System

Abstract

A system is provided.SOLUTION: This system is provided with a means for receiving information related with a daily trouble inputted by a user, a means for presenting questions corresponding to the kind of the trouble to the user, a means for collecting and storing answers from the user, a means for retrieving a database based on the collected information, and for selecting a proper solution, and a means for presenting the selected solution to the user.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 an instruction sentence related to a description of 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] When faced with various troubles that arise in daily life, it is often unclear how to deal with them or where to seek advice. Information on the Internet in particular can be unreliable, and acting on incorrect information can exacerbate the problem. Furthermore, when legal advice is needed, people often do not know which specialized institution to consult. A reliable consultation system is needed to resolve these issues. [Means for solving the problem]

[0005] This invention provides a system that receives information about daily life problems entered by users, presents questions according to the type of problem, and collects and stores the user's responses. Furthermore, it searches a database based on the collected information, selects appropriate solutions from past cases and legal perspectives, and presents them to the user, providing appropriate solutions and consultations based on reliable information. The database includes reliable information sources such as law firm documents, court records, and insurance policies, and natural language processing technology is used to generate questions, enabling more accurate information collection.

[0006] "User" refers to an individual or organization that uses this system and is the entity that inputs information about a problem.

[0007] "Troubles in daily life" refers to unexpected problems and conflicts that occur in daily life, including bicycle accidents, damage caused by pets, and neighborhood disputes.

[0008] "Means for receiving information" refers to a system component for obtaining trouble-related information entered by a user.

[0009] The "means for presenting questions" refers to a system component that displays questions to the user to request further information based on the received trouble information.

[0010] "Collection and storage means" refers to the system components that efficiently collect and store user responses.

[0011] A "database" refers to a data store containing reliable information such as case history, legal advice, and insurance policies.

[0012] "Means for searching the database and selecting the appropriate solution" refers to the system component that queries the database based on the collected information to find the best solution to the user's problem.

[0013] "Means for presenting solutions to users" refers to the system components that clearly display the selected solutions to users.

[0014] "Law firm materials" refers to documents containing legal advice or information about past legal actions.

[0015] "Court records" refers to data that includes records of past court cases and the content of court decisions.

[0016] "Terms and conditions of insurance" means the document relating to the terms and conditions set out in an insurance contract.

[0017] "Natural language processing technology" refers to technology that mechanically analyzes, understands, and generates human language, and is used to automatically generate questions. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 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. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 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. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 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. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single 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), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] 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.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] 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. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] 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.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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.

[0032] 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 (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. 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 process 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.

[0036] 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.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. 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.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. 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."

[0039] This invention is a consultation system for dealing with various troubles that occur in daily life. This system presents reliable solutions based on information about the trouble entered by the user. The basic flow of the system is explained below.

[0040] System Overview

[0041] The system mainly consists of the following components:

[0042] 1. User Device

[0043] 2. Server

[0044] 3. Database

[0045] Program processing flow

[0046] User device behavior

[0047] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[0048] Server Operation

[0049] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. The server also collects and stores the user's answers, searches the database based on that information, and selects the optimal solution based on the search results and presents it to the user.

[0050] The role of the database

[0051] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[0052] Program processing example

[0053] The operation of the system will be explained below using a specific example of a problem.

[0054] Example: A child hits an elderly person on a bicycle and injures them.

[0055] 1. User device operation

[0056] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[0057] The user terminal transmits this information to the server.

[0058] 2. Server Operation

[0059] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[0060] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[0061] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[0062] 3. Server Data Processing

[0063] The server organizes and stores the collected information and queries the database based on that information.

[0064] The server analyzes the results from the database and selects the most appropriate solution.

[0065] 4. Server Solution Presentation

[0066] The server generates a selected solution and presents it to the user: "Promptly administer first aid to the victim and seek appropriate medical attention at a hospital. Next, report the accident to the police and don't forget to notify your insurance company. We also recommend that you consult a law firm."

[0067] Key Details

[0068] Each component of the system works together to quickly and reliably provide optimal solutions to problems users face. The database contains a wealth of past cases, and natural language processing technology is used to accurately analyze and respond to user input. This system configuration allows users to receive reliable advice and respond calmly.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[0072] Step 2:

[0073] The terminal transmits the input information to the server, which includes details of the problem.

[0074] Step 3:

[0075] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[0076] Step 4:

[0077] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[0078] Step 5:

[0079] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[0080] Step 6:

[0081] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[0082] Step 7:

[0083] The device sends the user's response to the server, which includes detailed information about the accident.

[0084] Step 8:

[0085] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[0086] Step 9:

[0087] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[0088] Step 10:

[0089] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[0090] Step 11:

[0091] The server summarizes the selected solution in an easy-to-understand format and sends it to the web terminal. The summarized solution includes specific steps.

[0092] Step 12:

[0093] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[0094] Example 1

[0095] Next, a description will be given of 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."

[0096] Nowadays, many people face various problems in their daily lives. These problems range from legal issues to traffic accidents and insurance claims, and it is difficult to find an appropriate solution quickly and accurately. To deal with such situations, a system that can efficiently present reliable solutions is needed.

[0097] 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.

[0098] In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for analyzing the received trouble information and identifying the type of trouble, means for generating questions according to the type of trouble and presenting them to the user, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, and means for presenting the selected solution to the user. This makes it possible to provide quick and accurate solutions to the troubles that users face.

