System

Abstract

To provide a system for allowing even general users without specialized knowledge to quickly and accurately calculate compensation for damage.SOLUTION: A system includes means for: acquiring data obtained from vehicle sensors and cameras to receive information of a location, time, vehicle speed and impact force of a traffic accident, and analyzing the data to generate detailed information relating to the traffic accident; generating a prompt sentence for instructing calculation of compensation for damage based on the generated detailed information of the traffic accident and insurance contract information; calculating the compensation for the traffic accident using the generated prompt sentence, the traffic accident compensation standard, and the generative AI model; and notifying a user of the calculated compensation for damage.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including a description and related instruction sentence regarding the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Determining the amount of compensation in traffic accidents requires specialized knowledge and is difficult for ordinary people to understand. In addition, the results vary greatly depending on the circumstances of each accident, making it difficult to ensure consistency. [Means for solving the problem]

[0005] The present invention provides a system that uses AI to perform a simplified judgment of the standard of compensation for traffic accidents. This system reads information about traffic accidents and calculates the amount of compensation based on the read information. In particular, by reading the "Red Book" and "Standards for Calculating Compensation for Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Compensation for Traffic Accidents," it is possible to make a judgment based on specialized knowledge. In addition, by targeting subscribers of voluntary automobile insurance, it can be used widely. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15]FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] One embodiment of the present invention is a simplified system for determining standards for compensation for traffic accident damages using AI. This system is equipped with a means for reading information about traffic accidents and a means for calculating the amount of compensation for damages based on the read information. Specifically, the system receives detailed information about the traffic accident (such as the location and time of the accident, and the circumstances of the parties involved) as input, and the AI ​​analyzes this information. The system then calculates the amount of compensation for damages based on the "Red Book" "Standards for Calculating Compensation for Civil Traffic Accident Lawsuits" and the "Blue Book" "Standards for Calculating Compensation for Traffic Accident Damages," and outputs the results.

[0029] "Example 2"

[0030] Another embodiment of the present invention is a system targeted at voluntary automobile insurance subscribers. In this system, the subscriber inputs his / her insurance contract information and detailed information about the traffic accident, and AI analyzes this information and calculates the amount of damages. Specifically, the subscriber inputs his / her insurance contract information (type of insurance, insurance premium, etc.) and detailed information about the traffic accident (location of the accident, time, status of the parties involved, etc.), and AI analyzes this information. Then, the AI ​​calculates the amount of damages based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards," and outputs the results.

[0031] The process flow of each embodiment will be described below.

[0032] "Example 1"

[0033] Step 1: The user enters detailed information about the traffic accident (location, time of the accident, circumstances of the parties involved, etc.) into the system.

[0034] Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[0035] Step 3: The calculated amount of damages is output to the user.

[0036] "Example 2"

[0037] Step 1: A voluntary automobile insurance policyholder enters their insurance contract information (type of insurance, premium, etc.) and detailed information about the traffic accident (location of the accident, time, circumstances of the parties involved, etc.) into the system. Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[0038] Step 3: The calculated amount of damages is output to the subscriber.

[0039] Example 1

[0040] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0041] Calculating compensation for traffic accidents requires specialized knowledge and is time-consuming and laborious. In addition, the calculation standards for compensation are complex, making it difficult for general users to easily understand and apply. For this reason, a system that can calculate compensation quickly and accurately is required.

[0042] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0043] In this invention, the server includes a means for inputting detailed information about a traffic accident, a means for transmitting the input information to the server, a means for the server to analyze the information received, a means for the server to calculate the amount of compensation using the generative AI model, a means for transmitting the calculation result to the terminal, and a means for the terminal to display the calculation result to the user. This allows the user to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation.

[0044] "Detailed information about the traffic accident" is specific information related to the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[0045] "Input means" refers to an interface or device that allows a user to input detailed information about a traffic accident.

[0046] A "server" is a computer system that receives information sent by users, analyzes it, and calculates the amount of damages.

[0047] The "transmitting means" refers to a communication means for transmitting information from the terminal to the server.

[0048] "Means of analysis" refers to software or algorithms used by the server to process the information it receives and check its consistency.

[0049] A "generative AI model" is an artificial intelligence model trained to calculate compensation amounts for traffic accidents.

[0050] A “means for calculating” is a process or algorithm for calculating damages using a generative AI model.

[0051] A "terminal" is a device through which a user inputs information and checks the results of calculations.

[0052] The "display means" refers to an interface for visually presenting to the user the calculation results that the terminal receives from the server.

[0053] The present invention is a system for quickly and accurately calculating the amount of compensation for damages in a traffic accident. A specific embodiment of this system will be described below.

[0054] First, the user uses the terminal to input detailed information about a traffic accident. The input form includes items such as the location of the accident, the time of the accident, the circumstances of the people involved, etc. For example, the user inputs information according to the following prompts:

[0055] "Where did the accident occur?"

[0056] "What time did the accident occur?"

[0057] Please tell us the situation of the parties involved.

[0058] The information entered by the user is sent from the terminal to the server, which then sends the information to the server in an appropriate format (e.g., JSON format).

[0059] The server analyzes the information it receives, which may include checking the integrity of the information and pre-processing it, such as making sure the time of occurrence is not in the future and that the location is a valid place name.

[0060] The server then uses a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information and calculates the amount of compensation based on past traffic accident data and standards.

[0061] The calculation result is sent from the server to the terminal. The terminal displays the received calculation result to the user. The user can check the amount of compensation displayed on the terminal screen. For example, a result such as "The amount of compensation is 5 million yen" may be displayed.

[0062] This system allows users to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation. The hardware used includes the user's terminal (PC, smartphone, etc.) and the server. The software includes the input form, communication protocol, analysis algorithm, and generative AI model.

[0063] As a concrete example, if the user enters the following information:

[0064] Location of accident: Shinjuku Ward, Tokyo

[0065] Time of accident: October 1, 2023, 14:30

[0066] Situation of the parties involved: Vehicle A runs a red light and crashes into vehicle B.

[0067] The server receives this information and performs analysis using the generative AI model. As a result of the analysis, the amount of compensation is calculated and a result such as "The amount of compensation is 5 million yen" is displayed on the terminal.

[0068] In this way, users can easily check the amount of compensation by simply entering detailed information about a traffic accident.

[0069] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0070] Step 1:

[0071] The user enters detailed information about the traffic accident.

[0072] The user inputs information such as the location and time of the accident, and the status of the people involved into the input form on the terminal. For example, the user inputs information following prompts such as "Where did the accident occur?", "What time did the accident occur?", and "Please tell us the status of the people involved." The input information is temporarily stored in the terminal's memory.

[0073] Step 2:

[0074] The terminal transmits the input information to the server.

[0075] The terminal sends the information entered by the user to the server in an appropriate format (for example, JSON format). The data sent includes the location of the accident, the time of the accident, the status of the people involved, etc. For example, the following JSON data is sent:

[0076] json

[0077] {

[0078] "location": "Shinjuku-ku, Tokyo",

[0079] "time": "2023-10-01T14:30:00",

[0080] "details": "Vehicle A runs a red light and collides with vehicle B"

[0081] }

[0082] Step 3:

[0083] The server analyzes the information it receives.

[0084] The server receives the JSON data sent from the terminal and begins analyzing it. The analysis includes checking the consistency of the information and preprocessing. For example, it checks whether the time of occurrence is a future date, whether the location is a valid place name, etc. As a result of the analysis, data with confirmed consistency is generated.

[0085] Step 4:

[0086] The server uses the generative AI model to calculate damages.

[0087] The server inputs the analyzed information into a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information based on past traffic accident data and standards, and calculates the amount of compensation. The amount of compensation is generated as a calculation result.

[0088] Step 5:

[0089] The server transmits the calculation result to the terminal.

[0090] The server sends the calculated amount of damages to the terminal in an appropriate format (for example, JSON format). The data sent includes details of the amount of damages. For example, the following JSON data is sent:

[0091] json

[0092] {

[0093] "compensation_amount": 5000000,

[0094] "details": "The damages amount to 5 million yen."

[0095] }

[0096] Step 6:

[0097] The terminal displays the calculation results to the user.

[0098] The terminal displays the calculation results received from the server to the user. The user can check the amount of damages displayed on the terminal screen. For example, the result "The amount of damages is 5 million yen" may be displayed.

[0099] (Application example 1)

[0100] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0101] When a traffic accident occurs, it is important for both the victim and the at-fault party to calculate the amount of compensation quickly and accurately. However, the conventional method requires manually collecting detailed information about the accident and having experts analyze it before calculating the amount of compensation, which is time-consuming and labor-intensive. In addition, as autonomous vehicles become more widespread, there is a demand for a system that can respond immediately when an accident occurs.

[0102] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting accident information from the sensor or camera of the autonomous vehicle, a means for analyzing the collected information and calculating the amount of compensation, a means for calculating the amount of compensation using a generative AI model, and a means for generating a prompt sentence and inputting it into the AI ​​model. This makes it possible to quickly and accurately calculate the amount of compensation when a traffic accident occurs.

[0103] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0104] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[0105] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[0106] "Information regarding traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[0107] "Amount of damages" refers to the amount of money paid to a victim for damages suffered in a traffic accident.

[0108] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[0109] A "sensor" is a device that detects physical phenomena and outputs them as data.

[0110] A "camera" is a device that captures images or videos.

[0111] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[0112] A "prompt" is an instruction to be input to a generative AI model, which serves as a guideline for the model to generate appropriate output.

[0113] The system for carrying out the present invention is for quickly and accurately calculating the amount of compensation for damages when a traffic accident occurs. A specific embodiment of this system will be described below.

[0114] The system includes a means of collecting accident information from sensors and cameras installed in the autonomous vehicle, which allows detailed data such as the location and time of the accident, as well as the circumstances of the people involved, to be collected in real time. The collected data is then sent to a computer in the vehicle where it undergoes initial processing.

[0115] Then, the initially processed data is sent to a server. The server uses a generative AI model to analyze the collected accident information. Specifically, the server includes the following means:

[0116] 1. A means of reading information about traffic accidents: Read data collected from sensors and cameras to obtain detailed information about accidents.

[0117] 2. Method of calculating damages: Based on the information read in, the generative AI model calculates the amount of damages. The calculation is based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards."

[0118] 3. A means for generating prompt sentences and inputting them into the AI ​​model: A prompt sentence is generated based on the accident information and input into the generative AI model.

[0119] For example, the following prompt would be generated:

[0120] A traffic accident has occurred. Details of the accident are as follows:

[0121] Location: Tokyo, Japan

[0122] Occurrence time: 2023-10-01T12:34:56

[0123] Status of the parties: Driver A (Injured), Driver B (Uninjured)

[0124] Vehicle Damage: Severe

[0125] Use this information to assess your damages.

[0126] The server inputs this prompt into a generative AI model to calculate the amount of damages, and the calculation result is notified to the user via an in-vehicle display or a smartphone application.

[0127] This system will enable the prompt and accurate calculation of compensation when a traffic accident occurs, enabling a prompt response for both the victim and the at-fault party. In addition, as autonomous vehicles become more widespread, the response to accidents will be automated, further improving safety and efficiency.

[0128] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0129] Step 1:

[0130] Sensors and cameras in autonomous vehicles detect the occurrence of a traffic accident. The sensors collect impact and location information, and the cameras capture video of the accident scene. These data are sent to a computer in the vehicle. The input is data from the sensors and cameras, and the output is initially processed accident information.

[0131] Step 2:

[0132] An in-vehicle computer performs initial processing of the collected data, analyzing impact data and location information from sensors and extracting accident details from camera footage. The input is raw data from sensors and cameras, and the output is analyzed accident details.

[0133] Step 3:

[0134] The initial processed accident information is sent to the server. The server receives this information and stores it in a database. The input is the accident details sent from the computer in the vehicle, and the output is the accident information stored in the database.

[0135] Step 4:

[0136] The server generates a prompt sentence based on the stored accident information. Specifically, it converts information such as the location and time of the accident, and the situation of the people involved into text format. The input is the accident information stored in the database, and the output is the generated prompt sentence.

[0137] Step 5:

[0138] The server inputs the generated prompt sentence into the generative AI model. The generative AI model analyzes the prompt sentence and calculates the amount of damages. The input is the generated prompt sentence, and the output is the calculated amount of damages.

[0139] Step 6:

[0140] The server notifies the user of the calculated amount of compensation through the display in the vehicle or a smartphone application. The input is the calculated amount of compensation, and the output is the amount of compensation notified to the user.

[0141] Step 7:

[0142] The user checks the notified amount of damages and contacts the insurance company or relevant organizations if necessary. The input is the notified amount of damages, and the output is the user's confirmation and contact.

[0143] Example 2

[0144] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0145] Conventional calculations of compensation for traffic accidents require manual work by people with specialized knowledge, which is time-consuming and labor-intensive. In addition, the calculation standards for compensation can be complex, making accurate calculations difficult. Furthermore, there was a lack of a way for users to easily input their own insurance contract information and detailed information about the accident and quickly find out the amount of compensation.

[0146] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0147] In this invention, the server includes a means for a user to input insurance contract information and detailed information about a traffic accident, a means for the server to receive the input information and perform preprocessing, a means for the server to input the preprocessed information into a generative AI model and perform analysis, a means for the server to calculate the amount of damages based on the analysis result, a means for the server to output the calculation result to the user's terminal, and a means for the user to check the result on the terminal. This allows the user to easily input information and quickly and accurately know the amount of damages.

[0148] A "user" is an individual or legal entity that utilizes the system to input insurance policy information and detailed information about a traffic accident.

[0149] "Insurance contract information" is detailed information about insurance, such as the type of insurance the user has subscribed to and the insurance premiums.

[0150] "Detailed information about the traffic accident" is specific information about the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[0151] A “server” is a computer system that receives information input by a user, performs preprocessing, and analyzes it using a generative AI model.

[0152] "Preprocessing" refers to processing the data received to format it and make it suitable for analysis.

[0153] A "generative AI model" is an artificial intelligence model built using a machine learning framework to analyze input information and calculate the amount of damages.

[0154] "Analysis" is the process in which the generative AI model performs calculations and inferences based on the input information to determine the amount of damages.

[0155] "Amount of damages" means the amount to be paid for damages in a traffic accident.

[0156] A "terminal" is a device that a user uses to enter information and view results from a server.

[0157] The “results” are information on the amount of damages calculated by the generative AI model.

[0158] This invention is a system in which a user inputs insurance contract information and detailed information about a traffic accident, and a server analyzes this information to calculate the amount of compensation. A specific embodiment of this system will be described below.

[0159] Hardware and Software Used

[0160] Hardware

[0161] Server: A high-performance computer system that receives data, pre-processes it, analyzes it, and outputs the results.

[0162] Terminal: A device where a user enters information and checks the results. This includes computers, smartphones, tablets, etc.

[0163] software

[0164] Generative AI Model: An artificial intelligence model built using a machine learning framework such as TENSORFLOW® or PyTorch.

[0165] Database Management System: A system for storing and managing information received from users, such as MySQL (registered trademark) or PostgreSQL.

[0166] Web Application: Provides an interface for users to enter information. Uses web technologies such as HTML, CSS, and JavaScript.

[0167] Program Processing

[0168] User input of information

[0169] The user uses the terminal to input the insurance policy information and the details of the traffic accident. Specifically, the user inputs the following information:

[0170] Insurance contract information (e.g. type of insurance, premium)

[0171] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[0172] Receiving and preprocessing information by the server

[0173] The server receives the information sent by the user. The received information is stored in a database and pre-processed to format the data as necessary. For example, this includes standardizing the format of dates and times.

[0174] Input to the AI ​​model and analysis by the server

[0175] The server feeds the preprocessed information into a generative AI model, which generates a prompt like this:

[0176] Policy Information:

[0177] Insurance type: Comprehensive insurance

[0178] Insurance premium: 100,000 yen per year

[0179] Traffic accident details:

[0180] Location of accident: Shibuya Ward, Tokyo

[0181] Time of accident: October 1, 2023, 3:00 p.m.

[0182] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[0183] This prompt sentence is input into the AI ​​model and analysis begins.

[0184] Calculation of damages by the server

[0185] The generative AI model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[0186] Server output of results

[0187] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[0188] User review of results

[0189] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[0190] Examples

[0191] As a concrete example, consider the following scenario:

[0192] User A has automobile insurance, the type of insurance is "comprehensive insurance" and the premium is "100,000 yen per year."

[0193] User A is involved in a traffic accident. The location of the accident is "Shibuya Ward, Tokyo," the time of the accident is "October 1, 2023, 3:00 p.m.", and the circumstances of the parties involved are "The car driven by User A was hit by a car that ran a red light."

[0194] Based on this information, User A inputs the following prompt into the generative AI model:

[0195] Policy Information:

[0196] Insurance type: Comprehensive insurance

[0197] Insurance premium: 100,000 yen per year

[0198] Traffic accident details:

[0199] Location of accident: Shibuya Ward, Tokyo

[0200] Time of accident: October 1, 2023, 3:00 p.m.

[0201] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[0202] The server receives this prompt, calculates the amount of compensation using the generative AI model, and outputs the result to the terminal of User A. For example, if the calculation result is "The amount of compensation is 500,000 yen," User A can check the result.

[0203] The above is a specific embodiment for carrying out the present invention.

[0204] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0205] Step 1:

[0206] The user uses the device to enter the insurance policy information and the details of the traffic accident, using a dedicated web form or a mobile app to enter the following information:

[0207] Insurance contract information (e.g. type of insurance, premium)

[0208] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[0209] The entered information is transmitted from the terminal to the server.

[0210] Step 2:

[0211] The server receives the information sent by the user. The received information is stored in a database. After storage, pre-processing is performed to format the data. For example, this includes standardizing the format of the date and time.

[0212] Input: Insurance policy information and traffic accident details submitted by the user

[0213] Output: Preprocessed information

[0214] Step 3:

[0215] The server inputs the preprocessed information into a generative AI model, which generates a prompt sentence like this:

[0216] Policy Information:

[0217] Insurance type: Comprehensive insurance

[0218] Insurance premium: 100,000 yen per year

[0219] Traffic accident details:

[0220] Location of accident: Shibuya Ward, Tokyo

[0221] Time of accident: October 1, 2023, 3:00 p.m.

[0222] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[0223] This prompt sentence is input into the AI ​​model and analysis begins.

[0224] Input: Preprocessed information

[0225] Output: Prompt statement

[0226] Step 4:

[0227] The server analyzes the prompt sentence using a generative AI model. The AI ​​model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[0228] Input: Prompt statement

[0229] Output: Damages amount

[0230] Step 5:

[0231] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[0232] Input: Damages amount

[0233] Output: Damage amount result (text message and PDF file)

[0234] Step 6:

[0235] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[0236] Input: Damages amount result

[0237] Output: User review of results

[0238] (Application example 2)

[0239] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0240] Conventional calculations of compensation for traffic accidents are often done manually, which takes time and effort and can be inaccurate. As autonomous vehicles become more widespread, there is a demand for a system that can calculate compensation in real time when an accident occurs. This will enable quick and accurate calculation of compensation, reducing the burden on insureds and related parties.

[0241] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0242] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting detailed information about the accident from a sensor and a camera mounted on the autonomous vehicle, a means for analyzing the collected information in real time, a means for calculating the amount of compensation based on the analysis result, and a means for outputting the calculation result. This makes it possible to calculate the amount of compensation quickly and accurately when an accident occurs.

[0243] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0244] The "Traffic Accident Compensation Standards" are the standards for calculating the amount of compensation in traffic accidents, and are set out in the "Red Book" and "Blue Book."

[0245] "Simplified determination" is a method of obtaining results quickly by simplifying complex calculations and procedures.

[0246] "Information regarding traffic accidents" refers to detailed data related to the accident, such as the location and time of the accident, and the circumstances of the parties involved.

[0247] "Amount of damages" refers to the amount of money paid for damages caused by a traffic accident.

[0248] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[0249] A "sensor" is a device that detects physical phenomena and outputs them as data.

[0250] A "camera" is a device that captures images or videos.

[0251] "Real-time" refers to processing and analysis at the exact moment an event occurs.

[0252] "Analysis" means examining data in detail to clarify its meaning and structure.

[0253] "Output" refers to displaying the results of a calculation or analysis or sending them to another system.

[0254] As an embodiment of the present invention, a system installed in an autonomous vehicle will be described as an example. This system calculates the amount of damages in real time when a traffic accident occurs.

[0255] First, autonomous vehicles are equipped with multiple sensors and cameras that are used to collect detailed information about accidents. Specifically, they obtain data in real time about the location and time of the accident, the circumstances of the people involved, and other information.

