "(1) Flood disaster information collection / identification of disaster area", "(2) Damage investigation", "(3) Claim recommendation", and " (4) Calculation / payment of damage amount ”may be included.

"(1) Flood disaster information collection / identification of disaster area" is a business attribute that mainly aims to determine how to allocate response resources to each area in the event of a flood disaster. .. "(2) Damage investigation" is a business attribute that aims to grasp the degree of damage to the contractor who received the accident and make a decision to make a payment without the need for an on-site damage investigation. is there. "(3) Billing recommendation" aims to extract customers who have not been billed despite the high possibility of damage by collating with the list of contractors who have received the accident after a certain period of time has passed since the flood disaster occurred. It is a business attribute to be. "(4) Calculation / payment of damage amount" is a business attribute for the purpose of determining the internal payment of insurance money to a policyholder who has a high possibility of damage.

Here, in each business attribute, two contradictory indexes, "recall rate" and "compliance rate", can be considered. The "recall rate" is an index showing how much of the contractors who actually suffered a flood disaster were detected as correct answers in the final determination result by the information processing system 1. The "recall rate" can be calculated as, for example, the ratio of the number of contractors whose determination result is "reference depth or more" to the number of contractors who have paid. In addition, the "compliance rate" is the reliability of the result of determining that the inundation depth is equal to or greater than the reference depth as the final determination result by the information processing system 1, that is, how much of the result of determining that there is a flood disaster. It is an index showing whether or not the contractors who actually suffered a flood disaster are included. The "compliance rate" can be calculated, for example, as the ratio of the number of contractors who have paid to the number of contractors whose determination result is "more than the standard depth".

In "(1) Flood disaster information collection / identification of disaster area", it is important to grasp the outline of where the damage is concentrated in the vast area, so the recall rate is more important. In "(2) Damage investigation", it is important to grasp the damage situation with high accuracy for a specific contractor, so the precision rate is more important. In "(3) Billing recommendation", it is important to grasp as many contractors as possible who may have been damaged in a specific area where damage is concentrated, so the recall rate is more important. The contract. In "(4) Calculation and payment of damage amount", it is important to grasp the damage situation with high accuracy for each contractor in a specific area where damage is concentrated, so the precision rate is higher. It is emphasized.

Then, in the determination model table, a predetermined determination model is associated with the business attribute according to whether the business attribute emphasizes "reproducibility" or "adaptation rate". Here, the determination model is final based on the content of the provisional determination result obtained from each satellite image analysis system 30 as to whether or not the inundation depth is equal to or greater than the reference depth for each policyholder. This is a judgment model for determining the judgment result. The final judgment result is, for example, "above the standard depth" indicating that the inundation depth is likely to be covered by insurance claims, or an investigator or the like needs to conduct a field survey of the inundation depth. It is "less than the reference depth" indicating that there is. Each determination model determines the final determination result as, for example, when the ratio of "reference depth or more" among the plurality of provisional determination results acquired from each satellite image analysis system 30 is equal to or greater than a predetermined threshold value. When "more than the reference depth" and the ratio of "more than the reference depth" among the plurality of provisional judgment results is less than a predetermined threshold value, the final judgment result may be "less than the reference depth".

In the example shown in FIG. 3, the predetermined threshold values of the determination models A, B, C, D, E, and F are one-fourth, one-third, one-half, two-thirds, and four, respectively. Three-quarters and four-quarters. Then, in the example shown in FIG. 3, "(1) Flood disaster information collection / identification of disaster area", in which the recall rate is more important, is associated with the judgment model A, and "(2)" in which the precision rate is more important. "Damage investigation" is associated with the judgment model E and the recall rate is more important. "(3) Claim recommendation" is associated with the judgment model B and the conformity rate is more important. "(4) Damage amount" "Calculation / payment" is associated with the determination model F.