[0099] A "user terminal" is a device that allows a user to input information about troubles in their daily lives and communicate with the server.

[0100] The "server" is a device that analyzes received trouble information, generates necessary questions, collects and organizes responses from users, and selects and presents appropriate solutions.

[0101] A "database" is a storage device that stores reliable sources of information such as past cases, legal documents, court records, and insurance policies.

[0102] "Trouble information" is information entered by users about various problems and incidents in their daily lives.

[0103] "Questions" are questions that the server asks the user to gather additional information in order to resolve the issue.

[0104] "Natural language processing technology" is an artificial intelligence technology used to analyze and understand the meaning of trouble information and answers entered by users.

[0105] A "solution" is a proposal for the optimal procedure or countermeasure for a problem, selected from a database based on collected information.

[0106] A "collection means" is a method or device used to store and later analyze responses from users.

[0107] The present invention is a consultation system for helping users deal with various problems they encounter in their daily lives. This system is configured using the following hardware and software.

[0108] System Components

[0109] 1. User Device

[0110] A user terminal is a device that allows a user to input information about a problem and send it to a server. Examples include a PC or smartphone. A web browser or dedicated application is installed on the user terminal, and the user can access the system through this.

[0111] 2. Server

[0112] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. It also collects and stores the user's responses, queries the data against a database, and selects and presents the optimal solution. The server is equipped with a generative AI model incorporating natural language processing (NLP) technology, allowing it to accurately analyze user input.

[0113] 3. Database

[0114] The database contains reliable sources of information such as past cases, legal documents, court records, insurance policies, etc. The server queries this database to find the appropriate solution to the user's problem.

[0115] Program processing

[0116] 1. Information input and analysis

[0117] The user uses the device to input information about the incident. For example, they might input information like, "My child hit an elderly person on his bicycle and injured him." The device then sends this information to the server.

[0118] 2. Question generation and presentation

[0119] The server uses NLP technology to analyze the received accident information and identify the type of accident. It then generates questions to confirm the details of the accident. For example, it presents questions such as "Please tell us the date, time, and location of the accident," "Please tell us the ages and conditions of the victim and assailant," and "Are there any witnesses?"

[0120] 3. Response collection and database search

[0121] Users answer questions posed to them, and their devices send their answers to a server, which then organizes the collected information and queries a database to find relevant past cases and solutions.

[0122] 4. Solution selection and presentation

[0123] The server selects the optimal solution based on the information retrieved from the database. It then sends the solution to the user's device and presents it to the user. For example, it provides specific instructions such as, "Promptly administer first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend consulting a law firm."

[0124] Examples of specific examples and prompts

[0125] Below are some examples and prompts:

[0126] Examples:

[0127] Answers to the questions, "10:00 a.m. on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim suffered a broken arm," and "Yes, other parents and children were watching."

[0128] Example prompt sentence:

[0129] "What should I do if my child hits an elderly person on a bicycle and injures them?"

[0130] "If your household pet is destroying your neighbor's yard, what are the specific steps you can take to fix the problem?"

[0131] The system's components work together to provide accurate and prompt solutions to problems users encounter. By utilizing the abundant information stored in the database and natural language processing technology, users can receive reliable advice.

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Step 1:

[0134] Entering information via user terminal

[0135] The user inputs information about a trouble in their daily life, for example, "A child hit an elderly person on a bicycle and injured them," using a web browser or a dedicated application interface. This information is sent to the server via the API endpoint on the user's device.

[0136] Input: Trouble information entered by the user (e.g., "A child hit an elderly person on a bicycle and injured them")

[0137] Output: Sending trouble information from the terminal to the server

[0138] Step 2:

[0139] Server-based information analysis

[0140] The server analyzes the incident information received from the user's device and uses an NLP model to identify the type of incident and understand its details. For example, it identifies a "bicycle accident" based on the input information.

[0141] Input: Trouble information sent by the user

[0142] Data processing: Analyze information using an NLP model to identify the type and details of the problem

[0143] Output: Analyzed trouble information (e.g. "Bicycle accident")

[0144] Step 3:

[0145] Server-generated questionnaire

[0146] Based on the analyzed incident information, the server generates questions to gather additional information. Generative AI models are used to dynamically create questions, such as "Please tell us the date, time, and location of the accident," or "Please tell us the ages and conditions of the victim and assailant."

[0147] Input: Analyzed trouble information

[0148] Data processing: Question generation using generative AI models

[0149] Output: Generated questionnaire

[0150] Step 4:

[0151] Posting questions and collecting answers on user devices

[0152] The user device receives questions from the server and presents them to the user. The user then inputs answers to these questions. For example, the user can input answers such as "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," or "Yes, another parent and child were watching."

[0153] Input: Questions sent from the server

[0154] Output: User response (e.g., "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," "Yes, another parent and child were watching.")

[0155] Step 5:

[0156] Server collects answers and organizes data

[0157] The server receives the user's responses and organizes and stores them, i.e., converts each response into a format that can be stored in a database, and prepares the database for querying in the next step.

[0158] Input: User response

[0159] Data processing: Organizing responses and converting them into a format suitable for database storage

[0160] Output: Organized response data

[0161] Step 6:

[0162] Server queries database and selects solution

[0163] The server queries the database based on the organized response data to find the appropriate solution. The database contains past cases and materials, and the server selects the optimal solution.