[0256] The acquired data is then sent to a computer system in the vehicle, which uses AI (Artificial Intelligence) to analyze the data and calculate the amount of damages. The AI ​​uses models to calculate the amount of damages based on the "Red Book" and "Blue Book".

[0257] The specific process is as follows: first, data obtained from sensors and cameras is input into a computer system. Next, AI analyzes the data and calculates the amount of damages. Finally, the calculation result is notified to the user via the vehicle's display or a smartphone application.

[0258] The hardware used includes sensors, cameras, and computer systems installed in the autonomous vehicle, while the software uses programming languages ​​such as Python to implement AI models and transmit and receive data using HTTP requests.

[0259] As a concrete example, the following prompt sentence can be input into a generative AI model to calculate the amount of damages:

[0260] "Insurance contract information: Comprehensive insurance, Insurance premium: 50,000 yen, Accident details: Location: Tokyo, Japan, Time: 2023-10-01 14:30:00, Parties involved: Vehicle A, Vehicle B"

[0261] Based on this prompt, the AI ​​model calculates the amount of compensation and notifies the user of the result, making it possible to calculate compensation quickly and accurately when an accident occurs.

[0262] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0263] Step 1:

[0264] Sensors and cameras in autonomous vehicles collect detailed information about the accident.

[0265] Input: Data such as the location and time of the accident, and the circumstances of the people involved.

[0266] Output: Collected accident details.

[0267] How it works: Sensors detect the location, speed, and strength of the impact, and cameras capture images of the accident scene. This data is sent to the vehicle's computer system.

[0268] Step 2:

[0269] A computer system within the vehicle receives the collected data and prepares it for analysis.

[0270] Input: Accident details sent from sensors and cameras.

[0271] Output: Data formatted for analysis.

[0272] Specific operations: Format the received data, extract the necessary information, and prepare it in a form suitable for analysis.

[0273] Step 3:

[0274] A computer system will input the data into an AI model to calculate damages.

[0275] Input: Formatted accident details.

[0276] Output: Calculated damages.

[0277] Specific operation: The formatted data is input into the AI ​​model, and the amount of damages is calculated based on the "red book" and "blue book." The AI ​​model is implemented in a programming language such as Python, and sends and receives data using HTTP requests.

[0278] Step 4:

[0279] The calculation results are notified to the user via the vehicle's display or smartphone application.

[0280] Input: Calculated damages.

[0281] Output: A damages notice displayed to the user.

[0282] Specific operation: The calculation results are sent to a display or smartphone application to be displayed in a format that is easy for users to understand. This allows users to quickly and accurately check the amount of compensation in the event of an accident.

[0283] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0284] "Example 1"

[0285] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[0286] "Example 2"

[0287] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[0288] The process flow of each embodiment will be described below.

[0289] "Example 1"

[0290] Step 1: The user enters information about a traffic accident into the system, including details of the accident, the condition of the victims, the extent of damage, etc.

[0291] Step 2: The emotion engine works to recognize emotions from the user's tone of voice, facial expressions, choice of words, etc. This emotion recognition is done from the tone of voice, facial expressions, choice of words, etc. when the user enters information.

[0292] Step 3: If the emotion recognized is a strong emotion such as anger or sadness, the amount of compensation will be calculated taking that emotion into account. Specifically, a certain amount will be added or multiplied to the amount of compensation depending on the strength and type of emotion.

[0293] Step 4: The calculated amount of compensation is presented to the user. At this time, the emotion engine's emotion recognition results and their impact are clearly indicated to ensure transparency to the user.

[0294] Example 1

[0295] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0296] Conventional traffic accident compensation standard judgment systems calculate the amount of compensation based on information about the traffic accident, but since they do not take into account the emotional damage of the user, it is difficult to calculate an appropriate amount of compensation. In addition, it can take time to read and analyze information about traffic accidents, which is insufficient in situations where a quick response is required.

[0297] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0298] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the user's emotions, and a means for adjusting the calculation of the amount of compensation based on the recognized emotions. This enables a more appropriate calculation of the amount of compensation that takes into account the emotional damage of the user.

[0299] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0300] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[0301] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[0302] "Information regarding traffic accidents" refers to detailed data related to accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[0303] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[0304] "User emotion" refers to a psychological state such as anger, sadness, or happiness felt by a user.

[0305] "Means for recognizing emotions" refers to technology for analyzing and recognizing emotions from a user's tone of voice, facial expressions, choice of words, etc.

[0306] A "damages adjustment measure" is a method for appropriately modifying or adjusting the amount of damages based on perceived feelings.

[0307] The present invention relates to a simplified determination system for traffic accident compensation standards, and in particular to a system for calculating the amount of compensation taking into account the user's emotions.

[0308] System Configuration

[0309] Hardware

[0310] Server: A server with high-performance computing power (e.g. a virtual server for cloud services)

[0311] Terminal: The device through which the user enters information (e.g. computer, smartphone)

[0312] Input devices: Microphone, camera (to recognize the user's tone of voice and facial expressions)

[0313] software

[0314] Database: A database for storing information about traffic accidents and compensation criteria (e.g. MySQL)

[0315] AI model: An AI model (e.g. TensorFlow) for analyzing traffic accident information and calculating compensation amounts.

[0316] Emotion recognition engine: Software for recognizing user emotions (e.g. Affectiva)

[0317] System Operation

[0318] 1. The user enters detailed information about a traffic accident, such as the location and time of the accident, and the circumstances of the people involved, into a web form.

[0319] Example: "Location of accident: Shibuya-ku, Tokyo, Time: 14:00 on October 1, 2023, Situation of the parties involved: Pedestrian hit by car."

[0320] 2. The device sends the entered information to the server. The device sends the data using an HTTP request.

[0321] 3. The server saves the received information in the database. The server executes an INSERT query in the MySQL database to save the information.

[0322] 4. The server passes the stored information to the AI ​​model for analysis. The server inputs the data into the TensorFlow model and performs the analysis.

[0323] 5. The server calculates the amount of damages based on the analysis results. The server refers to the "Red Book" and "Blue Book" databases to calculate the amount of damages.

[0324] 6. When a user enters information about a traffic accident, the emotion engine recognizes the user's emotion. For example, if the user says "I'm very sad," the emotion engine recognizes "sadness."

[0325] 7. The server receives emotion data from the emotion engine. The server receives the data from the emotion engine via an HTTP request.

[0326] 8. The server saves the emotion data and traffic accident information in the database. The server executes an INSERT query on the MySQL database to save the information.

[0327] 9. The server passes the stored information to the AI ​​model for analysis. The server inputs the data into the TensorFlow model and performs the analysis.

[0328] 10. The server calculates the amount of damages based on the analysis results and takes emotions into account. The server refers to the databases of the "Red Book" and "Blue Book" and calculates the amount of damages taking into account emotional data.

[0329] 11. The server sends the calculation result to the terminal. The server sends the data to the terminal using an HTTP response.

[0330] 12. The terminal displays the calculation result to the user. The terminal displays "Amount of damages: 5.5 million yen (emotions taken into consideration)" on the web page.

[0331] Examples of prompt statements

[0332] 1. Simplified Judgment System for Traffic Accident Compensation Standards

[0333] Prompt: "Please enter details about the traffic accident. For example, location, time, and circumstances of the accident."

[0334] 2. System combining emotion engines

[0335] Prompt: "Please enter information about the traffic accident and express your feelings. For example, location of the accident, time, situation of the people involved, and emotions (anger, sadness, etc.)."

[0336] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0337] Step 1:

[0338] The user enters detailed information about the traffic accident.

[0339] Input: Details of the accident, such as location, time, and circumstances of the people involved

[0340] Specific actions: A user enters the following information into a web form: "Accident location: Shibuya-ku, Tokyo, Time: 14:00 on October 1, 2023, Situation of the parties involved: Pedestrian hit by car."

[0341] Output: Detailed information about the traffic accidents entered

[0342] Step 2:

[0343] The terminal transmits the input information to the server.

[0344] Input: User-entered details of the traffic accident

[0345] Specific operation: The device sends data to the server using an HTTP request.

[0346] Output: Detailed information about the traffic accident sent to the server

[0347] Step 3:

[0348] The server stores the received information in a database.

[0349] Input: Traffic accident details sent from the device

[0350] What happens next: The server executes an INSERT query into the MySQL database to save the information.

[0351] Output: Detailed information about traffic accidents stored in a database

[0352] Step 4:

[0353] The server passes the stored information to the AI ​​model for analysis.

[0354] Input: Traffic accident details stored in the database

[0355] What happens: The server inputs the data into the TensorFlow model and performs the analysis.

[0356] Output: Analysis results (data necessary for calculating the amount of damages)

[0357] Step 5:

[0358] The server calculates the amount of compensation based on the analysis results.

[0359] Input: Analysis results from the AI ​​model

[0360] Specific operation: The server refers to the "Red Book" and "Blue Book" databases and calculates the amount of damages.

[0361] Output: Calculated damages

[0362] Step 6:

[0363] When a user enters information about a traffic accident, the emotion engine recognizes the user's emotions.

[0364] Input: User tone of voice, facial expressions, and language

[0365] What happens: If a user says "I'm so sad," the emotion engine recognizes "sad."

[0366] Output: Recognized emotion data

[0367] Step 7:

[0368] A server receives emotion data from an emotion engine.

[0369] Input: Sentiment data from the sentiment engine

[0370] Specific operation: The server receives data from the emotion engine via an HTTP request.

[0371] Output: Emotion data received by the server

[0372] Step 8:

[0373] The server stores the emotion data and traffic accident information in a database.

[0374] Input: Sentiment data and details of traffic accidents

[0375] What happens next: The server executes an INSERT query into the MySQL database to save the information.

[0376] Output: Emotion data and traffic accident information stored in a database

[0377] Step 9:

[0378] The server passes the stored information to the AI ​​model for analysis.

[0379] Input: Emotion data and traffic accident information stored in the database

[0380] What happens: The server inputs the data into the TensorFlow model and performs the analysis.

[0381] Output: Analysis results (data necessary for calculating damages taking emotions into account)

[0382] Step 10:

[0383] The server calculates the amount of damages based on the analysis results, taking emotions into account.

[0384] Input: Analysis results from the AI ​​model and emotion data

[0385] Specific operation: The server refers to the database of "Red Book" and "Blue Book" and calculates the amount of compensation by taking into account the emotional data.

[0386] Output: Calculated damages taking emotions into account

[0387] Step 11:

[0388] The server transmits the calculation result to the terminal.

[0389] Input: Calculated damages taking into account emotions

[0390] Specific operation: The server sends data to the device using an HTTP response.

[0391] Output: Damage amount sent to the terminal

[0392] Step 12:

[0393] The terminal displays the calculation results to the user.

[0394] Input: damages amount sent from server

[0395] Specific operation: The device displays the following on a web page: "Amount of damages: 5.5 million yen (emotions taken into consideration)."

[0396] Output: The damages displayed to the user.

[0397] (Application example 1)

[0398] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0399] When a traffic accident occurs, it is important to calculate the amount of compensation quickly and accurately. However, in conventional systems, it takes a lot of time and effort to manually input detailed information about the accident and calculate the amount of compensation. It is also difficult to take into account the emotional damage of the victim, making it difficult to calculate an appropriate amount of compensation. Furthermore, in the case of autonomous vehicles, it is required to collect information at the time of the accident and calculate the amount of compensation in real time. A new system is needed to solve these problems.

[0400] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0401] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the emotions of the passengers, a means for adjusting the amount of compensation based on the recognized emotions, and a means for being installed in the autonomous vehicle. This makes it possible to quickly and accurately calculate the amount of compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that takes into account the emotional damage of the victim.

[0402] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0403] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[0404] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[0405] "Information regarding traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[0406] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[0407] "Passenger emotions" refers to the psychological state and feelings of passengers when they are involved in a traffic accident.

[0408] "Means of recognizing emotions" refers to technology that analyzes and recognizes emotions from passengers' tone of voice, facial expressions, language, etc.

[0409] An "autonomous vehicle" is a vehicle that can drive autonomously using artificial intelligence and sensor technology.

[0410] An "adjusting tool" is a method or technique for appropriately modifying damage awards based on perceived sentiment.

[0411] The system for carrying out this invention has the following configuration: The server includes a means for performing a simplified determination of traffic accident compensation standards using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing passenger emotions, a means for adjusting the amount of compensation based on the recognized emotions, and a means for being installed in the autonomous vehicle.

[0412] Program processing explanation

[0413] The server first collects information about the traffic accident, including details such as the location of the accident, time, vehicle speed, weather, etc. This information is obtained automatically from sensors, GPS and the vehicle's internal systems.

[0414] Next, to recognize passenger emotions, cameras and microphones installed in the vehicle are used. The camera captures the passenger's facial expressions, and the microphone collects the passenger's voice. These data are analyzed using software such as OpenCV and SpeechRecognition. The analyzed data is input into a deep learning model using Keras to recognize the passenger's emotions.

[0415] The recognized emotions and collected traffic accident information are input into an AI model for calculating the amount of compensation. The AI ​​model calculates the amount of compensation based on the traffic accident compensation standard. Furthermore, the amount of compensation is adjusted based on the recognized emotions.

[0416] Examples

[0417] For example, if the accident occurred in Tokyo, the vehicle speed was 60km / h, the weather was sunny, and the passengers expressed anger, the AI ​​model would use this information to calculate the compensation amount and adjust it to take into account the anger.

[0418] Examples of prompt statements

[0419] The accident occurred in Tokyo, the vehicle speed was 60km / h, and the weather was fine. The passengers showed angry emotions. Please calculate the amount of compensation based on this information.

[0420] In this way, it will be possible to quickly and accurately calculate compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that also takes into account the emotional damage suffered by the victim.

[0421] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0422] Step 1:

[0423] The server collects information about traffic accidents, including details such as the location and time of the accident, the vehicle's speed, and weather, automatically obtained from sensors, GPS, and the vehicle's internal systems. This information is then stored in a database.

[0424] Inputs: Data from sensors, GPS, and vehicle internal systems

[0425] Output: Detailed information about traffic accidents (location, time, speed, weather)

[0426] Step 2:

[0427] The server recognizes passengers' emotions using cameras and microphones installed in the vehicle. The camera captures the passengers' facial expressions, and the microphone collects the passengers' voices. These data are analyzed using software such as OpenCV and SpeechRecognition. The analyzed data is input into a deep learning model using Keras to recognize the passengers' emotions.

[0428] Input: Camera video, microphone audio

[0429] Output: Passenger sentiment data

[0430] Step 3:

[0431] The server inputs the recognized emotions and collected traffic accident information into an AI model for calculating the amount of compensation, which calculates the amount of compensation based on the traffic accident compensation standard.

[0432] Input: Traffic accident details, passenger emotion data

[0433] Output: Initial damages amount

[0434] Step 4:

[0435] The server adjusts the damage amount based on the recognized emotion, for example, if the passenger shows emotion of anger, it increases the damage amount to take the emotional damage into account.

[0436] Input: Initial damage amount, passenger emotion data

[0437] Output: Adjusted damages

[0438] Step 5:

[0439] The server outputs the final amount of damages and notifies the user via the vehicle's display or smartphone app.

[0440] Input: Adjusted damages amount

[0441] Output:Notification to the user

[0442] In this way, it will be possible to quickly and accurately calculate compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that also takes into account the emotional damage suffered by the victim.

[0443] Example 2

[0444] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0445] Conventional traffic accident compensation calculation systems have the problem that they are unable to take into account the emotional damage of the user, making it difficult to calculate an appropriate amount of compensation. In addition, inputting information about traffic accidents is cumbersome, making the system difficult to use for users.

[0446] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0447] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the user's emotions, and a means for adjusting the amount of compensation based on the recognized emotions. This makes it possible to calculate an appropriate amount of compensation taking into account the emotional damage of the user.

[0448] The "means for simplified determination of traffic accident compensation standards using AI" is a function that uses artificial intelligence technology to quickly and easily determine the standard for compensation amounts in traffic accidents.

[0449] "Means of reading information related to traffic accidents" refers to a function for inputting detailed information about traffic accidents (such as the location and time of the accident, the circumstances of the parties involved, etc.) into the system and importing it as data.

[0450] The "means for calculating the amount of compensation based on the loaded information" is a function for calculating the amount of compensation based on the loaded traffic accident information.

[0451] The "means for recognizing the user's emotions" is a function for detecting and recognizing the emotions of the user from the user's tone of voice, facial expressions, choice of words, etc.

[0452] The "means for adjusting the amount of damages based on the recognized emotion" is a function for appropriately adjusting the amount of damages taking into account the recognized emotion of the user.

[0453] This invention is a system for automobile insurance policyholders, where the user inputs their insurance contract information and detailed information about the traffic accident, and the AI ​​analyzes this information and calculates the amount of compensation. In addition, by combining it with an emotion engine that recognizes the user's emotions, it becomes possible to calculate the amount of compensation that takes emotional damage into account.

[0454] Hardware and Software Used

[0455] 1. Server

[0456] The server receives the information sent by the user and analyzes it using an AI model. The server is equipped with an AI model implemented in Python, and has the function of calculating the amount of damages based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards."

[0457] 2. Terminal

[0458] The terminal provides an interface for the user to input information. The terminal has a communication function for transmitting the input information to the server. The communication is performed using the HTTPS protocol, and the data is encrypted.

[0459] 3. Emotion Engine

[0460] The emotion engine is software for recognizing emotions from a user's tone of voice, facial expressions, language, etc. The emotion engine is built using TensorFlow and analyzes the user's emotions in real time.

[0461] Examples

[0462] For example, if a user enters the following information:

[0463] Insurance contract information: Type of insurance is "Comprehensive insurance", premium is "100,000 yen per year"

[0464] Traffic accident details: The accident occurred in "Shibuya Ward, Tokyo," the time was "3:00 p.m.", and the circumstances of the parties involved were "the other party ran a red light."

[0465] With this information, the server uses an AI model to calculate damages, and if the emotion engine detects that the user is feeling a strong sense of anger while typing, it will adjust the damages amount to take that emotion into account.

[0466] Examples of prompt statements

[0467] Here is an example of a prompt to be input to the generative AI model:

[0468] Use your insurance policy information and the details of the traffic accident to help us calculate your damages. Use the following information:

[0469] Insurance type: Comprehensive insurance

[0470] Insurance premium: 100,000 yen per year

[0471] Location of accident: Shibuya Ward, Tokyo

[0472] Time of accident: 3 p.m.

[0473] Situation of the parties involved: The other party ignored the traffic signal.

[0474] Also consider that the user's emotion is "anger."

[0475] Using this prompt, the generative AI model can calculate the amount of damages based on the necessary information and output a result that takes emotions into account.

[0476] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0477] Step 1:

[0478] The user enters information

[0479] The user inputs their own insurance contract information (type of insurance, premium, etc.) and detailed information about the traffic accident (location of the accident, time, circumstances of the parties involved, etc.) into an input form on the device. For example, the user inputs information such as "comprehensive insurance," "100,000 yen per year," "Shibuya-ku, Tokyo," "3:00 p.m.," and "the other party ran a red light." The input information is temporarily stored in the device's memory.

[0480] Step 2:

[0481] The device sends information

[0482] The terminal sends the insurance policy information and traffic accident details entered by the user to the server using the HTTPS protocol and the data is encrypted. The input data is converted to JSON format and sent to the server's API endpoint.

[0483] Step 3:

[0484] The server receives the information

[0485] The server receives the insurance contract information and the detailed information of the traffic accident sent from the terminal. The received data is stored in a database. Specifically, the server parses the received JSON data and stores each field in the corresponding column of the database.

[0486] Step 4:

[0487] The server analyzes the information

[0488] The server inputs the received information into the AI ​​model and begins analysis. Specifically, the AI ​​model implemented in Python calculates the amount of compensation based on the "Red Book" "Civil Traffic Accident Lawsuit Damage Compensation Calculation Standards" and the "Blue Book" "Traffic Accident Damage Calculation Standards." For example, the AI ​​model analyzes information such as "comprehensive insurance," "100,000 yen per year," "Shibuya Ward, Tokyo," "3:00 p.m.," and "other party ignored a traffic signal" to calculate the initial amount of compensation. The calculation results are temporarily stored in memory.

[0489] Step 5:

[0490] Emotion engine recognizes user emotions

[0491] When a user inputs information, the emotion engine recognizes emotions from the user's tone of voice, facial expressions, and language. For example, if a user feels strong anger while inputting information, the emotion engine recognizes that emotion. The emotion engine is built using TensorFlow and analyzes emotions in real time. The recognized emotion data is sent to the server.