FIG. 4 is a diagram showing a specific example of the determination result by the information processing system 1. FIG. 4 shows the final judgment results by each judgment model for the specific contractors C001 to C006. Each of the contractors C001 to C006 acquires the provisional judgment results obtained by analyzing the visible light satellite images on the first and second days after the occurrence of the flood disaster from the visible light satellite image analysis system 30A. , This is a case where the tentative determination result obtained by analyzing the SAR satellite images on the first day and the second day from the occurrence of the flood disaster is obtained from the SAR satellite image analysis system 30B. Each provisional judgment result is "more than the reference depth" indicating that the inundation depth is equal to or more than the reference depth, or "greater than or equal to the reference depth" indicating that the inundation depth is less than the reference depth. .. As described above, among a plurality of provisional judgment results, "greater than or equal to the reference depth" is the criterion for determining whether the final judgment result is "above the reference depth" or "less than the reference depth". The threshold value for the proportion is different for each judgment model. Therefore, as shown in FIG. 4, the final judgment result of each case is different for each judgment model.

Returning to FIG. 1, the processing unit 13 includes one or more processors and peripheral circuits thereof. The processing unit 13 comprehensively controls the overall operation of the server device 10, and is, for example, a CPU (Central Processing Unit). The processing unit 13 controls the operation of the communication unit 11 and the like so that various processes of the server device 10 are executed in an appropriate procedure based on the program and the like stored in the storage unit 12. The processing unit 13 executes processing based on a program (operating system program, driver program, application program, etc.) stored in the storage unit 12.

The processing unit 13 is, for example, a business attribute acquisition unit 131, a determination model determination unit 132, a provisional determination result acquisition unit 133, a determination result generation unit 134, a display data generation unit 135, a transmission / reception unit 136, an SNS information acquisition unit 137, and an SNS. It has an information analysis unit 138 and the like. Each of these units included in the processing unit 13 is a functional module implemented by a program executed on the processor included in the processing unit 13. Alternatively, each of these units included in the processing unit 13 may be mounted on the server device 10 as an independent integrated circuit, microprocessor, or firmware.

The business attribute acquisition unit 131 acquires business attributes from, for example, the client terminal 20 or the like. The determination model determination unit 132 determines, for example, the determination model associated with the acquired business attribute by referring to the determination model table. The provisional determination result acquisition unit 133, for example, obtains a provisional determination result (based on the depth of inundation for each policyholder) obtained by analyzing a plurality of satellite images having different observation frequencies from each of the plurality of satellite image analysis systems 30. (Judgment result of determining whether or not the depth is greater than or equal to the depth) is acquired.

The determination result generation unit 134 applies, for example, a plurality of provisional determination results acquired by the provisional determination result acquisition unit 133 to the determination model determined by the determination model determination unit 132, thereby reducing the inundation depth of the contractor. Generates a judgment result indicating whether the depth is equal to or greater than the reference depth. Further, the determination result generation unit 134 extracts inundation information from the damage information described later generated by the SNS information analysis unit 138, and corrects the determination result obtained by the above-mentioned determination model based on the inundation information. You may. Here, the inundation information may include a place included in the disaster information and information indicating the inundation depth at the place, and for example, a "reference depth" indicating that the inundation depth is equal to or more than the reference depth. It may be expressed as "greater than or equal to" or "greater than or equal to the reference depth" indicating that the depth of inundation is less than the reference depth. For example, when the determination result obtained by the determination model and the inundation information are different from each other in a predetermined place, the determination result generation unit 134 may modify the determination result according to a predetermined standard, or the determination result is based on the inundation information. It may be modified (updated). For example, the determination result generation unit 134 sets the determination result as "reference" when the determination result obtained by the determination model is "less than the reference depth" and the inundation information is "greater than or equal to the reference depth" at a predetermined location. It may be corrected (updated) to "more than the depth".

The display data generation unit 135 generates, for example, various display data for display on the client terminal 20 or the like. The display data generation unit 135 displays, for example, an image (mapping image) in which the generated determination result is mapped on the map based on the information such as the accident reception status and the insurance claim payment status included in the contractor data table. Generate display data for. The transmission / reception unit 136 functions as, for example, an output unit, and transmits / receives various data and signals to / from the client terminal 20 and the satellite image analysis system 30.

The SNS information acquisition unit 137 acquires, for example, a plurality of text information input by the user in the SNS from the SNS information DB 40. The SNS information acquisition unit 137 is not limited to the SNS information DB 40, and may acquire the text information directly from, for example, an information processing terminal (PC, smartphone, etc.) in which the user inputs the text information. The timing at which the SNS information acquisition unit 137 acquires text information is not particularly limited, but may be, for example, a periodic timing (for example, every hour, every day, every week, etc.), or the server device 10 is a client terminal. It may be when a request for acquiring text information is received from 20 or the like.