[0164] Input: Organized response data

[0165] Data processing: database queries and result analysis

[0166] Output: Selected solution

[0167] Step 7:

[0168] Server provides solutions

[0169] The server sends the selected solution to the user's device, which then displays it to the user. For example, the device provides specific instructions such as, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0170] Input: Selected Solution

[0171] Output: The solution presented to the user

[0172] (Application example 1)

[0173] Next, a description will be given of Application 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."

[0174] When users of autonomous vehicles encounter problems such as accidents or breakdowns, there is a need for a system that can collect information and provide solutions to respond quickly and accurately. However, currently, there is a lack of means to efficiently collect problem information and quickly provide appropriate instructions to users. In addition, there are few examples of applications that combine situation-specific question generation and natural language processing technology, and comprehensive solution systems are insufficient. Furthermore, there is no database specialized in measures for autonomous vehicles, making it difficult to derive solutions based on specialized information. Improving this situation is a challenge.

[0175] 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.

[0176] In this invention, the server includes means for receiving information about daily life troubles entered by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving responses from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for presenting the selected solution to the user, and means for quickly collecting trouble information when the autonomous vehicle encounters a breakdown or accident, asking for appropriate additional information, and analyzing the collected information. This allows for a prompt and accurate response even when the user encounters trouble with the autonomous vehicle, as the necessary information is quickly collected and appropriate questions and solutions are presented. Furthermore, the use of a specialized database allows for the provision of solutions based on more accurate information.

[0177] A "user terminal" is a device that users use to input information about troubles in their daily lives, such as a smartphone or computer.

[0178] A "server" is a computer system that has the function of analyzing trouble information received from a user terminal, generating appropriate questions, and presenting them to the user.

[0179] The "database" is an information collection system that stores reliable information such as past trouble cases, legal documents, insurance policies, car accident-related information, and repair procedures.

[0180] A "questionnaire" is a series of questions presented to a user to clarify the details of the problem, with the aim of gathering information to provide an appropriate solution.

[0181] "Natural language processing technology" is a technology that allows a machine to understand the text entered by the user and generate appropriate questions and solutions.

[0182] An "autonomous vehicle" is a vehicle that can drive autonomously.

[0183] "Trouble information" is information recorded when an autonomous vehicle encounters a problem such as a breakdown or accident.

[0184] A "solution" is a specific method of dealing with a problem that is presented to the user based on the collected information and database.

[0185] A "prompt" is a sentence that is input into a generative AI model and is used as the basis for deriving appropriate questions and solutions.

[0186] The system for implementing this invention comprises a user terminal, a server, and a database. The user terminal is a device for inputting information about the trouble a user encounters, such as a smartphone or computer. The trouble information input by the user is sent to the server.

[0187] The server is a Python server using the Flask framework that analyzes trouble information received from the user's device. Based on the analysis results, the server identifies the type of trouble and generates appropriate questions to present to the user's device. Natural language processing technology is used to generate the questions, and prompts are used to ask specific and appropriate questions.

[0188] For example, if a self-driving vehicle collides with another vehicle at an intersection, the server generates the following question:

[0189] "What type of accident was it (e.g., car collision, breakdown)?"

[0190] Please tell us the date, time and location of the accident.

[0191] "Please provide details about the victim or perpetrator."

[0192] Once the user answers these questions, the server collects and stores the answers and searches a database to find the optimal solution. The database includes reliable information such as past trouble cases, legal documents, insurance policies, car accident information, and repair procedures. Based on this information, the server selects the optimal solution and displays it on the user's device.

[0193] The specific software and hardware used are as follows:

[0194] Server: Python server using the Flask framework

[0195] Database: SQLite

[0196] Frontend: Smartphone client app

[0197] Data processing and data calculations include steps such as receiving user input, analyzing it, generating questions, collecting and storing answer information, searching a database, and selecting a solution.

[0198] Examples of specific prompts include:

[0199] Accident information: An autonomous vehicle collided with another vehicle at an intersection

[0200] Question 1: What type of accident was it (e.g. car collision, breakdown)?

[0201] Question 2: Please tell us the date, time and location of the accident.

[0202] Question 3: Please provide details about the victim or perpetrator.

[0203] This means that even if a user encounters a problem with an autonomous vehicle, the necessary information will be collected quickly and the appropriate questions and solutions will be presented, enabling a quick and accurate response.In addition, by using a specialized database, solutions can be provided based on more accurate information.

[0204] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0205] Step 1:

[0206] The user uses the device to input trouble information. This information may include, for example, "The autonomous vehicle collided with another vehicle at an intersection." The device receives this input information and sends it to the server.

[0207] Input: Trouble information entered by the user on the device

[0208] Output: Trouble information sent from the device to the server

[0209] Step 2:

[0210] The server analyzes the trouble information received from the device, identifies the type of trouble, and generates appropriate questions. This process uses natural language processing technology to create the necessary prompts.

[0211] Input: Trouble information sent from the device

[0212] Output: Generated questions and prompts

[0213] Specific operation: The server analyzes the trouble information and generates questions such as: "What type of accident was it (e.g., car collision, breakdown)?", "What time and place did the accident occur?", "Please provide details of the victim or perpetrator."

[0214] Step 3:

[0215] The server sends the generated questions to the user's terminal, where the user answers the questions and inputs the answer information.

[0216] Input: Server-generated questionnaire

[0217] Output: Questions presented to the user's device

[0218] Specific operation: The user answers questions on the device and inputs the following information: "Car collision," "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim suffered a broken arm."