[0492] Step 6:

[0493] The server adjusts the damage amount based on emotions.

[0494] The server adjusts the amount of damages based on the emotion recognition results from the emotion engine. For example, if the user feels strong anger, the amount of damages is increased taking that emotion into account. Specifically, a correction value that takes into account the influence of the emotion is applied to the initial amount of damages to calculate the final amount of damages. The adjusted amount of damages is stored in the database.

[0495] Step 7:

[0496] The server outputs the results

[0497] The server outputs the final calculated amount of damages to the user. The result is displayed on the terminal screen and sent to the user's email address. For example, a result such as "The final amount of damages is 1 million yen" may be displayed. The output data is generated in HTML format and sent to the user's terminal.

[0498] (Application example 2)

[0499] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0500] Conventional traffic accident compensation calculation systems calculate compensation amounts based on detailed information about the accident, but are unable to take into account the emotional damage suffered by passengers. Therefore, there is a need for a more appropriate compensation calculation method that includes emotional damage. There is also a need for a system that can calculate compensation amounts in real time when an accident occurs.

[0501] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0502] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for analyzing data obtained from the vehicle's sensors and cameras, and a means for taking into account the emotional state of the occupants using an emotion engine that recognizes their emotions. This makes it possible to calculate the amount of compensation in real time when an accident occurs, and to calculate a more appropriate amount of compensation that also takes into account emotional damage.

[0503] "AI" stands for artificial intelligence, a technology that allows computers to mimic human intelligence to learn, reason, and self-correct.

[0504] The "Traffic Accident Compensation Standards" are the standards for calculating the amount of compensation in traffic accidents, and specifically refer to the standards set out in the "Red Book" and "Blue Book."

[0505] "Information on traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[0506] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[0507] A "sensor" is a device that detects a physical phenomenon and converts it into an electrical signal.

[0508] A "camera" is a device that converts light into electrical signals to record images or videos.

[0509] An "emotion engine" is a technology that recognizes emotions from a user's tone of voice, facial expressions, choice of words, etc., and analyzes their emotional state.

[0510] "Emotional state" refers to the type and intensity of emotion a user is feeling.

[0511] A "system" refers to a collection of devices or programs in which multiple elements function in conjunction with each other.

[0512] The system for carrying out this invention is configured as follows: The server includes a means for performing a simplified determination of traffic accident compensation standards using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for analyzing data obtained from the vehicle's sensors and cameras, and a means for taking into account the emotional state of the occupants using an emotion engine that recognizes their emotions.

[0513] Program processing explanation

[0514] The server first receives real-time data from vehicle sensors and cameras, including information on the location and time of the accident, vehicle speed, impact force, etc. The server then analyzes this data to generate detailed information about the traffic accident.

[0515] The server then uses an emotion engine to analyze the passenger's tone of voice and facial expressions captured by the vehicle's microphones and cameras to recognize the passenger's emotional state. The emotion engine uses software called EmotionRecognizer to identify the passenger's emotions.

[0516] The server then calculates the amount of compensation based on the traffic accident compensation standard. Specifically, the AI ​​calculates the amount of compensation using the standards set out in the "Red Book" and "Blue Book." In addition, it adjusts the final amount of compensation by taking into account the perceived emotional state.

[0517] Examples

[0518] For example, if the accident occurred in Tokyo, the time of the accident was 14:30 on October 1, 2023, the vehicle speed was 60 km / h, and the impact force was 500 N, the server would calculate the amount of compensation based on this information. Also, if the passenger is feeling angry, the emotion engine would recognize that emotion and reflect it in the amount of compensation.

[0519] Examples of prompt statements

[0520] Below are examples of prompts to be input to the generative AI model.

[0521] The accident location is Tokyo, and the accident time is October 1, 2023 at 14:30. The vehicle speed is 60 km / h, and the impact force is 500 N. The occupants feel angry. Based on this information, please calculate the amount of damages.

[0522] In this way, the server can calculate compensation in real time, taking into account the details of the accident and the emotional state of the occupants.

[0523] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0524] Step 1:

[0525] The server receives data from vehicle sensors and cameras in real time. As input, it receives information such as the location and time of the accident, the vehicle speed, and the impact force, and analyzes this data to generate detailed information about the traffic accident. As output, it obtains the analyzed detailed information about the traffic accident.

[0526] Step 2:

[0527] The server uses the emotion engine to analyze the passenger's tone of voice and facial expressions captured by the in-car microphones and cameras. As input, it receives audio and video data and identifies the passenger's emotions using software called EmotionRecognizer. As output, it gets the recognized emotional state.

[0528] Step 3:

[0529] The server calculates the amount of compensation based on the traffic accident compensation standard. As input, it receives the detailed information of the traffic accident obtained in step 1 and the emotional state obtained in step 2, and the AI ​​calculates the amount of compensation using the standards described in the "Red Book" and "Blue Book". As output, it obtains the calculated amount of compensation.

[0530] Step 4:

[0531] The server adjusts the final damages amount taking into account the perceived emotional state. As input, it takes the damages amount calculated in step 3 and the perceived emotional state in step 2, and calculates the final damages amount that reflects the emotional damage. As output, it gets the adjusted final damages amount.

[0532] Step 5:

[0533] The server notifies the user of the final amount of damages. As input, it receives the final amount of damages obtained in step 4 and sends a notification to the user's terminal. As output, it obtains the amount of damages notified to the user.

[0534] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0535] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0536] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0537] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0538] [Second embodiment]

[0539] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0540] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0541] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0542] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0543] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0544] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0545] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0546] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0547] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0548] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0549] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0550] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0551] "Example 1"

[0552] One embodiment of the present invention is a simplified system for determining standards for compensation for traffic accident damages using AI. This system is equipped with a means for reading information about traffic accidents and a means for calculating the amount of compensation for damages based on the read information. Specifically, the system receives detailed information about the traffic accident (such as the location and time of the accident, and the circumstances of the parties involved) as input, and the AI ​​analyzes this information. The system then calculates the amount of compensation for damages based on the "Red Book" "Standards for Calculating Compensation for Civil Traffic Accident Lawsuits" and the "Blue Book" "Standards for Calculating Compensation for Traffic Accident Damages," and outputs the results.

[0553] "Example 2"

[0554] Another embodiment of the present invention is a system targeted at voluntary automobile insurance subscribers. In this system, the subscriber inputs his / her insurance contract information and detailed information about the traffic accident, and AI analyzes this information and calculates the amount of damages. Specifically, the subscriber inputs his / her insurance contract information (type of insurance, insurance premium, etc.) and detailed information about the traffic accident (location of the accident, time, status of the parties involved, etc.), and AI analyzes this information. Then, the AI ​​calculates the amount of damages based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards," and outputs the results.

[0555] The process flow of each embodiment will be described below.

[0556] "Example 1"

[0557] Step 1: The user enters detailed information about the traffic accident (location, time of the accident, circumstances of the parties involved, etc.) into the system.

[0558] Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[0559] Step 3: The calculated amount of damages is output to the user.

[0560] "Example 2"

[0561] Step 1: A voluntary automobile insurance policyholder enters their insurance contract information (type of insurance, premium, etc.) and detailed information about the traffic accident (location of the accident, time, circumstances of the parties involved, etc.) into the system. Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[0562] Step 3: The calculated amount of damages is output to the subscriber.

[0563] Example 1

[0564] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0565] Calculating compensation for traffic accidents requires specialized knowledge and is time-consuming and laborious. In addition, the calculation standards for compensation are complex, making it difficult for general users to easily understand and apply. For this reason, there is a demand for a system that can calculate compensation quickly and accurately.

[0566] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0567] In this invention, the server includes a means for inputting detailed information about a traffic accident, a means for transmitting the input information to the server, a means for the server to analyze the information received, a means for the server to calculate the amount of compensation using the generative AI model, a means for transmitting the calculation result to the terminal, and a means for the terminal to display the calculation result to the user. This allows the user to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation.

[0568] "Detailed information about the traffic accident" is specific information related to the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[0569] "Input means" refers to an interface or device that allows a user to input detailed information about a traffic accident.

[0570] A "server" is a computer system that receives information sent by users, analyzes it, and calculates the amount of damages.

[0571] The "transmitting means" refers to a communication means for transmitting information from the terminal to the server.

[0572] "Means of analysis" refers to software or algorithms used by the server to process the information it receives and check its consistency.

[0573] A "generative AI model" is an artificial intelligence model trained to calculate compensation amounts for traffic accidents.

[0574] A “means for calculating” is a process or algorithm for calculating damages using a generative AI model.

[0575] A "terminal" is a device through which a user inputs information and checks the results of calculations.

[0576] The "display means" refers to an interface for visually presenting to the user the calculation results that the terminal receives from the server.

[0577] The present invention is a system for quickly and accurately calculating the amount of compensation for damages in a traffic accident. A specific embodiment of this system will be described below.

[0578] First, the user uses the terminal to input detailed information about a traffic accident. The input form includes items such as the location of the accident, the time of the accident, the circumstances of the people involved, etc. For example, the user inputs information according to the following prompts:

[0579] "Where did the accident occur?"

[0580] "What time did the accident occur?"

[0581] Please tell us the situation of the parties involved.

[0582] The information entered by the user is sent from the terminal to the server, which then sends the information to the server in an appropriate format (e.g., JSON format).

[0583] The server analyzes the information it receives, which may include checking the integrity of the information and pre-processing it, such as making sure the time of occurrence is not in the future and that the location is a valid place name.

[0584] The server then uses a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information and calculates the amount of compensation based on past traffic accident data and standards.

[0585] The calculation result is sent from the server to the terminal. The terminal displays the received calculation result to the user. The user can check the amount of compensation displayed on the terminal screen. For example, a result such as "The amount of compensation is 5 million yen" may be displayed.

[0586] This system allows users to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation. The hardware used includes the user's terminal (PC, smartphone, etc.) and the server. The software includes the input form, communication protocol, analysis algorithm, and generative AI model.

[0587] As a concrete example, if the user enters the following information:

[0588] Location of accident: Shinjuku Ward, Tokyo

[0589] Time of accident: October 1, 2023, 14:30

[0590] Situation of the parties involved: Vehicle A runs a red light and crashes into vehicle B.

[0591] The server receives this information and performs analysis using the generative AI model. As a result of the analysis, the amount of compensation is calculated and a result such as "The amount of compensation is 5 million yen" is displayed on the terminal.

[0592] In this way, users can easily check the amount of compensation by simply entering detailed information about a traffic accident.

[0593] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0594] Step 1:

[0595] The user enters detailed information about the traffic accident.

[0596] The user inputs information such as the location and time of the accident, and the status of the people involved into the input form on the terminal. For example, the user inputs information following prompts such as "Where did the accident occur?", "What time did the accident occur?", and "Please tell us the status of the people involved." The input information is temporarily stored in the terminal's memory.

[0597] Step 2:

[0598] The terminal transmits the input information to the server.

[0599] The terminal sends the information entered by the user to the server in an appropriate format (for example, JSON format). The data sent includes the location of the accident, the time of the accident, the status of the people involved, etc. For example, the following JSON data is sent:

[0600] json

[0601] {

[0602] "location": "Shinjuku-ku, Tokyo",

[0603] "time": "2023-10-01T14:30:00",

[0604] "details": "Vehicle A runs a red light and collides with vehicle B"

[0605] }

[0606] Step 3:

[0607] The server analyzes the information it receives.

[0608] The server receives the JSON data sent from the terminal and begins analyzing it. The analysis includes checking the consistency of the information and preprocessing. For example, it checks whether the time of occurrence is a future date, whether the location is a valid place name, etc. As a result of the analysis, data with confirmed consistency is generated.

[0609] Step 4:

[0610] The server uses the generative AI model to calculate damages.

[0611] The server inputs the analyzed information into a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information based on past traffic accident data and standards, and calculates the amount of compensation. The amount of compensation is generated as a calculation result.

[0612] Step 5:

[0613] The server transmits the calculation result to the terminal.

[0614] The server sends the calculated amount of damages to the terminal in an appropriate format (for example, JSON format). The data sent includes details of the amount of damages. For example, the following JSON data is sent:

[0615] json

[0616] {

[0617] "compensation_amount": 5000000,

[0618] "details": "The damages amount to 5 million yen."

[0619] }

[0620] Step 6:

[0621] The terminal displays the calculation results to the user.

[0622] The terminal displays the calculation results received from the server to the user. The user can check the amount of damages displayed on the terminal screen. For example, the result "The amount of damages is 5 million yen" may be displayed.

[0623] (Application example 1)

[0624] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0625] When a traffic accident occurs, it is important for both the victim and the at-fault party to calculate the amount of compensation quickly and accurately. However, the conventional method requires manually collecting detailed information about the accident and having experts analyze it before calculating the amount of compensation, which is time-consuming and labor-intensive. In addition, as autonomous vehicles become more widespread, there is a demand for a system that can respond immediately when an accident occurs.

[0626] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting accident information from the sensor or camera of the autonomous vehicle, a means for analyzing the collected information and calculating the amount of compensation, a means for calculating the amount of compensation using a generative AI model, and a means for generating a prompt sentence and inputting it into the AI ​​model. This makes it possible to quickly and accurately calculate the amount of compensation when a traffic accident occurs.

[0627] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0628] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[0629] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[0630] "Information regarding traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[0631] "Amount of damages" refers to the amount of money paid to a victim for damages suffered in a traffic accident.

[0632] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[0633] A "sensor" is a device that detects physical phenomena and outputs them as data.

[0634] A "camera" is a device that captures images or videos.

[0635] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[0636] A "prompt" is an instruction to be input to a generative AI model, which serves as a guideline for the model to generate appropriate output.

[0637] The system for carrying out the present invention is for quickly and accurately calculating the amount of compensation for damages when a traffic accident occurs. A specific embodiment of this system will be described below.

[0638] The system includes a means of collecting accident information from sensors and cameras installed in the autonomous vehicle, which allows detailed data such as the location and time of the accident, as well as the circumstances of the people involved, to be collected in real time. The collected data is then sent to a computer in the vehicle where it undergoes initial processing.

[0639] Then, the initially processed data is sent to a server. The server uses a generative AI model to analyze the collected accident information. Specifically, the server includes the following means:

[0640] 1. A means of reading information about traffic accidents: Read data collected from sensors and cameras to obtain detailed information about accidents.

[0641] 2. Method of calculating damages: Based on the information read in, the generative AI model calculates the amount of damages. The calculation is based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards."

[0642] 3. A means for generating prompt sentences and inputting them into the AI ​​model: A prompt sentence is generated based on the accident information and input into the generative AI model.

[0643] For example, the following prompt would be generated:

[0644] A traffic accident has occurred. Details of the accident are as follows:

[0645] Location: Tokyo, Japan

[0646] Occurrence time: 2023-10-01T12:34:56

[0647] Status of the parties: Driver A (Injured), Driver B (Uninjured)

[0648] Vehicle Damage: Severe

[0649] Use this information to assess your damages.

[0650] The server inputs this prompt into a generative AI model to calculate the amount of damages, and the calculation result is notified to the user via an in-vehicle display or a smartphone application.

[0651] This system will enable the prompt and accurate calculation of compensation when a traffic accident occurs, enabling a prompt response for both the victim and the at-fault party. In addition, as autonomous vehicles become more widespread, the response to accidents will be automated, further improving safety and efficiency.

[0652] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0653] Step 1:

[0654] Sensors and cameras in autonomous vehicles detect the occurrence of a traffic accident. The sensors collect impact and location information, and the cameras capture video of the accident scene. These data are sent to a computer in the vehicle. The input is data from the sensors and cameras, and the output is initially processed accident information.

[0655] Step 2:

[0656] An in-vehicle computer performs initial processing of the collected data, analyzing impact data and location information from sensors and extracting accident details from camera footage. The input is raw data from sensors and cameras, and the output is analyzed accident details.

[0657] Step 3:

[0658] The initial processed accident information is sent to the server. The server receives this information and stores it in a database. The input is the accident details sent from the computer in the vehicle, and the output is the accident information stored in the database.

[0659] Step 4:

[0660] The server generates a prompt sentence based on the stored accident information. Specifically, it converts information such as the location and time of the accident, and the situation of the people involved into text format. The input is the accident information stored in the database, and the output is the generated prompt sentence.

[0661] Step 5:

[0662] The server inputs the generated prompt sentence into the generative AI model. The generative AI model analyzes the prompt sentence and calculates the amount of damages. The input is the generated prompt sentence, and the output is the calculated amount of damages.

[0663] Step 6:

[0664] The server notifies the user of the calculated amount of compensation through the display in the vehicle or a smartphone application. The input is the calculated amount of compensation, and the output is the amount of compensation notified to the user.

[0665] Step 7:

[0666] The user checks the notified amount of damages and contacts the insurance company or relevant organizations if necessary. The input is the notified amount of damages, and the output is the user's confirmation and contact.

[0667] Example 2

[0668] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0669] Conventional calculations of compensation for traffic accidents require manual work by people with specialized knowledge, which is time-consuming and labor-intensive. In addition, the calculation standards for compensation can be complex, making accurate calculations difficult. Furthermore, there was a lack of a way for users to easily input their own insurance contract information and detailed information about the accident and quickly find out the amount of compensation.

[0670] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0671] In this invention, the server includes a means for a user to input insurance contract information and detailed information about a traffic accident, a means for the server to receive the input information and perform preprocessing, a means for the server to input the preprocessed information into a generative AI model and perform analysis, a means for the server to calculate the amount of damages based on the analysis result, a means for the server to output the calculation result to the user's terminal, and a means for the user to check the result on the terminal. This allows the user to easily input information and quickly and accurately know the amount of damages.

[0672] A "user" is an individual or legal entity that utilizes the system to input insurance policy information and detailed information about a traffic accident.

[0673] "Insurance contract information" is detailed information about insurance, such as the type of insurance the user has subscribed to and the insurance premiums.

[0674] "Detailed information about the traffic accident" refers to specific information about the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[0675] A “server” is a computer system that receives information input by a user, performs preprocessing, and analyzes it using a generative AI model.

[0676] "Preprocessing" refers to processing the data received to format it and make it suitable for analysis.

[0677] A "generative AI model" is an artificial intelligence model built using a machine learning framework to analyze input information and calculate the amount of damages.

[0678] "Analysis" is the process in which the generative AI model performs calculations and inferences based on the input information to determine the amount of damages.

[0679] "Amount of damages" means the amount to be paid for damages in a traffic accident.

[0680] A "terminal" is a device that a user uses to enter information and view results from a server.

[0681] The “results” are information on the amount of damages calculated by the generative AI model.

[0682] This invention is a system in which a user inputs insurance contract information and detailed information about a traffic accident, and a server analyzes this information to calculate the amount of compensation. A specific embodiment of this system will be described below.

[0683] Hardware and Software Used

[0684] Hardware

[0685] Server: A high-performance computer system that receives data, pre-processes it, analyzes it, and outputs the results.

[0686] Terminal: A device where a user enters information and checks the results. This includes computers, smartphones, tablets, etc.

[0687] software

[0688] Generative AI Models: Artificial intelligence models built using machine learning frameworks such as TensorFlow and PyTorch.

[0689] Database Management System: A system for storing and managing information received from users, such as MySQL or PostgreSQL.

[0690] Web Application: Provides an interface for users to enter information. Uses web technologies such as HTML, CSS, and JavaScript.

[0691] Program Processing

[0692] User input of information

[0693] The user uses the terminal to input the insurance policy information and the details of the traffic accident, specifically, the following information:

[0694] Insurance contract information (e.g. type of insurance, premium)

[0695] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[0696] Receiving and preprocessing information by the server

[0697] The server receives the information sent by the user. The received information is stored in a database and pre-processed to format the data as necessary. For example, this includes standardizing the format of dates and times.

[0698] Input to the AI ​​model and analysis by the server

[0699] The server feeds the preprocessed information into a generative AI model, which generates a prompt like this:

[0700] Policy Information:

[0701] Insurance type: Comprehensive insurance

[0702] Insurance premium: 100,000 yen per year

[0703] Traffic accident details:

[0704] Location of accident: Shibuya Ward, Tokyo

[0705] Time of accident: October 1, 2023, 3:00 p.m.

[0706] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[0707] This prompt sentence is input into the AI ​​model and analysis begins.

[0708] Calculation of damages by the server

[0709] The generative AI model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[0710] Server output of results

[0711] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[0712] User review of results

[0713] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[0714] Examples

[0715] As a concrete example, consider the following scenario:

[0716] User A has automobile insurance, the type of insurance is "comprehensive insurance" and the premium is "100,000 yen per year."