The SNS information analysis unit 138 generates disaster information by analyzing a plurality of text information acquired by the SNS information acquisition unit 137 by natural language processing, for example. Here, the disaster information includes information indicating an arbitrary place and information indicating the damage situation at the place. The format of the information indicating the place is not particularly limited, but may be, for example, an address, an administrative division name, an area name, a building name, a common name / abbreviation of the place, or the like, in addition to the latitude and longitude. The information indicating the disaster situation may be arbitrarily set by the manager or the like, and may include, for example, information indicating the type of disaster, the damage situation of land or buildings, the depth of inundation, and the like. The information indicating the inundation depth is a quantitative value (for example, "○ centimeter") and a qualitative expression comparing the inundation depth with an arbitrary standard (for example, "underfloor inundation"). , "Flood on the floor", "Reach the second floor"), etc. The natural language processing method used by the SNS information analysis unit 138 for analyzing text information is not particularly limited. The SNS information analysis unit 138 may, for example, extract terms related to a place or a disaster situation from individual text information by natural language processing, and aggregate the extracted terms related to the place or the disaster situation. The SNS information analysis unit 138 may include, for example, the aggregated location and the disaster status in the disaster information when the total number of locations and the disaster status is equal to or more than a predetermined number.

(1-3) Client terminal 20
The client terminal 20 is, for example, an information processing device used by a non-life insurance investigator or the like related to flood disasters. The client terminal 20 has, for example, a communication unit 21, a storage unit 22, an operation unit 23, a display unit 24, and a processing unit 25.

The communication unit 21 has a communication interface circuit for connecting the client terminal 20 to the server device 10, the satellite image analysis system 30, and the like. The communication unit 21 supplies the data received from the server device 10 and the satellite image analysis system 30 and the like to the processing unit 25. Further, the communication unit 21 transmits the data supplied from the processing unit 25 to the server device 10, the satellite image analysis system 30, and the like.

The storage unit 22 has, for example, at least one of a semiconductor memory, a magnetic disk device, and an optical disk device. The storage unit 22 stores a driver program, an operating system program, an application program, data, and the like used for processing by the processing unit 25. For example, the storage unit 22 stores a communication device driver program or the like that controls the communication unit 21 as a driver program. The various programs may be installed in the storage unit 22 from a computer-readable portable recording medium such as a CD-ROM or a DVD-ROM using a known setup program or the like.

The operation unit 23 may be any device as long as the client terminal 20 can be operated, such as a touch panel or key buttons. The user can input characters, numbers, symbols, etc. using the operation unit 23. When the operation unit 23 is operated by the user, the operation unit 23 generates a signal corresponding to the operation. Then, the generated signal is supplied to the processing unit 25 as a user's instruction.

The display unit 24 may be any device as long as it can display an image, an image, or the like, and is, for example, a liquid crystal display, an organic EL (Electro-Luminescence) display, or the like. The display unit 24 displays an image corresponding to the image data supplied from the processing unit 25, an image corresponding to the image data, and the like.

The processing unit 25 includes one or more processors and peripheral circuits thereof. The processing unit 25 controls the overall operation of the client terminal 20 in an integrated manner, and is, for example, a CPU (Central Processing Unit). The processing unit 25 controls the operation of the communication unit 21 and the like so that various processes of the client terminal 20 are executed in an appropriate procedure based on the program and the like stored in the storage unit 22. The processing unit 25 executes processing based on a program (operating system program, driver program, application program, etc.) stored in the storage unit 22.

The processing unit 25 includes a transmission / reception unit 251 and a display control unit 252 and the like. Each of these units included in the processing unit 25 is a functional module implemented by a program executed on the processor included in the processing unit 25. Alternatively, each of these units included in the processing unit 25 may be mounted on the server device 10 as an independent integrated circuit, microprocessor, or firmware. The transmission / reception unit 251 transmits / receives various data and signals to / from the server device 10 and the satellite image analysis system 30, for example. The display control unit 252 causes the display unit 34 to display, for example, a screen or the like based on the display data received from the server device 10 or the like.

(2) Operation processing With reference to FIG. 5, the operation processing of the information processing system 1 according to the present embodiment will be described. FIG. 5 is a diagram showing an example of an operation sequence of the information processing system 1.