[0219] Step 4:

[0220] The user terminal sends the user's answer information to the server, which collects and stores the received answer information.

[0221] Input: Answer information entered by the user on the device

[0222] Output: Answer information sent to the server

[0223] Specific operation: The user terminal sends the answer information to the server, and the server stores the information in a database.

[0224] Step 5:

[0225] The server uses the collected information to search databases, including law firm documents, court records, insurance policies, car accident information, and repair procedures, to find the best solution.

[0226] Input: Answer information saved on the server

[0227] Output: The correct solution retrieved from the database

[0228] What happens: The server queries the database to find and select the most appropriate solution.

[0229] Step 6:

[0230] The server generates the selected solution and presents the information to the user terminal.

[0231] Input: Solutions retrieved from the database

[0232] Output: The solution presented to the user

[0233] Specific operation: The server generates a solution and sends it to the user's device, displaying the following message to the user: "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0234] Furthermore, an emotion engine that estimates the user's emotion may be 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.

[0235] This is a consultation system that provides reliable solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also recognize the user's emotional state and respond accordingly.

[0236] System Overview

[0237] The system consists of the following elements:

[0238] 1. User Device

[0239] 2. Server

[0240] 3. Database

[0241] 4. Emotion Engine

[0242] Program processing flow

[0243] User device behavior

[0244] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[0245] Server Operation

[0246] The server analyzes the trouble information received from the user's device, generates appropriate questions to present to the user, and collects and stores the user's responses, searching the database based on that information to select and present the optimal solution.

[0247] The role of the emotional engine

[0248] The emotion engine analyzes the user's input and responses to identify the user's emotional state. Based on the identified emotional state, the server adjusts the wording of the solutions and questions it presents.

[0249] The role of the database

[0250] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[0251] Program processing example

[0252] The operation of the system will be explained below using a specific example of a problem.

[0253] Example: A child hits an elderly person on a bicycle and injures them.

[0254] 1. User device operation

[0255] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[0256] The user terminal transmits this information to the server.

[0257] 2. Server Operation

[0258] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[0259] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[0260] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[0261] 3. Operation of the Emotion Engine

[0262] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[0263] The emotion engine reports the user's emotional state to the server.

[0264] 4. Server Data Processing

[0265] The server also takes into account information from the emotion engine when deciding how to respond to the user. For example, if a user is feeling anxious, the server will ask questions and give advice in a gentle and polite manner.

[0266] The server then generates a query to search the database based on the user's response information.

[0267] 5. Querying the Server

[0268] The server uses the generated query to search databases, which may include law firm files, court records, and insurance policies.

[0269] 6. Server Solution Selection

[0270] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[0271] The way solutions are presented is also adjusted based on the results of the emotion engine's analysis of user emotions.

[0272] 7. Server Solution Proposal

[0273] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps.

[0274] For example, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0275] Key Details

[0276] This system recognizes the user's emotions and adjusts its response accordingly, providing more appropriate and reliable support. The built-in emotion engine allows users to receive specific and appropriate advice to help them stay calm. The database contains a wealth of past cases, and natural language processing technology enables accurate analysis and response of user input.

[0277] The processing flow will be explained below.

[0278] Step 1:

[0279] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[0280] Step 2:

[0281] The terminal transmits the input information to the server, which includes details of the problem.

[0282] Step 3:

[0283] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[0284] Step 4:

[0285] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[0286] Step 5:

[0287] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[0288] Step 6:

[0289] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[0290] Step 7:

[0291] The device sends the user's response to the server, which includes detailed information about the accident.

[0292] Step 8:

[0293] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[0294] Step 9:

[0295] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[0296] Step 10:

[0297] The emotion engine reports the identified emotional state to the server, so that the server can take the emotional state into account.

[0298] Step 11:

[0299] The server takes into account the information from the emotion engine and decides how to respond to the user. For example, if a user feels anxious, it will ask questions and give advice in a gentle and polite manner.

[0300] Step 12:

[0301] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[0302] Step 13:

[0303] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[0304] Step 14:

[0305] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps. For example, "Promptly administer first aid to the victim and have them receive appropriate medical treatment at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0306] Step 15:

[0307] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[0308] Example 2

[0309] Next, a description will be given of 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."

[0310] In modern life, providing users with quick and appropriate solutions to the various problems they face is a major challenge. Providing an appropriate response can be particularly difficult depending on the specific nature of the problem and the user's emotional state. Conventional systems often provide only bureaucratic information without considering the user's emotions, so there is a need for a system that provides user-friendly and reliable solutions.

[0311] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving information about troubles in daily life input by the user, a means for presenting the user with questions according to the type of trouble, a means for collecting and saving answers from the user, a means for searching a database based on the collected information and selecting an appropriate solution, a means for identifying the emotional state of the user using an emotion analysis engine, and a means for adjusting questions to the user and solutions based on the identified emotional state. This allows a reliable solution according to the user's emotional state to be quickly provided, allowing the user to deal with the problem more calmly.

[0312] "Information entered by users regarding troubles in daily life" refers to details of problems and annoyances related to daily life that users enter using their own devices.

[0313] "Questions according to the type of problem" are questions that are automatically generated to collect necessary additional information based on the problem information entered by the user.

[0314] "Means for collecting and storing answers from users" refers to a function that receives answers entered by users to questions presented to them and stores them in storage such as a database.