[0717] User A is involved in a traffic accident. The location of the accident is "Shibuya Ward, Tokyo," the time of the accident is "October 1, 2023, 3:00 p.m.", and the circumstances of the parties involved are "The car driven by User A was hit by a car that ran a red light."

[0718] Based on this information, User A inputs the following prompt into the generative AI model:

[0719] Policy Information:

[0720] Insurance type: Comprehensive insurance

[0721] Insurance premium: 100,000 yen per year

[0722] Traffic accident details:

[0723] Location of accident: Shibuya Ward, Tokyo

[0724] Time of accident: October 1, 2023, 3:00 p.m.

[0725] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[0726] The server receives this prompt, calculates the amount of damages using the generative AI model, and outputs the result to the terminal of User A. For example, if the calculation result is "The amount of damages is 500,000 yen," User A can check the result.

[0727] The above is a specific embodiment for carrying out the present invention.

[0728] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0729] Step 1:

[0730] The user uses the device to enter the insurance policy information and the details of the traffic accident, using a dedicated web form or a mobile app to enter the following information:

[0731] Insurance contract information (e.g. type of insurance, premium)

[0732] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[0733] The entered information is transmitted from the terminal to the server.

[0734] Step 2:

[0735] The server receives the information sent by the user. The received information is stored in a database. After storage, pre-processing is performed to format the data. For example, this includes standardizing the format of the date and time.

[0736] Input: Insurance policy information and traffic accident details submitted by the user

[0737] Output: Preprocessed information

[0738] Step 3:

[0739] The server inputs the preprocessed information into a generative AI model, which generates a prompt sentence like this:

[0740] Policy Information:

[0741] Insurance type: Comprehensive insurance

[0742] Insurance premium: 100,000 yen per year

[0743] Traffic accident details:

[0744] Location of accident: Shibuya Ward, Tokyo

[0745] Time of accident: October 1, 2023, 3:00 p.m.

[0746] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[0747] This prompt sentence is input into the AI ​​model and analysis begins.

[0748] Input: Preprocessed information

[0749] Output: Prompt statement

[0750] Step 4:

[0751] The server analyzes the prompt sentence using a generative AI model. The AI ​​model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[0752] Input: Prompt statement

[0753] Output: Damages amount

[0754] Step 5:

[0755] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[0756] Input: Damages amount

[0757] Output: Damage amount result (text message and PDF file)

[0758] Step 6:

[0759] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[0760] Input: Damages amount result

[0761] Output: User review of results

[0762] (Application example 2)

[0763] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[0764] Conventional calculations of compensation for traffic accidents are often done manually, which takes time and effort and can be inaccurate. As autonomous vehicles become more widespread, there is a demand for a system that can calculate compensation in real time when an accident occurs. This will enable quick and accurate calculation of compensation, reducing the burden on insureds and related parties.

[0765] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0766] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting detailed information about the accident from a sensor and a camera mounted on the autonomous vehicle, a means for analyzing the collected information in real time, a means for calculating the amount of compensation based on the analysis result, and a means for outputting the calculation result. This makes it possible to calculate the amount of compensation quickly and accurately when an accident occurs.

[0767] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0768] The "Traffic Accident Compensation Standards" are the standards for calculating the amount of compensation in traffic accidents, and are set out in the "Red Book" and "Blue Book."

[0769] "Simplified determination" is a method of obtaining results quickly by simplifying complex calculations and procedures.

[0770] "Information regarding traffic accidents" refers to detailed data related to the accident, such as the location and time of the accident, and the circumstances of the parties involved.

[0771] "Amount of damages" refers to the amount of money paid for damages caused by a traffic accident.

[0772] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[0773] A "sensor" is a device that detects physical phenomena and outputs them as data.

[0774] A "camera" is a device that captures images or videos.

[0775] "Real-time" refers to processing and analysis at the exact moment an event occurs.

[0776] "Analysis" means examining data in detail to clarify its meaning and structure.

[0777] "Output" refers to displaying the results of a calculation or analysis or sending them to another system.

[0778] As an embodiment of the present invention, a system installed in an autonomous vehicle will be described as an example. This system calculates the amount of damages in real time when a traffic accident occurs.

[0779] First, autonomous vehicles are equipped with multiple sensors and cameras that are used to collect detailed information about accidents. Specifically, they obtain data in real time about the location and time of the accident, the circumstances of the people involved, and other information.

[0780] The acquired data is then sent to a computer system in the vehicle, which uses AI (Artificial Intelligence) to analyze the data and calculate the amount of damages. The AI ​​uses models to calculate the amount of damages based on the "Red Book" and "Blue Book".

[0781] The specific process is as follows: first, data obtained from sensors and cameras is input into a computer system. Next, AI analyzes the data and calculates the amount of damages. Finally, the calculation result is notified to the user via the vehicle's display or a smartphone application.

[0782] The hardware used includes sensors, cameras, and computer systems installed in the autonomous vehicle, while the software uses programming languages ​​such as Python to implement AI models and transmit and receive data using HTTP requests.

[0783] As a concrete example, the following prompt sentence can be input into a generative AI model to calculate the amount of damages:

[0784] "Insurance contract information: Comprehensive insurance, Insurance premium: 50,000 yen, Accident details: Location: Tokyo, Japan, Time: 2023-10-01 14:30:00, Parties involved: Vehicle A, Vehicle B"

[0785] Based on this prompt, the AI ​​model calculates the amount of compensation and notifies the user of the result, making it possible to calculate compensation quickly and accurately when an accident occurs.

[0786] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0787] Step 1:

[0788] Sensors and cameras in autonomous vehicles collect detailed information about the accident.

[0789] Input: Data such as the location and time of the accident, and the circumstances of the people involved.

[0790] Output: Collected accident details.

[0791] How it works: Sensors detect the location, speed, and strength of the impact, and cameras capture images of the accident scene. This data is sent to the vehicle's computer system.

[0792] Step 2:

[0793] A computer system within the vehicle receives the collected data and prepares it for analysis.

[0794] Input: Accident details sent from sensors and cameras.

[0795] Output: Data formatted for analysis.

[0796] Specific operations: Format the received data, extract the necessary information, and prepare it in a form suitable for analysis.

[0797] Step 3:

[0798] A computer system will input the data into an AI model to calculate damages.

[0799] Input: Formatted accident details.

[0800] Output: Calculated damages.

[0801] Specific operation: The formatted data is input into the AI ​​model, and the amount of damages is calculated based on the "red book" and "blue book." The AI ​​model is implemented in a programming language such as Python, and sends and receives data using HTTP requests.

[0802] Step 4:

[0803] The calculation results are notified to the user via the vehicle's display or smartphone application.

[0804] Input: Calculated damages.

[0805] Output: A damages notice displayed to the user.

[0806] Specific operation: The calculation results are sent to a display or smartphone application to be displayed in a format that is easy for users to understand. This allows users to quickly and accurately check the amount of compensation in the event of an accident.

[0807] In addition, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0808] "Example 1"

[0809] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[0810] "Example 2"

[0811] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[0812] The process flow of each embodiment will be described below.

[0813] "Example 1"

[0814] Step 1: The user enters information about a traffic accident into the system, including details of the accident, the condition of the victims, the extent of damage, etc.

[0815] Step 2: The emotion engine works to recognize emotions from the user's tone of voice, facial expressions, choice of words, etc. This emotion recognition is done from the tone of voice, facial expressions, choice of words, etc. when the user enters information.

[0816] Step 3: If the emotion recognized is a strong emotion such as anger or sadness, the amount of compensation will be calculated taking that emotion into account. Specifically, a certain amount will be added or multiplied to the amount of compensation depending on the strength and type of emotion.

[0817] Step 4: The calculated amount of compensation is presented to the user. At this time, the emotion engine's emotion recognition results and their impact are clearly indicated to ensure transparency to the user.

[0818] Example 1

[0819] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0820] Conventional traffic accident compensation standard judgment systems calculate the amount of compensation based on information about the traffic accident, but since they do not take into account the emotional damage of the user, it is difficult to calculate an appropriate amount of compensation. In addition, it can take time to read and analyze information about traffic accidents, which is insufficient in situations where a quick response is required.

[0821] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0822] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the user's emotions, and a means for adjusting the calculation of the amount of compensation based on the recognized emotions. This enables a more appropriate calculation of the amount of compensation that takes into account the emotional damage of the user.

[0823] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0824] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[0825] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[0826] "Information regarding traffic accidents" refers to detailed data related to accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[0827] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[0828] "User emotion" refers to a psychological state such as anger, sadness, or happiness felt by a user.

[0829] "Means for recognizing emotions" refers to technology for analyzing and recognizing emotions from a user's tone of voice, facial expressions, choice of words, etc.

[0830] A "damages adjustment measure" is a method for appropriately modifying or adjusting the amount of damages based on perceived feelings.

[0831] The present invention relates to a simplified determination system for traffic accident compensation standards, and in particular to a system for calculating the amount of compensation taking into account the user's emotions.

[0832] System Configuration

[0833] Hardware

[0834] Server: A server with high-performance computing power (e.g. a virtual server for cloud services)

[0835] Terminal: The device through which the user enters information (e.g. computer, smartphone)

[0836] Input devices: Microphone, camera (to recognize the user's tone of voice and facial expressions)

[0837] software

[0838] Database: A database for storing information about traffic accidents and compensation criteria (e.g. MySQL)

[0839] AI model: An AI model (e.g. TensorFlow) for analyzing traffic accident information and calculating compensation amounts.

[0840] Emotion recognition engine: Software for recognizing user emotions (e.g. Affectiva)

[0841] System Operation

[0842] 1. The user enters detailed information about a traffic accident, such as the location and time of the accident, and the circumstances of the people involved, into a web form.

[0843] Example: "Location of accident: Shibuya-ku, Tokyo, Time: 14:00 on October 1, 2023, Situation of the parties involved: Pedestrian hit by car."

[0844] 2. The device sends the entered information to the server. The device sends the data using an HTTP request.

[0845] 3. The server saves the received information in the database. The server executes an INSERT query in the MySQL database to save the information.

[0846] 4. The server passes the stored information to the AI ​​model for analysis. The server inputs the data into the TensorFlow model and performs the analysis.

[0847] 5. The server calculates the amount of damages based on the analysis results. The server refers to the "Red Book" and "Blue Book" databases to calculate the amount of damages.

[0848] 6. When a user enters information about a traffic accident, the emotion engine recognizes the user's emotion. For example, if the user says "I'm very sad," the emotion engine recognizes "sadness."

[0849] 7. The server receives emotion data from the emotion engine. The server receives the data from the emotion engine via an HTTP request.

[0850] 8. The server saves the emotion data and traffic accident information in the database. The server executes an INSERT query on the MySQL database to save the information.

[0851] 9. The server passes the stored information to the AI ​​model for analysis. The server inputs the data into the TensorFlow model and performs the analysis.

[0852] 10. The server calculates the amount of damages based on the analysis results and takes emotions into account. The server refers to the databases of the "Red Book" and "Blue Book" and calculates the amount of damages taking into account emotional data.

[0853] 11. The server sends the calculation result to the terminal. The server sends the data to the terminal using an HTTP response.

[0854] 12. The terminal displays the calculation result to the user. The terminal displays "Amount of damages: 5.5 million yen (emotions taken into consideration)" on the web page.

[0855] Examples of prompt statements

[0856] 1. Simplified Judgment System for Traffic Accident Compensation Standards

[0857] Prompt: "Please enter details about the traffic accident. For example, location, time, and circumstances of the accident."

[0858] 2. System combining emotion engines

[0859] Prompt: "Please enter information about the traffic accident and express your feelings. For example, location of the accident, time, situation of the people involved, and emotions (anger, sadness, etc.)."

[0860] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0861] Step 1:

[0862] The user enters detailed information about the traffic accident.

[0863] Input: Details of the accident, such as location, time, and circumstances of the people involved

[0864] Specific actions: A user enters the following information into a web form: "Accident location: Shibuya-ku, Tokyo, Time: 14:00 on October 1, 2023, Situation of the parties involved: Pedestrian hit by car."

[0865] Output: Detailed information about the traffic accidents entered

[0866] Step 2:

[0867] The terminal transmits the input information to the server.

[0868] Input: User-entered details of the traffic accident

[0869] Specific operation: The device sends data to the server using an HTTP request.

[0870] Output: Detailed information about the traffic accident sent to the server

[0871] Step 3:

[0872] The server stores the received information in a database.

[0873] Input: Traffic accident details sent from the device

[0874] What happens next: The server executes an INSERT query into the MySQL database to save the information.

[0875] Output: Detailed information about traffic accidents stored in a database

[0876] Step 4:

[0877] The server passes the stored information to the AI ​​model for analysis.

[0878] Input: Traffic accident details stored in the database

[0879] What happens: The server inputs the data into the TensorFlow model and performs the analysis.

[0880] Output: Analysis results (data necessary for calculating the amount of damages)

[0881] Step 5:

[0882] The server calculates the amount of compensation based on the analysis results.

[0883] Input: Analysis results from the AI ​​model

[0884] Specific operation: The server refers to the "Red Book" and "Blue Book" databases and calculates the amount of damages.

[0885] Output: Calculated damages

[0886] Step 6:

[0887] When a user enters information about a traffic accident, the emotion engine recognizes the user's emotions.

[0888] Input: User tone of voice, facial expressions, and language

[0889] What happens: If a user says "I'm so sad," the emotion engine recognizes "sad."

[0890] Output: Recognized emotion data

[0891] Step 7:

[0892] A server receives emotion data from an emotion engine.

[0893] Input: Sentiment data from the sentiment engine

[0894] Specific operation: The server receives data from the emotion engine via an HTTP request.

[0895] Output: Emotion data received by the server

[0896] Step 8:

[0897] The server stores the emotion data and traffic accident information in a database.

[0898] Input: Sentiment data and details of traffic accidents

[0899] What happens next: The server executes an INSERT query into the MySQL database to save the information.

[0900] Output: Emotion data and traffic accident information stored in a database

[0901] Step 9:

[0902] The server passes the stored information to the AI ​​model for analysis.

[0903] Input: Emotion data and traffic accident information stored in the database

[0904] What happens: The server inputs the data into the TensorFlow model and performs the analysis.

[0905] Output: Analysis results (data necessary for calculating damages taking emotions into account)

[0906] Step 10:

[0907] The server calculates the amount of damages based on the analysis results, taking emotions into account.

[0908] Input: Analysis results from the AI ​​model and emotion data

[0909] Specific operation: The server refers to the database of "Red Book" and "Blue Book" and calculates the amount of compensation by taking into account the emotional data.

[0910] Output: Calculated damages taking emotions into account

[0911] Step 11:

[0912] The server transmits the calculation result to the terminal.

[0913] Input: Calculated damages taking into account emotions

[0914] Specific operation: The server sends data to the device using an HTTP response.

[0915] Output: Damage amount sent to the terminal

[0916] Step 12:

[0917] The terminal displays the calculation results to the user.

[0918] Input: damages amount sent from server

[0919] Specific operation: The device displays the following on a web page: "Amount of damages: 5.5 million yen (emotions taken into consideration)."

[0920] Output: The damages displayed to the user.

[0921] (Application example 1)

[0922] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0923] When a traffic accident occurs, it is important to calculate the amount of compensation quickly and accurately. However, in conventional systems, it takes a lot of time and effort to manually input detailed information about the accident and calculate the amount of compensation. It is also difficult to take into account the emotional damage of the victim, making it difficult to calculate an appropriate amount of compensation. Furthermore, in the case of autonomous vehicles, it is required to collect information at the time of the accident and calculate the amount of compensation in real time. A new system is needed to solve these problems.

[0924] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0925] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the emotions of the passengers, a means for adjusting the amount of compensation based on the recognized emotions, and a means for being installed in the autonomous vehicle. This makes it possible to quickly and accurately calculate the amount of compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that takes into account the emotional damage of the victim.

[0926] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[0927] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[0928] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[0929] "Information regarding traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[0930] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[0931] "Passenger emotions" refers to the psychological state and feelings of passengers when they are involved in a traffic accident.

[0932] "Means of recognizing emotions" refers to technology that analyzes and recognizes emotions from passengers' tone of voice, facial expressions, language, etc.

[0933] An "autonomous vehicle" is a vehicle that can drive autonomously using artificial intelligence and sensor technology.

[0934] An "adjusting tool" is a method or technique for appropriately modifying damage awards based on perceived sentiment.

[0935] The system for carrying out this invention has the following configuration: The server includes a means for performing a simplified determination of traffic accident compensation standards using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing passenger emotions, a means for adjusting the amount of compensation based on the recognized emotions, and a means for being installed in the autonomous vehicle.

[0936] Program processing explanation

[0937] The server first collects information about the traffic accident, including details such as the location of the accident, time, vehicle speed, weather, etc. This information is obtained automatically from sensors, GPS and the vehicle's internal systems.

[0938] Next, to recognize passenger emotions, cameras and microphones installed in the vehicle are used. The camera captures the passenger's facial expressions, and the microphone collects the passenger's voice. These data are analyzed using software such as OpenCV and SpeechRecognition. The analyzed data is input into a deep learning model using Keras to recognize the passenger's emotions.

[0939] The recognized emotions and collected traffic accident information are input into an AI model for calculating the amount of compensation. The AI ​​model calculates the amount of compensation based on the traffic accident compensation standard. Furthermore, the amount of compensation is adjusted based on the recognized emotions.

[0940] Examples

[0941] For example, if the accident occurred in Tokyo, the vehicle speed was 60km / h, the weather was sunny, and the passengers expressed anger, the AI ​​model would use this information to calculate the compensation amount and adjust it to take into account the anger.

[0942] Examples of prompt statements

[0943] The accident occurred in Tokyo, the vehicle speed was 60km / h, and the weather was fine. The passengers showed angry emotions. Please calculate the amount of compensation based on this information.

[0944] In this way, it will be possible to quickly and accurately calculate compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that also takes into account the emotional damage suffered by the victim.

[0945] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0946] Step 1:

[0947] The server collects information about traffic accidents, including details such as the location and time of the accident, the vehicle's speed, and weather, automatically obtained from sensors, GPS, and the vehicle's internal systems. This information is then stored in a database.

[0948] Inputs: Data from sensors, GPS, and vehicle internal systems

[0949] Output: Detailed information about traffic accidents (location, time, speed, weather)

[0950] Step 2:

[0951] The server recognizes passengers' emotions using cameras and microphones installed in the vehicle. The camera captures the passengers' facial expressions, and the microphone collects the passengers' voices. These data are analyzed using software such as OpenCV and SpeechRecognition. The analyzed data is input into a deep learning model using Keras to recognize the passengers' emotions.

[0952] Input: Camera video, microphone audio

[0953] Output: Passenger sentiment data

[0954] Step 3:

[0955] The server inputs the recognized emotions and collected traffic accident information into an AI model for calculating the amount of compensation, which calculates the amount of compensation based on the traffic accident compensation standard.

[0956] Input: Traffic accident details, passenger emotion data

[0957] Output: Initial damages amount

[0958] Step 4:

[0959] The server adjusts the damage amount based on the recognized emotion, for example, if the passenger shows emotion of anger, it increases the damage amount to take the emotional damage into account.

[0960] Input: Initial damage amount, passenger emotion data

[0961] Output: Adjusted damages

[0962] Step 5:

[0963] The server outputs the final amount of damages and notifies the user via the vehicle's display or smartphone app.

[0964] Input: Adjusted damages amount

[0965] Output:Notification to the user

[0966] In this way, it will be possible to quickly and accurately calculate compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that also takes into account the emotional damage suffered by the victim.

[0967] Example 2

[0968] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0969] Conventional traffic accident compensation calculation systems have the problem that they are unable to take into account the emotional damage of the user, making it difficult to calculate an appropriate amount of compensation. In addition, inputting information about traffic accidents is cumbersome, making the system difficult to use for users.

[0970] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0971] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the user's emotions, and a means for adjusting the amount of compensation based on the recognized emotions. This makes it possible to calculate an appropriate amount of compensation taking into account the emotional damage of the user.

[0972] The "means for simplified determination of traffic accident compensation standards using AI" is a function that uses artificial intelligence technology to quickly and easily determine the standard for compensation amounts in traffic accidents.

[0973] "Means of reading information related to traffic accidents" refers to a function for inputting detailed information about traffic accidents (such as the location and time of the accident, the circumstances of the parties involved, etc.) into the system and importing it as data.