(S101) First, when the user inputs a business attribute via the operation unit 23, the transmission / reception unit 251 of the client terminal 20 transmits the business attribute to the server device 10. As a result, the business attribute acquisition unit 231 of the server device 10 acquires the business attribute from the client terminal 20. Business attributes include, for example, "(1) Flood disaster information collection / identification of disaster area", "(2) Damage investigation", "(3) Claim recommendation", and "(4) Damage amount calculation / payment", etc. It may be.

(S102) Next, the determination model determination unit 132 of the server device 10 refers to the determination model table stored in the storage unit 12 to determine the determination model corresponding to the business attribute acquired from the client terminal 20.

(S103) Next, the provisional determination result acquisition unit 133 of the server device 10 acquires the provisional determination result generated by analyzing the visible light satellite image from the visible light satellite image analysis system 30A. Further, the provisional determination result acquisition unit 133 acquires the provisional determination result generated by analyzing the SAR satellite image from the SAR satellite image analysis system 30B.

(S104) Next, the determination result generation unit 134 of the server device 10 determines in S102 the provisional determination result acquired from the visible light satellite image analysis system 30A and the provisional determination result acquired from the SAR satellite image analysis system 30B. It is applied to the judgment model to generate the judgment result.

(S105) Next, the SNS information acquisition unit 137 of the server device 10 acquires a plurality of text information input by the user from the SNS information DB 40. The timing at which the SNS information acquisition unit 137 acquires the text information is not particularly limited, but may be, for example, a periodic timing (for example, every hour, every day, every week, etc.), or the server device 10 may acquire the text information. It may be when a request for acquiring text information is received from the client terminal 20 or the like.

(S106) Next, the SNS information analysis unit 138 of the server device 10 analyzes the text information acquired by the SNS information acquisition unit 137 by a predetermined natural language processing, thereby indicating information indicating an arbitrary location and damage at the location. Generate disaster information, including information indicating the situation.

(S107) Next, the determination result generation unit 134 of the server device 10 extracts inundation information from the damage information, and corrects the determination result generated in step S104 based on the inundation information. For example, when the determination result generation unit 134 determines that the predetermined location is "less than the reference depth" in the determination result generated in step S104 and "greater than or equal to the reference depth" in the inundation information, the determination result generation unit 134 refers to the location. The determination result may be modified to "greater than or equal to the reference depth". The step S107 does not have to be executed.

(S108) Next, the display data generation unit 135 of the server device 10 maps the generated determination result on the map based on the information such as the accident reception status and the insurance claim payment status included in the contractor data table. Generate display data for displaying an image (mapping image) on the display unit. The details of the mapping image will be described later.

(S109) Next, the transmission / reception unit 136 transmits the generated mapping image display data to the client terminal 20. The transmission / reception unit 136 may transmit only the determination result generated in S105 to the client terminal 20. Further, the transmission / reception unit 136 may transmit the damage information generated by the SNS information analysis unit 138 to the client terminal 20.

(S1010) When the display control unit 252 of the client terminal 20 receives the display data of the mapping image from the server device 10, the display unit 24 displays the mapping image based on the display data. Further, the display control unit 252 of the client terminal 20 may display the damage information received from the server device 10 on the display unit 24.

FIG. 6 is a diagram showing an example of a mapping image. As shown in FIG. 6, in the mapping image, a predetermined object is arranged at a position corresponding to the address of the contractor on the map. The object indicates, for example, a determination result regarding the inundation depth of the contractor, an accident reception status, and the like. The display mode of the object is not particularly limited, but in the example shown in FIG. 6, for example, in the example shown in FIG. The reception status is "Yes", the square indicates the judgment result "less than the standard depth", the accident reception status is "None", and the triangle indicates the judgment result "less than the standard depth" and the accident reception status "Yes".

In addition, the mapping image may include disaster information. In FIG. 6, as an example of the disaster information, the disaster information regarding "A town" and "B evacuation site" is shown. As shown in FIG. 6, the damage information of "A town" includes "rescue> isolation" as the damage situation, and the damage information of "B evacuation center" includes "trouble> deficiency / shortage" as the damage situation. These disaster situations may be classified in advance arbitrarily set by the administrator or the like. In addition, as shown in Fig. 6, the damage information of "A town" includes the text "Isolated due to a landslide. Injured people cannot be transported." Includes the text "No food provided. The toilet is too crowded to use." These texts may be, for example, texts generated by the SNS information analysis unit 138.