[0315] "Means of searching the database and selecting the appropriate solution" is the process of searching related information in the database based on the collected information and finding the optimal solution.

[0316] "Means for presenting the selected solution to the user" refers to a function that sends the optimal solution selected through a database search to the user's terminal and displays it.

[0317] An "emotion analysis engine" is a software engine that analyzes user input and identifies the user's emotional state (e.g., anxiety, fear, joy, etc.).

[0318] "Means for adjusting questions and solutions to the user based on the identified emotional state" refers to a function that changes the wording of the questions and solutions presented to the user, taking into account the emotional state of the user identified by the emotion analysis engine.

[0319] "Natural language processing technology" refers to technology for analyzing and understanding natural language text entered by a user, and examples include text classification, sentiment analysis, and name recognition.

[0320] This invention is a consultation system that provides quick and appropriate solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also analyze the user's emotional state and respond accordingly. The system consists of a user terminal, a server, a database, and an emotion analysis engine.

[0321] System Components

[0322] 1. User terminal: Provides an interface for users to enter trouble information. Specifically, it is provided in the form of a web page or mobile application, and sends the information entered by the user to the server.

[0323] 2. Server: Receives and analyzes the trouble information. In particular, the server uses natural language processing technology to determine the nature of the trouble and generate appropriate questions. Examples of natural language processing technology used include SpaCy and NLTK. The server also collects and stores responses from users and searches a database based on that information.

[0324] 3. Database: Stores reliable sources of information such as past cases, legal documents, court information, insurance policies, etc. The server queries this database to find the best solution.

[0325] 4. Sentiment analysis engine: Analyzes the user's input and responses to identify their emotional state (anxiety, fear, joy, etc.). The sentiment analysis engine uses IBM Watson Tone Analyzer and Microsoft Azure Text Analytics.

[0326] Program operation explanation

[0327] 1. User device operation: The user is presented with a form to enter details of the incident, and the data is sent to the server. For example, the user might enter, "My child hit an elderly person on his bicycle and injured him."

[0328] 2. Server operation:

[0329] Analyze trouble information to determine the type of accident and the characteristics of those involved.

[0330] Generate appropriate questions and present them to the user.

[0331] 3. Collecting user responses: The user enters answers to questions presented to them, such as "date, time and location of the accident," "age and condition of the victim and assailant," and "whether there were any witnesses."

[0332] 4. Sentiment analysis engine operation: Analyzes the user's input and answers to identify their emotional state. For example, if the user is feeling anxious, it reports that emotional state to the server.

[0333] 5. Database search: The server searches the database based on the user's answers and emotional information and selects the optimal solution.

[0334] 6. Emotional adjustment of the solution: Based on the results of the emotion analysis engine, the way the solution is expressed is adjusted, for example, to use gentler and more polite language.

[0335] 7. Solution Presentation: The server sends the selected solution to the user's device and presents it to the user, showing specific steps and next actions to take.

[0336] Prompt sentence examples

[0337] "What should you do if your child hits an elderly person on a bicycle and injures them?"

[0338] Specific examples

[0339] For example, if a user types into their device, "At 10:00 AM on October 10, 2023, a 10-year-old child hit a 70-year-old man on a park's bicycle path, breaking his arm," the server receives and analyzes this information. Detailed questions, such as the date, time, and location of the accident, the ages and conditions of the victim and assailant, and whether there were any witnesses, are then generated and presented to the user. When the user answers these questions, the system searches a database based on the user's answers and presents optimal solutions, such as first aid, reporting the incident to the police, contacting an insurance company, or consulting a law firm. Furthermore, if the emotion analysis engine determines that the user's emotions are unstable, the solution is adjusted to be more polite and reassuring.

[0340] As described above, the system of the present invention provides a quick and appropriate response while taking the user's feelings into consideration, thereby realizing more reliable support for the user.

[0341] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0342] Step 1:

[0343] Input: The user enters details of the problem into the terminal.

[0344] How it works: The user opens the device and inputs information about a problem in their daily life, such as "A child hit an elderly person on a bicycle and injured him." The device receives this information and sends it to the server in a format.

[0345] Output: Trouble information is sent from the terminal to the server.

[0346] Step 2:

[0347] Input: The server receives the trouble information sent by the user.

[0348] How it works: The server uses natural language processing techniques (e.g., SpaCy, NLTK) to analyze the received trouble information and identify the type of trouble and its key elements.

[0349] Output: The type of problem and the identified elements are stored on the server.

[0350] Step 3:

[0351] Input: Type of trouble analyzed and key factors.

[0352] How it works: Based on the type of problem identified, the server automatically generates questions to gather additional information. This can be done using a rule-based or template-based approach.

[0353] Output: The generated questionnaires are stored in the server.

[0354] Step 4:

[0355] Input: The generated questionnaire.

[0356] Operation: The server sends the generated questionnaire to the user's terminal and presents the questionnaire to the user.

[0357] Output: The questionnaire is displayed on the user's terminal.

[0358] Step 5:

[0359] Input: The user answers the questions posed.

[0360] How it works: The user answers questions by entering specific details, such as "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching." The device then sends these answers to the server.

[0361] Output: Answer information is sent from the user terminal to the server.

[0362] Step 6:

[0363] Input: User response information.

[0364] How it works: The server analyzes the received user responses and inputs them into a sentiment analysis engine, which uses tools such as IBM Watson Tone Analyzer and Microsoft Azure Text Analytics to identify the user's emotional state.