[0974] The "means for calculating the amount of compensation based on the loaded information" is a function for calculating the amount of compensation based on the loaded traffic accident information.

[0975] The "means for recognizing the user's emotions" is a function for detecting and recognizing the emotions of the user from the user's tone of voice, facial expressions, choice of words, etc.

[0976] The "means for adjusting the amount of damages based on the recognized emotion" is a function for appropriately adjusting the amount of damages taking into account the recognized emotion of the user.

[0977] This invention is a system for automobile insurance policyholders, where the user inputs their insurance contract information and detailed information about the traffic accident, and the AI ​​analyzes this information and calculates the amount of compensation. In addition, by combining it with an emotion engine that recognizes the user's emotions, it becomes possible to calculate the amount of compensation that takes emotional damage into account.

[0978] Hardware and Software Used

[0979] 1. Server

[0980] The server receives the information sent by the user and analyzes it using an AI model. The server is equipped with an AI model implemented in Python, and has the function of calculating the amount of damages based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards."

[0981] 2. Terminal

[0982] The terminal provides an interface for the user to input information. The terminal has a communication function for transmitting the input information to the server. The communication is performed using the HTTPS protocol, and the data is encrypted.

[0983] 3. Emotion Engine

[0984] The emotion engine is software for recognizing emotions from a user's tone of voice, facial expressions, language, etc. The emotion engine is built using TensorFlow and analyzes the user's emotions in real time.

[0985] Examples

[0986] For example, if a user enters the following information:

[0987] Insurance contract information: Type of insurance is "Comprehensive insurance", premium is "100,000 yen per year"

[0988] Traffic accident details: The accident occurred in "Shibuya Ward, Tokyo," the time was "3:00 p.m.", and the circumstances of the parties involved were "the other party ran a red light."

[0989] With this information, the server uses an AI model to calculate damages, and if the emotion engine detects that the user is feeling a strong sense of anger while typing, it will adjust the damages amount to take that emotion into account.

[0990] Examples of prompt statements

[0991] Here is an example of a prompt to be input to the generative AI model:

[0992] Use your insurance policy information and the details of the traffic accident to help us calculate your damages. Use the following information:

[0993] Insurance type: Comprehensive insurance

[0994] Insurance premium: 100,000 yen per year

[0995] Location of accident: Shibuya Ward, Tokyo

[0996] Time of accident: 3 p.m.

[0997] Situation of the parties involved: The other party ignored the traffic signal.

[0998] Also consider that the user's emotion is "anger."

[0999] Using this prompt, the generative AI model can calculate the amount of damages based on the necessary information and output a result that takes emotions into account.

[1000] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1001] Step 1:

[1002] The user enters information

[1003] The user inputs their own insurance contract information (type of insurance, premium, etc.) and detailed information about the traffic accident (location of the accident, time, circumstances of the parties involved, etc.) into an input form on the device. For example, the user inputs information such as "comprehensive insurance," "100,000 yen per year," "Shibuya-ku, Tokyo," "3:00 p.m.," and "the other party ran a red light." The input information is temporarily stored in the device's memory.

[1004] Step 2:

[1005] The device sends information

[1006] The terminal sends the insurance policy information and traffic accident details entered by the user to the server using the HTTPS protocol and the data is encrypted. The input data is converted to JSON format and sent to the server's API endpoint.

[1007] Step 3:

[1008] The server receives the information

[1009] The server receives the insurance contract information and the detailed information of the traffic accident sent from the terminal. The received data is stored in a database. Specifically, the server parses the received JSON data and stores each field in the corresponding column of the database.

[1010] Step 4:

[1011] The server analyzes the information

[1012] The server inputs the received information into the AI ​​model and begins analysis. Specifically, the AI ​​model implemented in Python calculates the amount of compensation based on the "Red Book" "Civil Traffic Accident Lawsuit Damage Compensation Calculation Standards" and the "Blue Book" "Traffic Accident Damage Calculation Standards." For example, the AI ​​model analyzes information such as "comprehensive insurance," "100,000 yen per year," "Shibuya Ward, Tokyo," "3:00 p.m.," and "other party ignored a traffic signal" to calculate the initial amount of compensation. The calculation results are temporarily stored in memory.

[1013] Step 5:

[1014] Emotion engine recognizes user emotions

[1015] When a user inputs information, the emotion engine recognizes emotions from the user's tone of voice, facial expressions, and language. For example, if a user feels strong anger while inputting information, the emotion engine recognizes that emotion. The emotion engine is built using TensorFlow and analyzes emotions in real time. The recognized emotion data is sent to the server.

[1016] Step 6:

[1017] The server adjusts the damage amount based on emotions.

[1018] The server adjusts the amount of damages based on the emotion recognition results from the emotion engine. For example, if the user feels strong anger, the amount of damages is increased taking that emotion into account. Specifically, a correction value that takes into account the influence of the emotion is applied to the initial amount of damages to calculate the final amount of damages. The adjusted amount of damages is stored in the database.

[1019] Step 7:

[1020] The server outputs the results

[1021] The server outputs the final calculated amount of damages to the user. The result is displayed on the terminal screen and sent to the user's email address. For example, a result such as "The final amount of damages is 1 million yen" may be displayed. The output data is generated in HTML format and sent to the user's terminal.

[1022] (Application example 2)

[1023] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1024] Conventional traffic accident compensation calculation systems calculate compensation amounts based on detailed information about the accident, but are unable to take into account the emotional damage suffered by passengers. Therefore, there is a need for a more appropriate compensation calculation method that includes emotional damage. There is also a need for a system that can calculate compensation amounts in real time when an accident occurs.

[1025] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1026] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for analyzing data obtained from the vehicle's sensors and cameras, and a means for taking into account the emotional state of the occupants using an emotion engine that recognizes their emotions. This makes it possible to calculate the amount of compensation in real time when an accident occurs, and to calculate a more appropriate amount of compensation that also takes into account emotional damage.

[1027] "AI" stands for artificial intelligence, a technology that allows computers to mimic human intelligence to learn, reason, and self-correct.

[1028] The "Traffic Accident Compensation Standards" are the standards for calculating the amount of compensation in traffic accidents, and specifically refer to the standards set out in the "Red Book" and "Blue Book."

[1029] "Information on traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[1030] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[1031] A "sensor" is a device that detects a physical phenomenon and converts it into an electrical signal.

[1032] A "camera" is a device that converts light into electrical signals to record images or videos.

[1033] An "emotion engine" is a technology that recognizes emotions from a user's tone of voice, facial expressions, choice of words, etc., and analyzes their emotional state.

[1034] "Emotional state" refers to the type and intensity of emotion a user is feeling.

[1035] A "system" refers to a collection of devices or programs in which multiple elements function in conjunction with each other.

[1036] The system for carrying out this invention is configured as follows: The server includes a means for performing a simplified determination of traffic accident compensation standards using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for analyzing data obtained from the vehicle's sensors and cameras, and a means for taking into account the emotional state of the occupants using an emotion engine that recognizes their emotions.

[1037] Program processing explanation

[1038] The server first receives real-time data from vehicle sensors and cameras, including information on the location and time of the accident, vehicle speed, impact force, etc. The server then analyzes this data to generate detailed information about the traffic accident.

[1039] The server then uses an emotion engine to analyze the passenger's tone of voice and facial expressions captured by the vehicle's microphones and cameras to recognize the passenger's emotional state. The emotion engine uses software called EmotionRecognizer to identify the passenger's emotions.

[1040] The server then calculates the amount of compensation based on the traffic accident compensation standard. Specifically, the AI ​​calculates the amount of compensation using the standards set out in the "Red Book" and "Blue Book." In addition, it adjusts the final amount of compensation by taking into account the perceived emotional state.

[1041] Examples

[1042] For example, if the accident occurred in Tokyo, the time of the accident was 14:30 on October 1, 2023, the vehicle speed was 60 km / h, and the impact force was 500 N, the server would calculate the amount of compensation based on this information. Also, if the passenger is feeling angry, the emotion engine would recognize that emotion and reflect it in the amount of compensation.

[1043] Examples of prompt statements

[1044] Below are examples of prompts to be input to the generative AI model.

[1045] The accident location is Tokyo, and the accident time is October 1, 2023 at 14:30. The vehicle speed is 60 km / h, and the impact force is 500 N. The occupants feel angry. Based on this information, please calculate the amount of damages.

[1046] In this way, the server can calculate compensation in real time, taking into account the details of the accident and the emotional state of the occupants.

[1047] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1048] Step 1:

[1049] The server receives data from vehicle sensors and cameras in real time. As input, it receives information such as the location and time of the accident, the vehicle speed, and the impact force, and analyzes this data to generate detailed information about the traffic accident. As output, it obtains the analyzed detailed information about the traffic accident.

[1050] Step 2:

[1051] The server uses the emotion engine to analyze the passenger's tone of voice and facial expressions captured by the in-car microphones and cameras. As input, it receives audio and video data and identifies the passenger's emotions using software called EmotionRecognizer. As output, it gets the recognized emotional state.

[1052] Step 3:

[1053] The server calculates the amount of compensation based on the traffic accident compensation standard. As input, it receives the detailed information of the traffic accident obtained in step 1 and the emotional state obtained in step 2, and the AI ​​calculates the amount of compensation using the standards described in the "Red Book" and "Blue Book". As output, it obtains the calculated amount of compensation.

[1054] Step 4:

[1055] The server adjusts the final damages amount taking into account the perceived emotional state. As input, it takes the damages amount calculated in step 3 and the perceived emotional state in step 2, and calculates the final damages amount that reflects the emotional damage. As output, it gets the adjusted final damages amount.

[1056] Step 5:

[1057] The server notifies the user of the final amount of damages. As input, it receives the final amount of damages obtained in step 4 and sends a notification to the user's terminal. As output, it obtains the amount of damages notified to the user.

[1058] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input on the result of the specific processing.

[1059] The unit 46A transmits voice data representing the user input captured by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 captures the voice data.

[1060] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1061] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1062] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1063] [Third embodiment]

[1064] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1065] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1066] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1067] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1068] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1069] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1070] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1071] Fig. 6 shows an example of main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1072] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1073] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1074] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1075] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1076] "Example 1"

[1077] One embodiment of the present invention is a simplified system for determining standards for compensation for traffic accident damages using AI. This system is equipped with a means for reading information about traffic accidents and a means for calculating the amount of compensation for damages based on the read information. Specifically, the system receives detailed information about the traffic accident (such as the location and time of the accident, and the circumstances of the parties involved) as input, and the AI ​​analyzes this information. The system then calculates the amount of compensation for damages based on the "Red Book" "Standards for Calculating Compensation for Civil Traffic Accident Lawsuits" and the "Blue Book" "Standards for Calculating Compensation for Traffic Accident Damages," and outputs the results.

[1078] "Example 2"

[1079] Another embodiment of the present invention is a system targeted at voluntary automobile insurance subscribers. In this system, the subscriber inputs his / her insurance contract information and detailed information about the traffic accident, and AI analyzes this information and calculates the amount of damages. Specifically, the subscriber inputs his / her insurance contract information (type of insurance, insurance premium, etc.) and detailed information about the traffic accident (location of the accident, time, status of the parties involved, etc.), and AI analyzes this information. Then, the AI ​​calculates the amount of damages based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards," and outputs the results.

[1080] The process flow of each embodiment will be described below.

[1081] "Example 1"

[1082] Step 1: The user enters detailed information about the traffic accident (location, time of the accident, circumstances of the parties involved, etc.) into the system.

[1083] Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[1084] Step 3: The calculated amount of damages is output to the user.

[1085] "Example 2"

[1086] Step 1: A voluntary automobile insurance policyholder enters their insurance contract information (type of insurance, premium, etc.) and detailed information about the traffic accident (location of the accident, time, circumstances of the parties involved, etc.) into the system. Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[1087] Step 3: The calculated amount of damages is output to the subscriber.

[1088] Example 1

[1089] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1090] Calculating compensation for traffic accidents requires specialized knowledge and is time-consuming and laborious. In addition, the calculation standards for compensation are complex, making it difficult for general users to easily understand and apply. For this reason, there is a demand for a system that can calculate compensation quickly and accurately.

[1091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1092] In this invention, the server includes a means for inputting detailed information about a traffic accident, a means for transmitting the input information to the server, a means for the server to analyze the information received, a means for the server to calculate the amount of compensation using the generative AI model, a means for transmitting the calculation result to the terminal, and a means for the terminal to display the calculation result to the user. This allows the user to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation.

[1093] "Detailed information about the traffic accident" is specific information related to the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[1094] "Input means" refers to an interface or device that allows a user to input detailed information about a traffic accident.

[1095] A "server" is a computer system that receives information sent by users, analyzes it, and calculates the amount of damages.

[1096] The "transmitting means" refers to a communication means for transmitting information from the terminal to the server.

[1097] "Means of analysis" refers to software or algorithms used by the server to process the information it receives and check its consistency.

[1098] A "generative AI model" is an artificial intelligence model trained to calculate compensation amounts for traffic accidents.

[1099] A “means for calculating” is a process or algorithm for calculating damages using a generative AI model.

[1100] A "terminal" is a device through which a user inputs information and checks the results of calculations.

[1101] The "display means" refers to an interface for visually presenting to the user the calculation results that the terminal receives from the server.

[1102] The present invention is a system for quickly and accurately calculating the amount of compensation for damages in a traffic accident. A specific embodiment of this system will be described below.

[1103] First, the user uses the terminal to input detailed information about a traffic accident. The input form includes items such as the location of the accident, the time of the accident, the circumstances of the people involved, etc. For example, the user inputs information according to the following prompts:

[1104] "Where did the accident occur?"

[1105] "What time did the accident occur?"

[1106] Please tell us the situation of the parties involved.

[1107] The information entered by the user is sent from the terminal to the server, which then sends the information to the server in an appropriate format (e.g., JSON format).

[1108] The server analyzes the information it receives, which may include checking the integrity of the information and pre-processing it, such as making sure the time of occurrence is not in the future and that the location is a valid place name.

[1109] The server then uses a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information and calculates the amount of compensation based on past traffic accident data and standards.

[1110] The calculation result is sent from the server to the terminal. The terminal displays the received calculation result to the user. The user can check the amount of compensation displayed on the terminal screen. For example, a result such as "The amount of compensation is 5 million yen" may be displayed.

[1111] This system allows users to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation. The hardware used includes the user's terminal (PC, smartphone, etc.) and the server. The software includes the input form, communication protocol, analysis algorithm, and generative AI model.

[1112] As a concrete example, if the user enters the following information:

[1113] Location of accident: Shinjuku Ward, Tokyo

[1114] Time of accident: October 1, 2023, 14:30

[1115] Situation of the parties involved: Vehicle A runs a red light and crashes into vehicle B.

[1116] The server receives this information and performs analysis using the generative AI model. As a result of the analysis, the amount of compensation is calculated and a result such as "The amount of compensation is 5 million yen" is displayed on the terminal.

[1117] In this way, users can easily check the amount of compensation by simply entering detailed information about a traffic accident.

[1118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1119] Step 1:

[1120] The user enters detailed information about the traffic accident.

[1121] The user inputs information such as the location and time of the accident, and the status of the people involved into the input form on the terminal. For example, the user inputs information following prompts such as "Where did the accident occur?", "What time did the accident occur?", and "Please tell us the status of the people involved." The input information is temporarily stored in the terminal's memory.

[1122] Step 2:

[1123] The terminal transmits the input information to the server.

[1124] The terminal sends the information entered by the user to the server in an appropriate format (for example, JSON format). The data sent includes the location of the accident, the time of the accident, the status of the people involved, etc. For example, the following JSON data is sent:

[1125] json

[1126] {

[1127] "location": "Shinjuku-ku, Tokyo",

[1128] "time": "2023-10-01T14:30:00",

[1129] "details": "Vehicle A runs a red light and collides with vehicle B"

[1130] }

[1131] Step 3:

[1132] The server analyzes the information it receives.

[1133] The server receives the JSON data sent from the terminal and begins analyzing it. The analysis includes checking the consistency of the information and preprocessing. For example, it checks whether the time of occurrence is a future date, whether the location is a valid place name, etc. As a result of the analysis, data with confirmed consistency is generated.

[1134] Step 4:

[1135] The server uses the generative AI model to calculate damages.

[1136] The server inputs the analyzed information into a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information based on past traffic accident data and standards, and calculates the amount of compensation. The amount of compensation is generated as a calculation result.

[1137] Step 5:

[1138] The server transmits the calculation result to the terminal.

[1139] The server sends the calculated amount of damages to the terminal in an appropriate format (for example, JSON format). The data sent includes details of the amount of damages. For example, the following JSON data is sent:

[1140] json

[1141] {

[1142] "compensation_amount": 5000000,

[1143] "details": "The damages amount to 5 million yen."

[1144] }

[1145] Step 6:

[1146] The terminal displays the calculation results to the user.

[1147] The terminal displays the calculation results received from the server to the user. The user can check the amount of damages displayed on the terminal screen. For example, the result "The amount of damages is 5 million yen" may be displayed.

[1148] (Application example 1)

[1149] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1150] When a traffic accident occurs, it is important for both the victim and the at-fault party to calculate the amount of compensation quickly and accurately. However, the conventional method requires manually collecting detailed information about the accident and having experts analyze it before calculating the amount of compensation, which is time-consuming and labor-intensive. In addition, as autonomous vehicles become more widespread, there is a demand for a system that can respond immediately when an accident occurs.

[1151] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting accident information from the sensor or camera of the autonomous vehicle, a means for analyzing the collected information and calculating the amount of compensation, a means for calculating the amount of compensation using a generative AI model, and a means for generating a prompt sentence and inputting it into the AI ​​model. This makes it possible to quickly and accurately calculate the amount of compensation when a traffic accident occurs.

[1152] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[1153] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[1154] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[1155] "Information regarding traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[1156] "Amount of damages" refers to the amount of money paid to a victim for damages suffered in a traffic accident.

[1157] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[1158] A "sensor" is a device that detects physical phenomena and outputs them as data.

[1159] A "camera" is a device that captures images or videos.

[1160] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[1161] A "prompt" is an instruction to be input to a generative AI model, which serves as a guideline for the model to generate appropriate output.

[1162] The system for carrying out the present invention is for quickly and accurately calculating the amount of compensation for damages when a traffic accident occurs. A specific embodiment of this system will be described below.

[1163] The system includes a means of collecting accident information from sensors and cameras installed in the autonomous vehicle, which allows detailed data such as the location and time of the accident, as well as the circumstances of the people involved, to be collected in real time. The collected data is then sent to a computer in the vehicle where it undergoes initial processing.

[1164] Then, the initially processed data is sent to a server. The server uses a generative AI model to analyze the collected accident information. Specifically, the server includes the following means:

[1165] 1. A means of reading information about traffic accidents: Read data collected from sensors and cameras to obtain detailed information about accidents.

[1166] 2. Method of calculating damages: Based on the information read in, the generative AI model calculates the amount of damages. The calculation is based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards."

[1167] 3. A means for generating prompt sentences and inputting them into the AI ​​model: A prompt sentence is generated based on the accident information and input into the generative AI model.

[1168] For example, the following prompt would be generated:

[1169] A traffic accident has occurred. Details of the accident are as follows:

[1170] Location: Tokyo, Japan

[1171] Occurrence time: 2023-10-01T12:34:56

[1172] Status of the parties: Driver A (Injured), Driver B (Uninjured)

[1173] Vehicle Damage: Severe

[1174] Use this information to assess your damages.

[1175] The server inputs this prompt into a generative AI model to calculate the amount of damages, and the calculation result is notified to the user via an in-vehicle display or a smartphone application.

[1176] This system will enable the prompt and accurate calculation of compensation when a traffic accident occurs, enabling a prompt response for both the victim and the at-fault party. In addition, as autonomous vehicles become more widespread, the response to accidents will be automated, further improving safety and efficiency.

[1177] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1178] Step 1:

[1179] Sensors and cameras in autonomous vehicles detect the occurrence of a traffic accident. The sensors collect impact and location information, and the cameras capture video of the accident scene. These data are sent to a computer in the vehicle. The input is data from the sensors and cameras, and the output is initially processed accident information.

[1180] Step 2:

[1181] An in-vehicle computer performs initial processing of the collected data, analyzing impact data and location information from sensors and extracting accident details from camera footage. The input is raw data from sensors and cameras, and the output is analyzed accident details.

[1182] Step 3:

[1183] The initial processed accident information is sent to the server. The server receives this information and stores it in a database. The input is the accident details sent from the computer in the vehicle, and the output is the accident information stored in the database.