The embodiments described above are for facilitating the understanding of the present invention, and are not for limiting and interpreting the present invention. Each element included in the embodiment and its arrangement, material, condition, shape, size, and the like are not limited to those exemplified, and can be changed as appropriate. In addition, the configurations shown in different embodiments can be partially replaced or combined.

1 ... Information processing system, 10 ... Server device, 11 ... Communication unit, 12 ... Storage unit, 13 ... Processing unit, 131 ... Business attribute acquisition unit, 132 ... Judgment model determination unit 133 ... Temporary judgment result acquisition unit, 134 ... Judgment result generation unit, 135 ... Display data generation unit, 136 ... Transmission / reception unit, 20 ... Client terminal, 21 ... Communication unit, 22 ... Storage unit, 23 ... Operation unit, 24 ... Display unit, 25 ... Processing unit, 251 ... Transmission / reception Unit, 252 ... Display control unit, 30 ... Satellite image analysis system, 30A ... Visible light satellite image analysis system, 30B ... SAR satellite image analysis system

Claims (9)

A business attribute acquisition unit that acquires business attributes, which are information indicating the purpose of business, from other information processing devices.
A judgment model determination unit that determines a determination model associated with the business attribute acquired by the business attribute acquisition unit, and a determination model determination unit.
Obtained multiple tentative judgment results indicating whether or not the inundation depth for non-life insurance policyholders related to flood disasters is greater than or equal to the standard depth, which is obtained by analyzing each of multiple satellite images with different observation frequencies. Temporary judgment result acquisition unit and
By applying the plurality of provisional determination results to the determination model determined by the determination model determination unit, a determination to generate a determination result indicating whether the inundation depth for the contractor is equal to or greater than the reference depth. Result generator and
An information processing device including an output unit that outputs the determination result generated by the determination result generation unit to another information processing device. The information processing according to claim 1, wherein the plurality of satellite images include at least one visible light satellite image generated by visible light and at least one SAR satellite image generated by a synthetic aperture radar (SAR). apparatus. The information processing apparatus according to claim 2, wherein the plurality of satellite images include the visible light satellite image and the SAR satellite image, which are respectively captured at a plurality of timings from the occurrence of a flood disaster. The output unit according to any one of claims 1 to 3, wherein the output unit outputs display data for displaying an image in which the determination result generated by the determination result generation unit is mapped on a map on the display unit. Information processing device. The information processing apparatus according to claim 4, wherein the image includes an object of an aspect based on the determination result in a portion corresponding to the address of the contractor on the map. The information processing device according to claim 5, wherein the object is further based on at least one of an accident reception status and an insurance claim payment status. An SNS information acquisition unit that acquires a plurality of text information input by a user on a predetermined social networking site (SNS), and an SNS information acquisition unit.
SNS information analysis that generates disaster information including information indicating an arbitrary place and information indicating a damage situation at the place by analyzing the plurality of text information acquired by the SNS information acquisition unit by natural language processing. With more parts,
The information processing device according to any one of claims 1 to 6, wherein the output unit further outputs the damage information to the other information processing device. The information processing device according to claim 7, wherein the determination result generation unit extracts inundation information from the damage information and corrects the determination result based on the inundation information. Computer,
A business attribute acquisition unit that acquires business attributes, which are information indicating the purpose of business, from other information processing devices.
A judgment model determination unit that determines a determination model associated with the business attribute acquired by the business attribute acquisition unit, and a determination model determination unit.
Obtained multiple tentative judgment results indicating whether or not the inundation depth for non-life insurance policyholders related to flood disasters is greater than or equal to the standard depth, which is obtained by analyzing each of multiple satellite images with different observation frequencies. Temporary judgment result acquisition unit and
By applying the plurality of temporary determination result to the determination the determination model model determination unit has determined, the depth of immersion of the contractor to generate a determination result indicating whether it is greater than or equal to the reference depth Judgment result generator and
A program for functioning as an output unit that outputs the determination result generated by the determination result generation unit to another information processing device.

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