[0365] Output: The identified emotional state is stored in the server.

[0366] Step 7:

[0367] Input: User response information and emotional state from the sentiment analysis engine.

[0368] How it works: The server generates a query for database search based on the response information and emotional state. The query is formulated as an SQL statement or a NoSQL query.

[0369] Output: The generated queries are stored in the server.

[0370] Step 8:

[0371] Input: The generated query.

[0372] How it works: The server runs the generated query against a database to retrieve relevant information, such as legal documents, court information, and insurance policies.

[0373] Output: The relevant information is returned to the server.

[0374] Step 9:

[0375] Input: Relevant information returned from the database.

[0376] How it works: The server analyzes the relevant information it has obtained and selects an appropriate solution to the user's problem, such as "first aid," "reporting to the police," "contacting your insurance company," or "consulting a law firm."

[0377] Output: The selected solution is stored in the server.

[0378] Step 10:

[0379] Input: Selected solution and emotional state from the sentiment analysis engine.

[0380] How it works: The server adjusts the way the solution is phrased based on the user's emotional state. If the user is feeling anxious, the solution is phrased more gently and politely.

[0381] Output: The adjusted solution is stored in the server.

[0382] Step 11:

[0383] Input: Adjusted solution.

[0384] Operation: The server sends the final solution to the user's terminal and presents it to the user.

[0385] Output: The adjusted solution is displayed on the user's terminal.

[0386] (Application example 2)

[0387] Next, a description will be given of Application 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."

[0388] This invention is a consultation system that provides fast and reliable solutions to purchase-related problems and questions when users are searching for products on an online shopping site. However, current systems often cause dissatisfaction and anxiety because they are unable to respond appropriately while taking into account the user's emotional state. Furthermore, they do not fully utilize data such as past support cases and order history, making it difficult to provide optimal solutions.

[0389] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for analyzing the user's emotional state, and means for adjusting the way the solution is presented based on the analyzed emotional state. This enables an appropriate response according to the user's emotional state and makes it possible to provide a quick and reliable solution.

[0390] "Means for receiving information entered by users about troubles in daily life" refers to an interface or function that allows users to enter information about troubles or questions they have encountered and for the system to receive that information.

[0391] "Means for presenting questions to the user according to the type of trouble" is a function that automatically generates questions appropriate to the content of the trouble based on the information entered by the user and presents them to the user.

[0392] The "means for collecting and storing responses from users" refers to a system for collecting, recording, and storing responses entered by users to questions presented to them.

[0393] "Means of searching the database based on collected information and selecting an appropriate solution" is a function that uses information collected from the user to search for appropriate information in the database and selects the optimal solution from the results.

[0394] "Means for analyzing a user's emotional state" refers to an algorithm or system that analyzes a user's input and responses to identify their current emotional state.

[0395] The "means for adjusting the way in which a solution is presented based on the analyzed emotional state" is a function that changes the presentation of the solution provided depending on the user's emotional state, thereby providing a more appropriate and reassuring response.

[0396] "Law firm documents, court records, insurance policies, past order history, delivery status, and support case studies" are a wide range of data sources that are referenced when selecting solutions and provide reliable responses to user problems.

[0397] This is a consultation system that provides quick and reliable solutions to problems and questions about purchases when users are searching for products on online shopping sites. The system is composed of elements such as a user terminal, a server, a database, and a sentiment analysis engine.

[0398] System configuration

[0399] 1. User Device

[0400] The user terminal is a mobile device such as a smartphone or tablet, and provides an interface for users to input information about the problem. Users access the system by inputting information about their purchase or problem.

[0401] 2. Server

[0402] The server receives and analyzes information entered by users. Specifically, it generates questions based on the user's trouble information and presents them to the user. It also collects and stores the user's responses, uses this information to search a database, and selects the appropriate solution.

[0403] 3. Database

[0404] The database contains law firm documents, court records, insurance policies, as well as past order history, delivery status, support case studies, etc. The server searches this database to find the best solution for the user's problem.

[0405] 4. Sentiment Analysis Engine

[0406] The emotion analysis engine analyzes the user's input and identifies their emotional state. Based on the detected emotional state, the server adjusts its response to the user and presents a solution expression appropriate to the user's emotional state.

[0407] Implementation example

[0408] User device behavior

[0409] The user uses their smartphone to input information about the problem of not receiving the purchased product, and the user's device sends this information to the server.

[0410] Server Operation

[0411] The server analyzes the trouble information received from the user and identifies the type of trouble. For example, it determines that the product has not arrived, and generates questions to present to the user. Specific examples of questions include, "What is your order number?" and "When is the product expected to arrive?" When the user answers these questions, the information is collected and stored.

[0412] How the sentiment analysis engine works

[0413] The emotion analysis engine analyzes and identifies the user's emotional state from their input. For example, it may detect that the user is feeling anxious or irritated. The emotion analysis engine provides this information to the server, which then determines how to respond based on the user's emotional state.

[0414] Server data processing

[0415] The server searches a database based on the user's response information and emotional state to select an appropriate solution. The database includes information such as past order history, delivery status, and support case studies, so specific and reliable solutions can be obtained.

[0416] Proposing a solution

[0417] The selected solution is then presented to the user in a way that eases their concerns, such as, "Order number 123456 is currently on its way. If you do not receive your order within one week of the expected delivery date of October 15, 2023, please contact customer support. Additional notifications can be found within the app."