[1184] Step 4:

[1185] The server generates a prompt sentence based on the stored accident information. Specifically, it converts information such as the location and time of the accident, and the situation of the people involved into text format. The input is the accident information stored in the database, and the output is the generated prompt sentence.

[1186] Step 5:

[1187] The server inputs the generated prompt sentence into the generative AI model. The generative AI model analyzes the prompt sentence and calculates the amount of damages. The input is the generated prompt sentence, and the output is the calculated amount of damages.

[1188] Step 6:

[1189] The server notifies the user of the calculated amount of compensation through the display in the vehicle or a smartphone application. The input is the calculated amount of compensation, and the output is the amount of compensation notified to the user.

[1190] Step 7:

[1191] The user checks the notified amount of damages and contacts the insurance company or relevant organizations if necessary. The input is the notified amount of damages, and the output is the user's confirmation and contact.

[1192] Example 2

[1193] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1194] Conventional calculations of compensation for traffic accidents require manual work by people with specialized knowledge, which is time-consuming and labor-intensive. In addition, the calculation standards for compensation can be complex, making accurate calculations difficult. Furthermore, there was a lack of a way for users to easily input their own insurance contract information and detailed information about the accident and quickly find out the amount of compensation.

[1195] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1196] In this invention, the server includes a means for a user to input insurance contract information and detailed information about a traffic accident, a means for the server to receive the input information and perform preprocessing, a means for the server to input the preprocessed information into a generative AI model and perform analysis, a means for the server to calculate the amount of damages based on the analysis result, a means for the server to output the calculation result to the user's terminal, and a means for the user to check the result on the terminal. This allows the user to easily input information and quickly and accurately know the amount of damages.

[1197] A "user" is an individual or legal entity that utilizes the system to input insurance policy information and detailed information about a traffic accident.

[1198] "Insurance contract information" is detailed information about insurance, such as the type of insurance the user has subscribed to and the insurance premiums.

[1199] "Detailed information about the traffic accident" is specific information about the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[1200] A “server” is a computer system that receives information input by a user, performs preprocessing, and analyzes it using a generative AI model.

[1201] "Preprocessing" refers to processing the data received to format it and make it suitable for analysis.

[1202] A "generative AI model" is an artificial intelligence model built using a machine learning framework to analyze input information and calculate the amount of damages.

[1203] "Analysis" is the process in which the generative AI model performs calculations and inferences based on the input information to determine the amount of damages.

[1204] "Amount of damages" means the amount to be paid for damages in a traffic accident.

[1205] A "terminal" is a device that a user uses to enter information and view results from a server.

[1206] The “results” are information on the amount of damages calculated by the generative AI model.

[1207] This invention is a system in which a user inputs insurance contract information and detailed information about a traffic accident, and a server analyzes this information to calculate the amount of compensation. A specific embodiment of this system will be described below.

[1208] Hardware and Software Used

[1209] Hardware

[1210] Server: A high-performance computer system that receives data, pre-processes it, analyzes it, and outputs the results.

[1211] Terminal: A device where a user enters information and checks the results. This includes computers, smartphones, tablets, etc.

[1212] software

[1213] Generative AI Models: Artificial intelligence models built using machine learning frameworks such as TensorFlow and PyTorch.

[1214] Database Management System: A system for storing and managing information received from users, such as MySQL or PostgreSQL.

[1215] Web Application: Provides an interface for users to enter information. Uses web technologies such as HTML, CSS, and JavaScript.

[1216] Program Processing

[1217] User input of information

[1218] The user uses the terminal to input the insurance policy information and the details of the traffic accident, specifically, the following information:

[1219] Insurance contract information (e.g. type of insurance, premium)

[1220] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[1221] Receiving and preprocessing information by the server

[1222] The server receives the information sent by the user. The received information is stored in a database and pre-processed to format the data as necessary. For example, this includes standardizing the format of dates and times.

[1223] Input to the AI ​​model and analysis by the server

[1224] The server feeds the preprocessed information into a generative AI model, which generates a prompt like this:

[1225] Policy Information:

[1226] Insurance type: Comprehensive insurance

[1227] Insurance premium: 100,000 yen per year

[1228] Traffic accident details:

[1229] Location of accident: Shibuya Ward, Tokyo

[1230] Time of accident: October 1, 2023, 3:00 p.m.

[1231] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[1232] This prompt sentence is input into the AI ​​model and analysis begins.

[1233] Calculation of damages by the server

[1234] The generative AI model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[1235] Server output of results

[1236] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[1237] User review of results

[1238] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[1239] Examples

[1240] As a concrete example, consider the following scenario:

[1241] User A has automobile insurance, the type of insurance is "comprehensive insurance" and the premium is "100,000 yen per year."

[1242] User A is involved in a traffic accident. The location of the accident is "Shibuya Ward, Tokyo," the time of the accident is "October 1, 2023 at 3:00 p.m.", and the circumstances of the parties involved are "The car driven by User A was hit by a car that ran a red light."

[1243] Based on this information, User A inputs the following prompt into the generative AI model:

[1244] Policy Information:

[1245] Insurance type: Comprehensive insurance

[1246] Insurance premium: 100,000 yen per year

[1247] Traffic accident details:

[1248] Location of accident: Shibuya Ward, Tokyo

[1249] Time of accident: October 1, 2023, 3:00 p.m.

[1250] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[1251] The server receives this prompt, calculates the amount of compensation using the generative AI model, and outputs the result to the terminal of User A. For example, if the calculation result is "The amount of compensation is 500,000 yen," User A can check the result.

[1252] The above is a specific embodiment for carrying out the present invention.

[1253] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1254] Step 1:

[1255] The user uses the device to enter the insurance policy information and the details of the traffic accident, using a dedicated web form or a mobile app to enter the following information:

[1256] Insurance contract information (e.g. type of insurance, premium)

[1257] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[1258] The entered information is transmitted from the terminal to the server.

[1259] Step 2:

[1260] The server receives the information sent by the user. The received information is stored in a database. After storage, pre-processing is performed to format the data. For example, this includes standardizing the format of the date and time.

[1261] Input: Insurance policy information and traffic accident details submitted by the user

[1262] Output: Preprocessed information

[1263] Step 3:

[1264] The server inputs the preprocessed information into a generative AI model, which generates a prompt sentence like this:

[1265] Policy Information:

[1266] Insurance type: Comprehensive insurance

[1267] Insurance premium: 100,000 yen per year

[1268] Traffic accident details:

[1269] Location of accident: Shibuya Ward, Tokyo

[1270] Time of accident: October 1, 2023, 3:00 p.m.

[1271] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[1272] This prompt sentence is input into the AI ​​model and analysis begins.

[1273] Input: Preprocessed information

[1274] Output: Prompt statement

[1275] Step 4:

[1276] The server analyzes the prompt sentence using a generative AI model. The AI ​​model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[1277] Input: Prompt statement

[1278] Output: Damages amount

[1279] Step 5:

[1280] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[1281] Input: Damages amount

[1282] Output: Damage amount result (text message and PDF file)

[1283] Step 6:

[1284] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[1285] Input: Damages result

[1286] Output: User review of results

[1287] (Application example 2)

[1288] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1289] Conventional calculations of compensation for traffic accidents are often done manually, which takes time and effort and can be inaccurate. As autonomous vehicles become more widespread, there is a demand for a system that can calculate compensation in real time when an accident occurs. This will enable quick and accurate calculation of compensation, reducing the burden on insureds and related parties.

[1290] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1291] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting detailed information about the accident from a sensor and a camera mounted on the autonomous vehicle, a means for analyzing the collected information in real time, a means for calculating the amount of compensation based on the analysis result, and a means for outputting the calculation result. This makes it possible to calculate the amount of compensation quickly and accurately when an accident occurs.

[1292] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[1293] The "Traffic Accident Compensation Standards" are the standards for calculating the amount of compensation in traffic accidents, and are set out in the "Red Book" and "Blue Book."

[1294] "Simplified determination" is a method of obtaining results quickly by simplifying complex calculations and procedures.

[1295] "Information regarding traffic accidents" refers to detailed data related to the accident, such as the location and time of the accident, and the circumstances of the parties involved.

[1296] "Amount of damages" refers to the amount of money paid for damages caused by a traffic accident.

[1297] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[1298] A "sensor" is a device that detects physical phenomena and outputs them as data.

[1299] A "camera" is a device that captures images or videos.

[1300] "Real-time" refers to processing and analysis at the exact moment an event occurs.

[1301] "Analysis" means examining data in detail to clarify its meaning and structure.

[1302] "Output" refers to displaying the results of a calculation or analysis or sending them to another system.

[1303] As an embodiment of the present invention, a system installed in an autonomous vehicle will be described as an example. This system calculates the amount of damages in real time when a traffic accident occurs.

[1304] First, autonomous vehicles are equipped with multiple sensors and cameras that are used to collect detailed information about accidents. Specifically, they obtain data in real time about the location and time of the accident, the circumstances of the people involved, and other information.

[1305] The acquired data is then sent to a computer system in the vehicle, which uses AI (Artificial Intelligence) to analyze the data and calculate the amount of damages. The AI ​​uses models to calculate the amount of damages based on the "Red Book" and "Blue Book".

[1306] The specific process is as follows: first, data obtained from sensors and cameras is input into a computer system. Next, AI analyzes the data and calculates the amount of damages. Finally, the calculation result is notified to the user via the vehicle's display or a smartphone application.

[1307] The hardware used includes sensors, cameras, and computer systems installed in the autonomous vehicle, while the software uses programming languages ​​such as Python to implement AI models and transmit and receive data using HTTP requests.

[1308] As a concrete example, the following prompt sentence can be input into a generative AI model to calculate the amount of damages:

[1309] "Insurance contract information: Comprehensive insurance, Insurance premium: 50,000 yen, Accident details: Location: Tokyo, Japan, Time: 2023-10-01 14:30:00, Parties involved: Vehicle A, Vehicle B"

[1310] Based on this prompt, the AI ​​model calculates the amount of compensation and notifies the user of the result, making it possible to calculate compensation quickly and accurately when an accident occurs.

[1311] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1312] Step 1:

[1313] Sensors and cameras in autonomous vehicles collect detailed information about the accident.

[1314] Input: Data such as the location and time of the accident, and the circumstances of the people involved.

[1315] Output: Collected accident details.

[1316] How it works: Sensors detect the location, speed, and strength of the impact, and cameras capture images of the accident scene. This data is sent to the vehicle's computer system.

[1317] Step 2:

[1318] A computer system within the vehicle receives the collected data and prepares it for analysis.

[1319] Input: Accident details sent from sensors and cameras.

[1320] Output: Data formatted for analysis.

[1321] Specific operations: Format the received data, extract the necessary information, and prepare it in a form suitable for analysis.

[1322] Step 3:

[1323] A computer system will input the data into an AI model to calculate damages.

[1324] Input: Formatted accident details.

[1325] Output: Calculated damages.

[1326] Specific operation: The formatted data is input into the AI ​​model, and the amount of damages is calculated based on the "red book" and "blue book." The AI ​​model is implemented in a programming language such as Python, and sends and receives data using HTTP requests.

[1327] Step 4:

[1328] The calculation results are notified to the user via the vehicle's display or smartphone application.

[1329] Input: Calculated damages.

[1330] Output: A damages notice displayed to the user.

[1331] Specific operation: The calculation results are sent to a display or smartphone application to be displayed in a format that is easy for users to understand. This allows users to quickly and accurately check the amount of compensation in the event of an accident.

[1332] In addition, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1333] "Example 1"

[1334] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[1335] "Example 2"

[1336] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[1337] The process flow of each embodiment will be described below.

[1338] "Example 1"

[1339] Step 1: The user enters information about a traffic accident into the system, including details of the accident, the condition of the victims, the extent of damage, etc.

[1340] Step 2: The emotion engine works to recognize emotions from the user's tone of voice, facial expressions, choice of words, etc. This emotion recognition is done from the tone of voice, facial expressions, choice of words, etc. when the user enters information.

[1341] Step 3: If the emotion recognized is a strong emotion such as anger or sadness, the amount of compensation will be calculated taking that emotion into account. Specifically, a certain amount will be added or multiplied to the amount of compensation depending on the strength and type of emotion.

[1342] Step 4: The calculated amount of compensation is presented to the user. At this time, the emotion engine's emotion recognition results and their impact are clearly indicated to ensure transparency to the user.

[1343] Example 1

[1344] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1345] Conventional traffic accident compensation standard judgment systems calculate the amount of compensation based on information about the traffic accident, but since they do not take into account the emotional damage of the user, it is difficult to calculate an appropriate amount of compensation. In addition, it can take time to read and analyze information about traffic accidents, which is insufficient in situations where a quick response is required.

[1346] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1347] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the user's emotions, and a means for adjusting the calculation of the amount of compensation based on the recognized emotions. This enables a more appropriate calculation of the amount of compensation that takes into account the emotional damage of the user.

[1348] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[1349] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[1350] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[1351] "Information regarding traffic accidents" refers to detailed data related to accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[1352] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[1353] "User emotion" refers to a psychological state such as anger, sadness, or happiness felt by a user.

[1354] "Means for recognizing emotions" refers to technology for analyzing and recognizing emotions from a user's tone of voice, facial expressions, choice of words, etc.

[1355] A "damages adjustment measure" is a method for appropriately modifying or adjusting the amount of damages based on perceived feelings.

[1356] The present invention relates to a simplified determination system for traffic accident compensation standards, and in particular to a system for calculating the amount of compensation taking into account the user's emotions.

[1357] System Configuration

[1358] Hardware

[1359] Server: A server with high-performance computing power (e.g. a virtual server for cloud services)

[1360] Terminal: The device through which the user enters information (e.g. computer, smartphone)

[1361] Input devices: Microphone, camera (to recognize the user's tone of voice and facial expressions)

[1362] software

[1363] Database: A database for storing information about traffic accidents and compensation criteria (e.g. MySQL)

[1364] AI model: An AI model (e.g. TensorFlow) for analyzing traffic accident information and calculating compensation amounts.

[1365] Emotion recognition engine: Software for recognizing user emotions (e.g. Affectiva)

[1366] System Operation

[1367] 1. The user enters detailed information about a traffic accident, such as the location and time of the accident, and the circumstances of the people involved, into a web form.

[1368] Example: "Location of accident: Shibuya-ku, Tokyo, Time: 14:00 on October 1, 2023, Situation of the parties involved: Pedestrian hit by car."

[1369] 2. The device sends the entered information to the server. The device sends the data using an HTTP request.

[1370] 3. The server saves the received information in the database. The server executes an INSERT query in the MySQL database to save the information.

[1371] 4. The server passes the stored information to the AI ​​model for analysis. The server inputs the data into the TensorFlow model and performs the analysis.

[1372] 5. The server calculates the amount of damages based on the analysis results. The server refers to the "Red Book" and "Blue Book" databases to calculate the amount of damages.

[1373] 6. When a user enters information about a traffic accident, the emotion engine recognizes the user's emotion. For example, if the user says "I'm very sad," the emotion engine recognizes "sadness."

[1374] 7. The server receives emotion data from the emotion engine. The server receives the data from the emotion engine via an HTTP request.

[1375] 8. The server saves the emotion data and traffic accident information in the database. The server executes an INSERT query on the MySQL database to save the information.

[1376] 9. The server passes the stored information to the AI ​​model for analysis. The server inputs the data into the TensorFlow model and performs the analysis.

[1377] 10. The server calculates the amount of damages based on the analysis results and takes emotions into account. The server refers to the databases of the "Red Book" and "Blue Book" and calculates the amount of damages taking into account emotional data.

[1378] 11. The server sends the calculation result to the terminal. The server sends the data to the terminal using an HTTP response.

[1379] 12. The terminal displays the calculation result to the user. The terminal displays "Amount of damages: 5.5 million yen (emotions taken into consideration)" on the web page.

[1380] Examples of prompt statements

[1381] 1. Simplified Judgment System for Traffic Accident Compensation Standards

[1382] Prompt: "Please enter details about the traffic accident. For example, location, time, and circumstances of the accident."

[1383] 2. System combining emotion engines

[1384] Prompt: "Please enter information about the traffic accident and express your feelings. For example, location of the accident, time, situation of the people involved, and emotions (anger, sadness, etc.)."

[1385] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1386] Step 1:

[1387] The user enters detailed information about the traffic accident.

[1388] Input: Details of the accident, such as location, time, and circumstances of the people involved

[1389] Specific actions: A user enters the following information into a web form: "Accident location: Shibuya-ku, Tokyo, Time: 14:00 on October 1, 2023, Situation of the parties involved: Pedestrian hit by car."

[1390] Output: Detailed information about the traffic accidents entered

[1391] Step 2:

[1392] The terminal transmits the input information to the server.

[1393] Input: User-entered details of the traffic accident

[1394] Specific operation: The device sends data to the server using an HTTP request.

[1395] Output: Detailed information about the traffic accident sent to the server

[1396] Step 3:

[1397] The server stores the received information in a database.

[1398] Input: Traffic accident details sent from the device

[1399] What happens next: The server executes an INSERT query into the MySQL database to save the information.

[1400] Output: Detailed information about traffic accidents stored in a database

[1401] Step 4:

[1402] The server passes the stored information to the AI ​​model for analysis.

[1403] Input: Traffic accident details stored in the database

[1404] What happens: The server inputs the data into the TensorFlow model and performs the analysis.

[1405] Output: Analysis results (data necessary for calculating the amount of damages)

[1406] Step 5:

[1407] The server calculates the amount of compensation based on the analysis results.

[1408] Input: Analysis results from the AI ​​model

[1409] Specific operation: The server refers to the "Red Book" and "Blue Book" databases and calculates the amount of damages.

[1410] Output: Calculated damages

[1411] Step 6:

[1412] When a user enters information about a traffic accident, the emotion engine recognizes the user's emotions.

[1413] Input: User tone of voice, facial expressions, and language

[1414] What happens: If a user says "I'm so sad," the emotion engine recognizes "sad."

[1415] Output: Recognized emotion data

[1416] Step 7:

[1417] A server receives emotion data from an emotion engine.

[1418] Input: Sentiment data from the sentiment engine

[1419] Specific operation: The server receives data from the emotion engine via an HTTP request.

[1420] Output: Emotion data received by the server

[1421] Step 8:

[1422] The server stores the emotion data and traffic accident information in a database.

[1423] Input: Sentiment data and details of traffic accidents

[1424] What happens next: The server executes an INSERT query into the MySQL database to save the information.

[1425] Output: Emotion data and traffic accident information stored in a database

[1426] Step 9:

[1427] The server passes the stored information to the AI ​​model for analysis.

[1428] Input: Emotion data and traffic accident information stored in the database

[1429] What happens: The server inputs the data into the TensorFlow model and performs the analysis.

[1430] Output: Analysis results (data necessary for calculating damages taking emotions into account)

[1431] Step 10:

[1432] The server calculates the amount of damages based on the analysis results, taking emotions into account.

[1433] Input: Analysis results from the AI ​​model and emotion data

[1434] Specific operation: The server refers to the database of "Red Book" and "Blue Book" and calculates the amount of compensation by taking into account the emotional data.

[1435] Output: Calculated damages taking emotions into account

[1436] Step 11:

[1437] The server transmits the calculation result to the terminal.

[1438] Input: Calculated damages taking into account emotions

[1439] Specific operation: The server sends data to the device using an HTTP response.

[1440] Output: Damage amount sent to the terminal

[1441] Step 12:

[1442] The terminal displays the calculation results to the user.

[1443] Input: damages amount sent from server

[1444] Specific operation: The device displays the following on a web page: "Amount of damages: 5.5 million yen (emotions taken into consideration)."

[1445] Output: The damages displayed to the user.

[1446] (Application example 1)

[1447] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1448] When a traffic accident occurs, it is important to calculate the amount of compensation quickly and accurately. However, in conventional systems, it takes a lot of time and effort to manually input detailed information about the accident and calculate the amount of compensation. It is also difficult to take into account the emotional damage of the victim, making it difficult to calculate an appropriate amount of compensation. Furthermore, in the case of autonomous vehicles, it is required to collect information at the time of the accident and calculate the amount of compensation in real time. A new system is needed to solve these problems.

[1449] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1450] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the emotions of the passengers, a means for adjusting the amount of compensation based on the recognized emotions, and a means for being installed in the autonomous vehicle. This makes it possible to quickly and accurately calculate the amount of compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that takes into account the emotional damage of the victim.

[1451] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[1452] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[1453] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[1454] "Information regarding traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[1455] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[1456] "Passenger emotions" refers to the psychological state and feelings of passengers when they are involved in a traffic accident.

[1457] "Means of recognizing emotions" refers to technology that analyzes and recognizes emotions from passengers' tone of voice, facial expressions, language, etc.

[1458] An "autonomous vehicle" is a vehicle that can drive autonomously using artificial intelligence and sensor technology.

[1459] An "adjusting tool" is a method or technique for appropriately modifying damage awards based on perceived sentiment.

[1460] The system for carrying out this invention has the following configuration: The server includes a means for performing a simplified determination of traffic accident compensation standards using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing passenger emotions, a means for adjusting the amount of compensation based on the recognized emotions, and a means for being installed in the autonomous vehicle.

[1461] Program processing explanation

[1462] The server first collects information about the traffic accident, including details such as the location of the accident, time, vehicle speed, weather, etc. This information is obtained automatically from sensors, GPS and the vehicle's internal systems.

[1463] Next, to recognize passenger emotions, cameras and microphones installed in the vehicle are used. The camera captures the passenger's facial expressions, and the microphone collects the passenger's voice. These data are analyzed using software such as OpenCV and SpeechRecognition. The analyzed data is input into a deep learning model using Keras to recognize the passenger's emotions.

[1464] The recognized emotions and collected traffic accident information are input into an AI model for calculating the amount of compensation. The AI ​​model calculates the amount of compensation based on the traffic accident compensation standard. Furthermore, the amount of compensation is adjusted based on the recognized emotions.

[1465] Examples

[1466] For example, if the accident occurred in Tokyo, the vehicle speed was 60km / h, the weather was sunny, and the passengers expressed anger, the AI ​​model would use this information to calculate the compensation amount and adjust it to take into account the anger.

[1467] Examples of prompt statements

[1468] The accident occurred in Tokyo, the vehicle speed was 60km / h, and the weather was fine. The passengers showed angry emotions. Please calculate the amount of compensation based on this information.

[1469] In this way, it will be possible to quickly and accurately calculate compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that also takes into account the emotional damage suffered by the victim.

[1470] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1471] Step 1:

[1472] The server collects information about traffic accidents, including details such as the location and time of the accident, the vehicle's speed, and weather, automatically obtained from sensors, GPS, and the vehicle's internal systems. This information is then stored in a database.

[1473] Inputs: Data from sensors, GPS, and vehicle internal systems

[1474] Output: Detailed information about traffic accidents (location, time, speed, weather)

[1475] Step 2:

[1476] The server recognizes passengers' emotions using cameras and microphones installed in the vehicle. The camera captures the passengers' facial expressions, and the microphone collects the passengers' voices. These data are analyzed using software such as OpenCV and SpeechRecognition. The analyzed data is input into a deep learning model using Keras to recognize the passengers' emotions.

[1477] Input: Camera video, microphone audio

[1478] Output: Passenger sentiment data

[1479] Step 3:

[1480] The server inputs the recognized emotions and collected traffic accident information into an AI model for calculating the amount of compensation, which calculates the amount of compensation based on the traffic accident compensation standard.

[1481] Input: Traffic accident details, passenger emotion data

[1482] Output: Initial damages amount

[1483] Step 4:

[1484] The server adjusts the damage amount based on the recognized emotion, for example, if the passenger shows emotion of anger, it increases the damage amount to take the emotional damage into account.

[1485] Input: Initial damage amount, passenger emotion data

[1486] Output: Adjusted damages

[1487] Step 5:

[1488] The server outputs the final amount of damages and notifies the user via the vehicle's display or smartphone app.

[1489] Input: Adjusted damages amount

[1490] Output:Notification to the user

[1491] In this way, it will be possible to quickly and accurately calculate compensation when a traffic accident occurs, and to calculate an appropriate amount of compensation that also takes into account the emotional damage suffered by the victim.

[1492] Example 2

[1493] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1494] Conventional traffic accident compensation calculation systems have the problem that they are unable to take into account the emotional damage of the user, making it difficult to calculate an appropriate amount of compensation. In addition, inputting information about traffic accidents is cumbersome, making the system difficult to use for users.

[1495] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1496] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the user's emotions, and a means for adjusting the amount of compensation based on the recognized emotions. This makes it possible to calculate an appropriate amount of compensation taking into account the emotional damage of the user.

[1497] The "means for simplified determination of traffic accident compensation standards using AI" is a function that uses artificial intelligence technology to quickly and easily determine the standard for compensation amounts in traffic accidents.

[1498] "Means of reading information related to traffic accidents" refers to a function for inputting detailed information about traffic accidents (such as the location and time of the accident, the circumstances of the parties involved, etc.) into the system and importing it as data.

[1499] The "means for calculating the amount of compensation based on the loaded information" is a function for calculating the amount of compensation based on the loaded traffic accident information.

[1500] The "means for recognizing the user's emotions" is a function for detecting and recognizing the emotions of the user from the user's tone of voice, facial expressions, choice of words, etc.

[1501] The "means for adjusting the amount of damages based on the recognized emotion" is a function for appropriately adjusting the amount of damages taking into account the recognized emotion of the user.

[1502] This invention is a system for automobile insurance policyholders, where the user inputs their insurance contract information and detailed information about the traffic accident, and the AI ​​analyzes this information and calculates the amount of compensation. In addition, by combining it with an emotion engine that recognizes the user's emotions, it becomes possible to calculate the amount of compensation that takes emotional damage into account.

[1503] Hardware and Software Used

[1504] 1. Server

[1505] The server receives the information sent by the user and analyzes it using an AI model. The server is equipped with an AI model implemented in Python, and has the function of calculating the amount of damages based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards."

[1506] 2. Terminal

[1507] The terminal provides an interface for the user to input information. The terminal has a communication function for transmitting the input information to the server. The communication is performed using the HTTPS protocol, and the data is encrypted.

[1508] 3. Emotion Engine

[1509] The emotion engine is software for recognizing emotions from a user's tone of voice, facial expressions, language, etc. The emotion engine is built using TensorFlow and analyzes the user's emotions in real time.

[1510] Examples

[1511] For example, if a user enters the following information:

[1512] Insurance contract information: Type of insurance is "Comprehensive insurance", premium is "100,000 yen per year"

[1513] Traffic accident details: The accident occurred in "Shibuya Ward, Tokyo," the time was "3:00 p.m.", and the circumstances of the parties involved were "the other party ran a red light."

[1514] With this information, the server uses an AI model to calculate damages, and if the emotion engine detects that the user is feeling a strong sense of anger while typing, it will adjust the damages amount to take that emotion into account.

[1515] Examples of prompt statements

[1516] Here is an example of a prompt to be input to the generative AI model:

[1517] Use your insurance policy information and the details of the traffic accident to help us calculate your damages. Use the following information:

[1518] Insurance type: Comprehensive insurance

[1519] Insurance premium: 100,000 yen per year

[1520] Location of accident: Shibuya Ward, Tokyo

[1521] Time of accident: 3 p.m.

[1522] Situation of the parties involved: The other party ignored the traffic signal.

[1523] Also consider that the user's emotion is "anger."

[1524] Using this prompt, the generative AI model can calculate the amount of damages based on the necessary information and output a result that takes emotions into account.

[1525] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1526] Step 1:

[1527] The user enters information

[1528] The user inputs their own insurance contract information (type of insurance, premium, etc.) and detailed information about the traffic accident (location of the accident, time, circumstances of the parties involved, etc.) into an input form on the device. For example, the user inputs information such as "comprehensive insurance," "100,000 yen per year," "Shibuya-ku, Tokyo," "3:00 p.m.," and "the other party ran a red light." The input information is temporarily stored in the device's memory.

[1529] Step 2:

[1530] The device sends information

[1531] The terminal sends the insurance policy information and traffic accident details entered by the user to the server using the HTTPS protocol and the data is encrypted. The input data is converted to JSON format and sent to the server's API endpoint.

[1532] Step 3:

[1533] The server receives the information

[1534] The server receives the insurance contract information and the detailed information of the traffic accident sent from the terminal. The received data is stored in a database. Specifically, the server parses the received JSON data and stores each field in the corresponding column of the database.

[1535] Step 4:

[1536] The server analyzes the information

[1537] The server inputs the received information into the AI ​​model and begins analysis. Specifically, the AI ​​model implemented in Python calculates the amount of compensation based on the "Red Book" "Civil Traffic Accident Lawsuit Damage Compensation Calculation Standards" and the "Blue Book" "Traffic Accident Damage Calculation Standards." For example, the AI ​​model analyzes information such as "comprehensive insurance," "100,000 yen per year," "Shibuya Ward, Tokyo," "3:00 p.m.," and "other party ignored a traffic signal" to calculate the initial amount of compensation. The calculation results are temporarily stored in memory.

[1538] Step 5:

[1539] Emotion engine recognizes user emotions

[1540] When a user inputs information, the emotion engine recognizes emotions from the user's tone of voice, facial expressions, and language. For example, if a user feels strong anger while inputting information, the emotion engine recognizes that emotion. The emotion engine is built using TensorFlow and analyzes emotions in real time. The recognized emotion data is sent to the server.

[1541] Step 6:

[1542] The server adjusts the damage amount based on emotions.

[1543] The server adjusts the amount of damages based on the emotion recognition results from the emotion engine. For example, if the user feels strong anger, the amount of damages is increased taking that emotion into account. Specifically, a correction value that takes into account the influence of the emotion is applied to the initial amount of damages to calculate the final amount of damages. The adjusted amount of damages is stored in the database.

[1544] Step 7:

[1545] The server outputs the results

[1546] The server outputs the final calculated amount of damages to the user. The result is displayed on the terminal screen and sent to the user's email address. For example, a result such as "The final amount of damages is 1 million yen" may be displayed. The output data is generated in HTML format and sent to the user's terminal.

[1547] (Application example 2)

[1548] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1549] Conventional traffic accident compensation calculation systems calculate compensation amounts based on detailed information about the accident, but are unable to take into account the emotional damage suffered by passengers. Therefore, there is a need for a more appropriate compensation calculation method that includes emotional damage. There is also a need for a system that can calculate compensation amounts in real time when an accident occurs.

[1550] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1551] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for analyzing data obtained from the vehicle's sensors and cameras, and a means for taking into account the emotional state of the occupants using an emotion engine that recognizes their emotions. This makes it possible to calculate the amount of compensation in real time when an accident occurs, and to calculate a more appropriate amount of compensation that also takes into account emotional damage.

[1552] "AI" stands for artificial intelligence, a technology that allows computers to mimic human intelligence to learn, reason, and self-correct.

[1553] The "Traffic Accident Compensation Standards" are the standards for calculating the amount of compensation in traffic accidents, and specifically refer to the standards set out in the "Red Book" and "Blue Book."

[1554] "Information on traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[1555] "Amount of damages" refers to the monetary compensation paid to a victim for damages suffered in a traffic accident.

[1556] A "sensor" is a device that detects a physical phenomenon and converts it into an electrical signal.

[1557] A "camera" is a device that converts light into electrical signals to record images or videos.

[1558] An "emotion engine" is a technology that recognizes emotions from a user's tone of voice, facial expressions, choice of words, etc., and analyzes their emotional state.

[1559] "Emotional state" refers to the type and intensity of emotion a user is feeling.

[1560] A "system" refers to a collection of devices or programs in which multiple elements function in conjunction with each other.

[1561] The system for carrying out this invention is configured as follows: The server includes a means for performing a simplified determination of traffic accident compensation standards using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for analyzing data obtained from the vehicle's sensors and cameras, and a means for taking into account the emotional state of the occupants using an emotion engine that recognizes their emotions.

[1562] Program processing explanation

[1563] The server first receives real-time data from vehicle sensors and cameras, including information on the location and time of the accident, vehicle speed, impact force, etc. The server then analyzes this data to generate detailed information about the traffic accident.

[1564] The server then uses an emotion engine to analyze the passenger's tone of voice and facial expressions captured by the vehicle's microphones and cameras to recognize the passenger's emotional state. The emotion engine uses software called EmotionRecognizer to identify the passenger's emotions.

[1565] The server then calculates the amount of compensation based on the traffic accident compensation standard. Specifically, the AI ​​calculates the amount of compensation using the standards set out in the "Red Book" and "Blue Book." In addition, it adjusts the final amount of compensation by taking into account the perceived emotional state.

[1566] Examples

[1567] For example, if the accident occurred in Tokyo, the time of the accident was 14:30 on October 1, 2023, the vehicle speed was 60 km / h, and the impact force was 500 N, the server would calculate the amount of compensation based on this information. Also, if the passenger is feeling angry, the emotion engine would recognize that emotion and reflect it in the amount of compensation.

[1568] Examples of prompt statements

[1569] Below are examples of prompts to be input to the generative AI model.

[1570] The accident location is Tokyo, and the accident time is October 1, 2023 at 14:30. The vehicle speed is 60 km / h, and the impact force is 500 N. The occupants feel angry. Based on this information, please calculate the amount of damages.

[1571] In this way, the server can calculate compensation in real time, taking into account the details of the accident and the emotional state of the occupants.

[1572] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1573] Step 1:

[1574] The server receives data from vehicle sensors and cameras in real time. As input, it receives information such as the location and time of the accident, the vehicle speed, and the impact force, and analyzes this data to generate detailed information about the traffic accident. As output, it obtains the analyzed detailed information about the traffic accident.

[1575] Step 2:

[1576] The server uses the emotion engine to analyze the passenger's tone of voice and facial expressions captured by the in-car microphones and cameras. As input, it receives audio and video data and identifies the passenger's emotions using software called EmotionRecognizer. As output, it gets the recognized emotional state.

[1577] Step 3:

[1578] The server calculates the amount of compensation based on the traffic accident compensation standard. As input, it receives the detailed information of the traffic accident obtained in step 1 and the emotional state obtained in step 2, and the AI ​​calculates the amount of compensation using the standards described in the "Red Book" and "Blue Book". As output, it obtains the calculated amount of compensation.

[1579] Step 4:

[1580] The server adjusts the final damages amount taking into account the perceived emotional state. As input, it takes the damages amount calculated in step 3 and the perceived emotional state in step 2, and calculates the final damages amount that reflects the emotional damage. As output, it gets the adjusted final damages amount.

[1581] Step 5:

[1582] The server notifies the user of the final amount of damages. As input, it receives the final amount of damages obtained in step 4 and sends a notification to the user's terminal. As output, it obtains the amount of damages notified to the user.

[1583] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1584] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1585] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1586] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1587] [Fourth embodiment]

[1588] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1589] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1590] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1591] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. In addition, the microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1592] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1593] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1594] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1595] The control target 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, legs, etc. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, legs, etc. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1596] Fig. 8 shows an example of main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1597] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1598] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1599] In the robot 414, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1600] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1601] "Example 1"

[1602] One embodiment of the present invention is a simplified system for determining standards for compensation for traffic accident damages using AI. This system is equipped with a means for reading information about traffic accidents and a means for calculating the amount of compensation for damages based on the read information. Specifically, the system receives detailed information about the traffic accident (such as the location and time of the accident, and the circumstances of the parties involved) as input, and the AI ​​analyzes this information. The system then calculates the amount of compensation for damages based on the "Red Book" "Standards for Calculating Compensation for Civil Traffic Accident Lawsuits" and the "Blue Book" "Standards for Calculating Compensation for Traffic Accident Damages," and outputs the results.

[1603] "Example 2"

[1604] Another embodiment of the present invention is a system targeted at voluntary automobile insurance subscribers. In this system, the subscriber inputs his / her insurance contract information and detailed information about the traffic accident, and AI analyzes this information and calculates the amount of damages. Specifically, the subscriber inputs his / her insurance contract information (type of insurance, insurance premium, etc.) and detailed information about the traffic accident (location of the accident, time, status of the parties involved, etc.), and AI analyzes this information. Then, the AI ​​calculates the amount of damages based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards," and outputs the results.

[1605] The process flow of each embodiment will be described below.

[1606] "Example 1"

[1607] Step 1: The user enters detailed information about the traffic accident (location, time of the accident, circumstances of the parties involved, etc.) into the system.

[1608] Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[1609] Step 3: The calculated amount of damages is output to the user.

[1610] "Example 2"

[1611] Step 1: A voluntary automobile insurance policyholder enters their insurance contract information (type of insurance, premium, etc.) and detailed information about the traffic accident (location of the accident, time, circumstances of the parties involved, etc.) into the system. Step 2: The AI ​​analyzes the entered information and calculates the amount of compensation based on the "Red Book" and "Standards for Calculating Damages in Civil Traffic Accident Lawsuits" and the "Blue Book" and "Standards for Calculating Damages in Traffic Accidents."

[1612] Step 3: The calculated amount of damages is output to the subscriber.

[1613] Example 1

[1614] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1615] Calculating compensation for traffic accidents requires specialized knowledge and is time-consuming and laborious. In addition, the calculation standards for compensation are complex, making it difficult for general users to easily understand and apply. For this reason, a system that can calculate compensation quickly and accurately is required.

[1616] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1617] In this invention, the server includes a means for inputting detailed information about a traffic accident, a means for transmitting the input information to the server, a means for the server to analyze the information received, a means for the server to calculate the amount of compensation using the generative AI model, a means for transmitting the calculation result to the terminal, and a means for the terminal to display the calculation result to the user. This allows the user to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation.

[1618] "Detailed information about the traffic accident" is specific information related to the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[1619] "Input means" refers to an interface or device that allows a user to input detailed information about a traffic accident.

[1620] A "server" is a computer system that receives information sent by users, analyzes it, and calculates the amount of damages.

[1621] The "transmitting means" refers to a communication means for transmitting information from the terminal to the server.

[1622] "Means of analysis" refers to software or algorithms used by the server to process the information it receives and check its consistency.

[1623] A "generative AI model" is an artificial intelligence model trained to calculate compensation amounts for traffic accidents.

[1624] A “means for calculating” is a process or algorithm for calculating damages using a generative AI model.

[1625] A "terminal" is a device through which a user inputs information and checks the results of calculations.

[1626] The "display means" refers to an interface for visually presenting to the user the calculation results that the terminal receives from the server.

[1627] The present invention is a system for quickly and accurately calculating the amount of compensation for damages in a traffic accident. A specific embodiment of this system will be described below.

[1628] First, the user uses the terminal to input detailed information about a traffic accident. The input form includes items such as the location of the accident, the time of the accident, the circumstances of the people involved, etc. For example, the user inputs information according to the following prompts:

[1629] "Where did the accident occur?"

[1630] "What time did the accident occur?"

[1631] Please tell us the situation of the parties involved.

[1632] The information entered by the user is sent from the terminal to the server, which then sends the information to the server in an appropriate format (e.g., JSON format).

[1633] The server analyzes the information it receives, which may include checking the integrity of the information and pre-processing it, such as making sure the time of occurrence is not in the future and that the location is a valid place name.

[1634] The server then uses a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information and calculates the amount of compensation based on past traffic accident data and standards.

[1635] The calculation result is sent from the server to the terminal. The terminal displays the received calculation result to the user. The user can check the amount of compensation displayed on the terminal screen. For example, a result such as "The amount of compensation is 5 million yen" may be displayed.

[1636] This system allows users to easily input detailed information about a traffic accident and quickly and accurately check the amount of compensation. The hardware used includes the user's terminal (PC, smartphone, etc.) and the server. The software includes the input form, communication protocol, analysis algorithm, and generative AI model.

[1637] As a concrete example, if the user enters the following information:

[1638] Location of accident: Shinjuku Ward, Tokyo

[1639] Time of accident: October 1, 2023, 14:30

[1640] Situation of the parties involved: Vehicle A runs a red light and crashes into vehicle B.

[1641] The server receives this information and performs analysis using the generative AI model. As a result of the analysis, the amount of compensation is calculated and a result such as "The amount of compensation is 5 million yen" is displayed on the terminal.

[1642] In this way, users can easily check the amount of compensation by simply entering detailed information about a traffic accident.

[1643] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1644] Step 1:

[1645] The user enters detailed information about the traffic accident.

[1646] The user inputs information such as the location and time of the accident, and the status of the people involved into the input form on the terminal. For example, the user inputs information following prompts such as "Where did the accident occur?", "What time did the accident occur?", and "Please tell us the status of the people involved." The input information is temporarily stored in the terminal's memory.

[1647] Step 2:

[1648] The terminal transmits the input information to the server.

[1649] The terminal sends the information entered by the user to the server in an appropriate format (for example, JSON format). The data sent includes the location of the accident, the time of the accident, the status of the people involved, etc. For example, the following JSON data is sent:

[1650] json

[1651] {

[1652] "location": "Shinjuku-ku, Tokyo",

[1653] "time": "2023-10-01T14:30:00",

[1654] "details": "Vehicle A runs a red light and collides with vehicle B"

[1655] }

[1656] Step 3:

[1657] The server analyzes the information it receives.