[0418] Specific prompts include "What is your order number?" and "When is the expected delivery date?"

[0419] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0420] Step 1:

[0421] The user device receives input information from the user. Specifically, the user enters details about the problem into the smartphone interface. For example, the input information, such as "The purchased product has not arrived," is sent to the server. The input at this stage is the details of the problem, and the output is the transmission of the problem information to the server.

[0422] Step 2:

[0423] The server analyzes the trouble information received from the user. The server uses natural language processing technology to analyze the input text and identify the type of trouble. In this step, the input trouble information is analyzed and the trouble category, for example, "item not delivered," is clarified. The output is the generation of questions based on the type of trouble.

[0424] Step 3:

[0425] The server generates questions according to the type of problem identified and sends them to the user's device. A generative AI model is used to generate specific questions. For example, questions such as "What is your order number?" or "When is the expected delivery date for the product?" are generated. The input for this step is the type of problem, and the output is the specific questions.

[0426] Step 4:

[0427] The user terminal presents the generated questions to the user and accepts the user's answers. The user inputs answers to the presented questions. For example, the user might input answers such as "The order number is 123456" or "The product is scheduled to arrive on October 15, 2023." The input at this stage is the answer to the questions, and the output is the transmission of the answer information to the server.

[0428] Step 5:

[0429] The server collects and stores the answers received from the user. Here, the user's answer data is stored in a database and the necessary information is extracted. The input of this step is the user's answer information, and the output is storage in the database.

[0430] Step 6:

[0431] The server searches the database based on the collected information and selects an appropriate solution. The server queries the database for past cases and related information to identify the optimal solution. The input for this step is the user's response information and the contents of the database, and the output is the selection of a solution.

[0432] Step 7:

[0433] The emotion analysis engine analyzes the user's emotional state. The server uses the emotion analysis engine to identify the user's emotional state from their input and responses. For example, it can detect that the user is feeling anxious or angry. The input for this step is the user's input and responses, and the output is the identified emotional state.

[0434] Step 8:

[0435] The server adjusts the way the solution is presented based on the analyzed emotional state. The server presents the solution in a gentle and polite manner depending on the user's emotional state. For example, the solution is adjusted to be something like, "Don't worry. Order number 123456 is currently being delivered. If you have any questions, please contact customer support." The input of this step is the emotional state and the selected solution, and the output is the presentation of the adjusted solution.

[0436] Step 9:

[0437] The server sends the adjusted solution to the user terminal and presents it to the user. The user terminal displays the adjusted solution, and the user can take action based on it. The input of this step is the adjusted solution, and the output is the solution presented to the user.

[0438] 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 audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio 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 audio data.

[0439] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with 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.

[0440] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0441] [Second embodiment]

[0442] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0443] 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.

[0444] 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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0445] 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.

[0446] 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 audio in accordance with instructions from the processor 46.

[0447] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and 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 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0448] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0449] Fig. 4 shows an example of the 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.

[0450] 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.

[0451] 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.

[0452] 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.

[0453] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0454] This invention is a consultation system for dealing with various troubles that occur in daily life. This system presents reliable solutions based on information about the trouble entered by the user. The basic flow of the system is explained below.

[0455] System Overview

[0456] The system mainly consists of the following components:

[0457] 1. User Device

[0458] 2. Server

[0459] 3. Database

[0460] Program processing flow

[0461] User device behavior

[0462] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[0463] Server Operation

[0464] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. The server also collects and stores the user's answers, searches the database based on that information, and selects the optimal solution based on the search results and presents it to the user.

[0465] The role of the database

[0466] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[0467] Program processing example

[0468] The operation of the system will be explained below using a specific example of a problem.

[0469] Example: A child hits an elderly person on a bicycle and injures them.

[0470] 1. User device operation

[0471] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[0472] The user terminal transmits this information to the server.

[0473] 2. Server Operation

[0474] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[0475] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[0476] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[0477] 3. Server Data Processing

[0478] The server organizes and stores the collected information and queries the database based on that information.

[0479] The server analyzes the results from the database and selects the most appropriate solution.

[0480] 4. Server Solution Presentation

[0481] The server generates a selected solution and presents it to the user: "Promptly administer first aid to the victim and seek appropriate medical attention at a hospital. Next, report the accident to the police and don't forget to notify your insurance company. We also recommend that you consult a law firm."

[0482] Key Details

[0483] Each component of the system works together to quickly and reliably provide optimal solutions to problems users face. The database contains a wealth of past cases, and natural language processing technology is used to accurately analyze and respond to user input. This system configuration allows users to receive reliable advice and respond calmly.

[0484] The processing flow will be explained below.

[0485] Step 1:

[0486] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[0487] Step 2:

[0488] The terminal transmits the input information to the server, which includes details of the problem.

[0489] Step 3:

[0490] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[0491] Step 4:

[0492] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[0493] Step 5:

[0494] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[0495] Step 6:

[0496] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[0497] Step 7:

[0498] The device sends the user's response to the server, which includes detailed information about the accident.

[0499] Step 8:

[0500] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[0501] Step 9:

[0502] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[0503] Step 10:

[0504] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[0505] Step 11:

[0506] The server summarizes the selected solution in an easy-to-understand format and sends it to the web terminal. The summarized solution includes specific steps.

[0507] Step 12:

[0508] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[0509] Example 1

[0510] Next, a description will be given of 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."