[1658] The server receives the JSON data sent from the terminal and begins analyzing it. The analysis includes checking the consistency of the information and preprocessing. For example, it checks whether the time of occurrence is a future date, whether the location is a valid place name, etc. As a result of the analysis, data with confirmed consistency is generated.

[1659] Step 4:

[1660] The server uses the generative AI model to calculate damages.

[1661] The server inputs the analyzed information into a generative AI model to calculate the amount of compensation. This generative AI model is trained based on the "Traffic Accident Compensation Standards" to calculate the amount of compensation for traffic accidents. The AI ​​model analyzes the input information based on past traffic accident data and standards, and calculates the amount of compensation. The amount of compensation is generated as a calculation result.

[1662] Step 5:

[1663] The server transmits the calculation result to the terminal.

[1664] The server sends the calculated amount of damages to the terminal in an appropriate format (for example, JSON format). The data sent includes details of the amount of damages. For example, the following JSON data is sent:

[1665] json

[1666] {

[1667] "compensation_amount": 5000000,

[1668] "details": "The damages amount to 5 million yen."

[1669] }

[1670] Step 6:

[1671] The terminal displays the calculation results to the user.

[1672] The terminal displays the calculation results received from the server to the user. The user can check the amount of damages displayed on the terminal screen. For example, the result "The amount of damages is 5 million yen" may be displayed.

[1673] (Application example 1)

[1674] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1675] When a traffic accident occurs, it is important for both the victim and the at-fault party to calculate the amount of compensation quickly and accurately. However, the conventional method requires manually collecting detailed information about the accident and having experts analyze it before calculating the amount of compensation, which is time-consuming and labor-intensive. In addition, as autonomous vehicles become more widespread, there is a demand for a system that can respond immediately when an accident occurs.

[1676] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting accident information from the sensor or camera of the autonomous vehicle, a means for analyzing the collected information and calculating the amount of compensation, a means for calculating the amount of compensation using a generative AI model, and a means for generating a prompt sentence and inputting it into the AI ​​model. This makes it possible to quickly and accurately calculate the amount of compensation when a traffic accident occurs.

[1677] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[1678] The "Traffic Accident Compensation Standards" are standards for calculating the amount of compensation in traffic accidents and are used as legal guidelines.

[1679] "Simplified assessment" is a method of assessment that simplifies complicated procedures and provides results quickly.

[1680] "Information regarding traffic accidents" refers to detailed data related to traffic accidents, such as the location and time of the accident, and the circumstances of the parties involved.

[1681] "Amount of damages" refers to the amount of money paid to a victim for damages suffered in a traffic accident.

[1682] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[1683] A "sensor" is a device that detects physical phenomena and outputs them as data.

[1684] A "camera" is a device that captures images or videos.

[1685] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[1686] A "prompt" is an instruction to be input to a generative AI model, which serves as a guideline for the model to generate appropriate output.

[1687] The system for carrying out the present invention is for quickly and accurately calculating the amount of compensation for damages when a traffic accident occurs. A specific embodiment of this system will be described below.

[1688] The system includes a means of collecting accident information from sensors and cameras installed in the autonomous vehicle, which allows detailed data such as the location and time of the accident, as well as the circumstances of the people involved, to be collected in real time. The collected data is then sent to a computer in the vehicle where it undergoes initial processing.

[1689] Then, the initially processed data is sent to a server. The server uses a generative AI model to analyze the collected accident information. Specifically, the server includes the following means:

[1690] 1. A means of reading information about traffic accidents: Read data collected from sensors and cameras to obtain detailed information about accidents.

[1691] 2. Method of calculating damages: Based on the information read in, the generative AI model calculates the amount of damages. The calculation is based on the "Red Book" "Civil Traffic Accident Lawsuit Damages Calculation Standards" and the "Blue Book" "Traffic Accident Damages Calculation Standards."

[1692] 3. A means for generating prompt sentences and inputting them into the AI ​​model: A prompt sentence is generated based on the accident information and input into the generative AI model.

[1693] For example, the following prompt would be generated:

[1694] A traffic accident has occurred. Details of the accident are as follows:

[1695] Location: Tokyo, Japan

[1696] Occurrence time: 2023-10-01T12:34:56

[1697] Status of the parties: Driver A (Injured), Driver B (Uninjured)

[1698] Vehicle Damage: Severe

[1699] Use this information to assess your damages.

[1700] The server inputs this prompt into a generative AI model to calculate the amount of damages, and the calculation result is notified to the user via an in-vehicle display or a smartphone application.

[1701] This system will enable the prompt and accurate calculation of compensation when a traffic accident occurs, enabling a prompt response for both the victim and the at-fault party. In addition, as autonomous vehicles become more widespread, the response to accidents will be automated, further improving safety and efficiency.

[1702] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1703] Step 1:

[1704] Sensors and cameras in autonomous vehicles detect the occurrence of a traffic accident. The sensors collect impact and location information, and the cameras capture video of the accident scene. These data are sent to a computer in the vehicle. The input is data from the sensors and cameras, and the output is initially processed accident information.

[1705] Step 2:

[1706] An in-vehicle computer performs initial processing of the collected data, analyzing impact data and location information from sensors and extracting accident details from camera footage. The input is raw data from sensors and cameras, and the output is analyzed accident details.

[1707] Step 3:

[1708] The initial processed accident information is sent to the server. The server receives this information and stores it in a database. The input is the accident details sent from the computer in the vehicle, and the output is the accident information stored in the database.

[1709] Step 4:

[1710] The server generates a prompt sentence based on the stored accident information. Specifically, it converts information such as the location and time of the accident, and the situation of the people involved into text format. The input is the accident information stored in the database, and the output is the generated prompt sentence.

[1711] Step 5:

[1712] The server inputs the generated prompt sentence into the generative AI model. The generative AI model analyzes the prompt sentence and calculates the amount of damages. The input is the generated prompt sentence, and the output is the calculated amount of damages.

[1713] Step 6:

[1714] The server notifies the user of the calculated amount of compensation through the display in the vehicle or a smartphone application. The input is the calculated amount of compensation, and the output is the amount of compensation notified to the user.

[1715] Step 7:

[1716] The user checks the notified amount of damages and contacts the insurance company or relevant organizations if necessary. The input is the notified amount of damages, and the output is the user's confirmation and contact.

[1717] Example 2

[1718] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1719] Conventional calculations of compensation for traffic accidents require manual work by people with specialized knowledge, which is time-consuming and labor-intensive. In addition, the calculation standards for compensation can be complex, making accurate calculations difficult. Furthermore, there was a lack of a way for users to easily input their own insurance contract information and detailed information about the accident and quickly find out the amount of compensation.

[1720] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1721] In this invention, the server includes a means for a user to input insurance contract information and detailed information about a traffic accident, a means for the server to receive the input information and perform preprocessing, a means for the server to input the preprocessed information into a generative AI model and perform analysis, a means for the server to calculate the amount of damages based on the analysis result, a means for the server to output the calculation result to the user's terminal, and a means for the user to check the result on the terminal. This allows the user to easily input information and quickly and accurately know the amount of damages.

[1722] A "user" is an individual or legal entity that utilizes the system to input insurance policy information and detailed information about a traffic accident.

[1723] "Insurance contract information" is detailed information about insurance, such as the type of insurance the user has subscribed to and the insurance premiums.

[1724] "Detailed information about the traffic accident" refers to specific information about the traffic accident, such as the location and time of the accident, and the circumstances of the parties involved.

[1725] A “server” is a computer system that receives information input by a user, performs preprocessing, and analyzes it using a generative AI model.

[1726] "Preprocessing" refers to processing the data received to format it and make it suitable for analysis.

[1727] A "generative AI model" is an artificial intelligence model built using a machine learning framework to analyze input information and calculate the amount of damages.

[1728] "Analysis" is the process in which the generative AI model performs calculations and inferences based on the input information to determine the amount of damages.

[1729] "Amount of damages" means the amount to be paid for damages in a traffic accident.

[1730] A "terminal" is a device that a user uses to enter information and view results from a server.

[1731] The “results” are information on the amount of damages calculated by the generative AI model.

[1732] This invention is a system in which a user inputs insurance contract information and detailed information about a traffic accident, and a server analyzes this information to calculate the amount of compensation. A specific embodiment of this system will be described below.

[1733] Hardware and Software Used

[1734] Hardware

[1735] Server: A high-performance computer system that receives data, pre-processes it, analyzes it, and outputs the results.

[1736] Terminal: A device where a user enters information and checks the results. This includes computers, smartphones, tablets, etc.

[1737] software

[1738] Generative AI Models: Artificial intelligence models built using machine learning frameworks such as TensorFlow and PyTorch.

[1739] Database Management System: A system for storing and managing information received from users, such as MySQL or PostgreSQL.

[1740] Web Application: Provides an interface for users to enter information. Uses web technologies such as HTML, CSS, and JavaScript.

[1741] Program Processing

[1742] User input of information

[1743] The user uses the terminal to input the insurance policy information and the details of the traffic accident. Specifically, the user inputs the following information:

[1744] Insurance contract information (e.g. type of insurance, premium)

[1745] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[1746] Receiving and preprocessing information by the server

[1747] The server receives the information sent by the user. The received information is stored in a database and pre-processed to format the data as necessary. For example, this includes standardizing the format of dates and times.

[1748] Input to the AI ​​model and analysis by the server

[1749] The server feeds the preprocessed information into a generative AI model, which generates a prompt like this:

[1750] Policy Information:

[1751] Insurance type: Comprehensive insurance

[1752] Insurance premium: 100,000 yen per year

[1753] Traffic accident details:

[1754] Location of accident: Shibuya Ward, Tokyo

[1755] Time of accident: October 1, 2023, 3:00 p.m.

[1756] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[1757] This prompt sentence is input into the AI ​​model and analysis begins.

[1758] Calculation of damages by the server

[1759] The generative AI model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[1760] Server output of results

[1761] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[1762] User review of results

[1763] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[1764] Examples

[1765] As a concrete example, consider the following scenario:

[1766] User A has automobile insurance, the type of insurance is "comprehensive insurance" and the premium is "100,000 yen per year."

[1767] User A is involved in a traffic accident. The location of the accident is "Shibuya Ward, Tokyo," the time of the accident is "October 1, 2023 at 3:00 p.m.", and the circumstances of the parties involved are "The car driven by User A was hit by a car that ran a red light."

[1768] Based on this information, User A inputs the following prompt into the generative AI model:

[1769] Policy Information:

[1770] Insurance type: Comprehensive insurance

[1771] Insurance premium: 100,000 yen per year

[1772] Traffic accident details:

[1773] Location of accident: Shibuya Ward, Tokyo

[1774] Time of accident: October 1, 2023, 3:00 p.m.

[1775] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[1776] The server receives this prompt, calculates the amount of compensation using the generative AI model, and outputs the result to the terminal of User A. For example, if the calculation result is "The amount of compensation is 500,000 yen," User A can check the result.

[1777] The above is a specific embodiment for carrying out the present invention.

[1778] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1779] Step 1:

[1780] The user uses the device to enter the insurance policy information and the details of the traffic accident, using a dedicated web form or a mobile app to enter the following information:

[1781] Insurance contract information (e.g. type of insurance, premium)

[1782] Detailed information about the traffic accident (e.g. location, time, and circumstances of the parties involved)

[1783] The entered information is transmitted from the terminal to the server.

[1784] Step 2:

[1785] The server receives the information sent by the user. The received information is stored in a database. After storage, pre-processing is performed to format the data. For example, this includes standardizing the format of the date and time.

[1786] Input: Insurance policy information and traffic accident details submitted by the user

[1787] Output: Preprocessed information

[1788] Step 3:

[1789] The server inputs the preprocessed information into a generative AI model, which generates a prompt sentence like this:

[1790] Policy Information:

[1791] Insurance type: Comprehensive insurance

[1792] Insurance premium: 100,000 yen per year

[1793] Traffic accident details:

[1794] Location of accident: Shibuya Ward, Tokyo

[1795] Time of accident: October 1, 2023, 3:00 p.m.

[1796] Situation of the parties involved: The car driven by User A was hit by a car that ran a red light.

[1797] This prompt sentence is input into the AI ​​model and analysis begins.

[1798] Input: Preprocessed information

[1799] Output: Prompt statement

[1800] Step 4:

[1801] The server analyzes the prompt sentence using a generative AI model. The AI ​​model calculates the amount of compensation based on the "traffic accident compensation standard." For example, the AI ​​model refers to past case data and estimates the amount of compensation based on similar cases.

[1802] Input: Prompt statement

[1803] Output: Damages amount

[1804] Step 5:

[1805] The server outputs the amount of damages calculated by the AI ​​model to the user's device in the format selected by the user, such as a text message or PDF file.

[1806] Input: Damages amount

[1807] Output: Damage amount result (text message and PDF file)

[1808] Step 6:

[1809] The user uses the terminal to check the result of the damages amount sent from the server. For example, User A receives the result "The damages amount is 500,000 yen" and checks it.

[1810] Input: Damages result

[1811] Output: User review of results

[1812] (Application example 2)

[1813] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1814] Conventional calculations of compensation for traffic accidents are often done manually, which takes time and effort and can be inaccurate. As autonomous vehicles become more widespread, there is a demand for a system that can calculate compensation in real time when an accident occurs. This will enable quick and accurate calculation of compensation, reducing the burden on insureds and related parties.

[1815] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1816] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for collecting detailed information about the accident from a sensor and a camera mounted on the autonomous vehicle, a means for analyzing the collected information in real time, a means for calculating the amount of compensation based on the analysis result, and a means for outputting the calculation result. This makes it possible to calculate the amount of compensation quickly and accurately when an accident occurs.

[1817] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to learn and make inferences.

[1818] The "Traffic Accident Compensation Standards" are the standards for calculating the amount of compensation in traffic accidents, and are set out in the "Red Book" and "Blue Book."

[1819] "Simplified determination" is a method of obtaining results quickly by simplifying complex calculations and procedures.

[1820] "Information regarding traffic accidents" refers to detailed data related to the accident, such as the location and time of the accident, and the circumstances of the parties involved.

[1821] "Amount of damages" refers to the amount of money paid for damages caused by a traffic accident.

[1822] An "autonomous vehicle" is a vehicle that drives itself using artificial intelligence and sensor technology.

[1823] A "sensor" is a device that detects physical phenomena and outputs them as data.

[1824] A "camera" is a device that captures images or videos.

[1825] "Real-time" refers to processing and analysis at the exact moment an event occurs.

[1826] "Analysis" means examining data in detail to clarify its meaning and structure.

[1827] "Output" refers to displaying the results of a calculation or analysis or sending them to another system.

[1828] As an embodiment of the present invention, a system installed in an autonomous vehicle will be described as an example. This system calculates the amount of damages in real time when a traffic accident occurs.

[1829] First, autonomous vehicles are equipped with multiple sensors and cameras that are used to collect detailed information about accidents. Specifically, they obtain data in real time about the location and time of the accident, the circumstances of the people involved, and other information.

[1830] The acquired data is then sent to a computer system in the vehicle, which uses AI (Artificial Intelligence) to analyze the data and calculate the amount of damages. The AI ​​uses models to calculate the amount of damages based on the "Red Book" and "Blue Book".

[1831] The specific process is as follows: first, data obtained from sensors and cameras is input into a computer system. Next, AI analyzes the data and calculates the amount of damages. Finally, the calculation result is notified to the user via the vehicle's display or a smartphone application.

[1832] The hardware used includes sensors, cameras, and computer systems installed in the autonomous vehicle, while the software uses programming languages ​​such as Python to implement AI models and transmit and receive data using HTTP requests.

[1833] As a concrete example, the following prompt sentence can be input into a generative AI model to calculate the amount of damages:

[1834] "Insurance contract information: Comprehensive insurance, Insurance premium: 50,000 yen, Accident details: Location: Tokyo, Japan, Time: 2023-10-01 14:30:00, Parties involved: Vehicle A, Vehicle B"

[1835] Based on this prompt, the AI ​​model calculates the amount of compensation and notifies the user of the result, making it possible to calculate compensation quickly and accurately when an accident occurs.

[1836] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1837] Step 1:

[1838] Sensors and cameras in autonomous vehicles collect detailed information about the accident.

[1839] Input: Data such as the location and time of the accident, and the circumstances of the people involved.

[1840] Output: Collected accident details.

[1841] How it works: Sensors detect the location, speed, and strength of the impact, and cameras capture images of the accident scene. This data is sent to the vehicle's computer system.

[1842] Step 2:

[1843] A computer system within the vehicle receives the collected data and prepares it for analysis.

[1844] Input: Accident details sent from sensors and cameras.

[1845] Output: Data formatted for analysis.

[1846] Specific operations: Format the received data, extract the necessary information, and prepare it in a form suitable for analysis.

[1847] Step 3:

[1848] A computer system will input the data into an AI model to calculate damages.

[1849] Input: Formatted accident details.

[1850] Output: Calculated damages.

[1851] Specific operation: The formatted data is input into the AI ​​model, and the amount of damages is calculated based on the "red book" and "blue book." The AI ​​model is implemented in a programming language such as Python, and sends and receives data using HTTP requests.

[1852] Step 4:

[1853] The calculation results are notified to the user via the vehicle's display or smartphone application.

[1854] Input: Calculated damages.

[1855] Output: A damages notice displayed to the user.

[1856] Specific operation: The calculation results are sent to a display or smartphone application to be displayed in a format that is easy for users to understand. This allows users to quickly and accurately check the amount of compensation in the event of an accident.

[1857] In addition, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1858] "Example 1"

[1859] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[1860] "Example 2"

[1861] One embodiment of the present invention is a system that combines an emotion engine that recognizes the emotions of a user. This system recognizes emotions from the user's tone of voice, facial expressions, language, etc., and adjusts the calculation of the amount of compensation based on the recognized emotions. Specifically, when a user inputs information about a traffic accident, the emotion engine recognizes the user's emotions. For example, if the user is feeling strong anger or sadness, the emotion engine recognizes the emotion and takes it into account when calculating the amount of compensation. This makes it possible to calculate a more appropriate amount of compensation that also takes into account the emotional damage of the user.

[1862] The process flow of each embodiment will be described below.

[1863] "Example 1"

[1864] Step 1: The user enters information about a traffic accident into the system, including details of the accident, the condition of the victims, the extent of damage, etc.

[1865] Step 2: The emotion engine works to recognize emotions from the user's tone of voice, facial expressions, choice of words, etc. This emotion recognition is done from the tone of voice, facial expressions, choice of words, etc. when the user enters information.

[1866] Step 3: If the emotion recognized is a strong emotion such as anger or sadness, the amount of compensation will be calculated taking that emotion into account. Specifically, a certain amount will be added or multiplied to the amount of compensation depending on the strength and type of emotion.

[1867] Step 4: The calculated amount of compensation is presented to the user. At this time, the emotion engine's emotion recognition results and their impact are clearly indicated to ensure transparency to the user.

[1868] Example 1

[1869] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1870] Conventional traffic accident compensation standard judgment systems calculate the amount of compensation based on information about the traffic accident, but since they do not take into account the emotional damage of the user, it is difficult to calculate an appropriate amount of compensation. In addition, it can take time to read and analyze information about traffic accidents, which is insufficient in situations where a quick response is required.

[1871] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1872] In this invention, the server includes a means for performing a simplified judgment of the traffic accident compensation standard using AI, a means for reading information about the traffic accident, a means for calculating the amount of compensation based on the read information, a means for recognizing the user's emotions, and a means for adjusting the calculation of the amount of compensation based on the recognized emotions. This enables a more appropriate calculation of the amount of compensation that takes into account the emotional damage of the user.

[1873] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence to lea...

Claims

1. A means for receiving information on the location, time, vehicle speed, and impact force of a traffic accident by acquiring data obtained from a vehicle sensor and a camera, and analyzing the data to generate detailed information on the traffic accident; a means for generating a prompt sentence for instructing calculation of the amount of compensation for damages based on the generated detailed information on the traffic accident and the insurance contract information; A means for calculating the amount of compensation for the traffic accident using the generated prompt sentence, the traffic accident compensation standard, and the generation AI model; A means for notifying the user of the amount of damages assessed; and A system including:

2. The means for calculating the amount of damages is to use the civil traffic accident litigation damages calculation standards to calculate the amount of damages; The system of claim 1 .

3. The system according to claim 1 , wherein users who have voluntary automobile insurance are subject to calculation of the amount of damages.

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