[0511] Nowadays, many people face various problems in their daily lives. These problems range from legal issues to traffic accidents and insurance claims, and it is difficult to find an appropriate solution quickly and accurately. To deal with such situations, a system that can efficiently present reliable solutions is needed.

[0512] 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.

[0513] In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for analyzing the received trouble information and identifying the type of trouble, means for generating questions according to the type of trouble and presenting them to the user, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, and means for presenting the selected solution to the user. This makes it possible to provide quick and accurate solutions to the troubles that users face.

[0514] A "user terminal" is a device that allows a user to input information about troubles in their daily lives and communicate with the server.

[0515] The "server" is a device that analyzes received trouble information, generates necessary questions, collects and organizes responses from users, and selects and presents appropriate solutions.

[0516] A "database" is a storage device that stores reliable sources of information such as past cases, legal documents, court records, and insurance policies.

[0517] "Trouble information" is information entered by users about various problems and incidents in their daily lives.

[0518] "Questions" are questions that the server asks the user to gather additional information in order to resolve the issue.

[0519] "Natural language processing technology" is an artificial intelligence technology used to analyze and understand the meaning of trouble information and answers entered by users.

[0520] A "solution" is a proposal for the optimal procedure or countermeasure for a problem, selected from a database based on collected information.

[0521] A "collection means" is a method or device used to store and later analyze responses from users.

[0522] The present invention is a consultation system for helping users deal with various problems they encounter in their daily lives. This system is configured using the following hardware and software.

[0523] System Components

[0524] 1. User Device

[0525] A user terminal is a device that allows a user to input information about a problem and send it to a server. Examples include a PC or smartphone. A web browser or dedicated application is installed on the user terminal, and the user can access the system through this.

[0526] 2. Server

[0527] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. It also collects and stores the user's responses, queries the data against a database, and selects and presents the optimal solution. The server is equipped with a generative AI model incorporating natural language processing (NLP) technology, allowing it to accurately analyze user input.

[0528] 3. Database

[0529] The database contains reliable sources of information such as past cases, legal documents, court records, insurance policies, etc. The server queries this database to find the appropriate solution to the user's problem.

[0530] Program processing

[0531] 1. Information input and analysis

[0532] The user uses the device to input information about the incident. For example, they might input information like, "My child hit an elderly person on his bicycle and injured him." The device then sends this information to the server.

[0533] 2. Question generation and presentation

[0534] The server uses NLP technology to analyze the received accident information and identify the type of accident. It then generates questions to confirm the details of the accident. For example, it presents questions such as "Please tell us the date, time, and location of the accident," "Please tell us the ages and conditions of the victim and assailant," and "Are there any witnesses?"

[0535] 3. Response collection and database search

[0536] Users answer questions posed to them, and their devices send their answers to a server, which then organizes the collected information and queries a database to find relevant past cases and solutions.

[0537] 4. Solution selection and presentation

[0538] The server selects the optimal solution based on the information retrieved from the database. It then sends the solution to the user's device and presents it to the user. For example, it provides specific instructions such as, "Promptly administer first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend consulting a law firm."

[0539] Examples of specific examples and prompts

[0540] Below are some examples and prompts:

[0541] Examples:

[0542] Answers to the questions, "10:00 a.m. on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim suffered a broken arm," and "Yes, other parents and children were watching."

[0543] Example prompt sentence:

[0544] "What should I do if my child hits an elderly person on a bicycle and injures them?"

[0545] "If your household pet is destroying your neighbor's yard, what are the specific steps you can take to fix the problem?"

[0546] The system's components work together to provide accurate and prompt solutions to problems users encounter. By utilizing the abundant information stored in the database and natural language processing technology, users can receive reliable advice.

[0547] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0548] Step 1:

[0549] Entering information via user terminal

[0550] The user inputs information about a trouble in their daily life, for example, "A child hit an elderly person on a bicycle and injured them," using a web browser or a dedicated application interface. This information is sent to the server via the API endpoint on the user's device.

[0551] Input: Trouble information entered by the user (e.g., "A child hit an elderly person on a bicycle and injured them")

[0552] Output: Sending trouble information from the terminal to the server

[0553] Step 2:

[0554] Server-based information analysis

[0555] The server analyzes the incident information received from the user's device and uses an NLP model to identify the type of incident and understand its details. For example, it identifies a "bicycle accident" based on the input information.

[0556] Input: Trouble information sent by the user

[0557] Data processing: Analyze information using an NLP model to identify the type and details of the problem

[0558] Output: Analyzed trouble information (e.g. "Bicycle accident")

[0559] Step 3:

[0560] Server-generated questionnaire

[0561] Based on the analyzed incident information, the server generates questions to gather additional information. Generative AI models are used to dynamically create questions, such as "Please tell us the date, time, and location of the accident," or "Please tell us the ages and conditions of the victim and assailant."

[0562] Input: Analyzed trouble information

[0563] Data processing: Question generation using generative AI models

[0564] Output: Generated questionnaire

[0565] Step 4:

[0566] Posting questions and collecting answers on user devices

[0567] The user device receives questions from the server and presents them to the user. The user then inputs answers to these questions. For example, the user can input answers such as "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," or "Yes, another parent and child were watching."

[0568] Input: Questions sent from the server

[0569] Output: User response (e.g., "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," "Yes, another parent and child were watching.")

[0570] Step 5:

[0571] Server collects answers and organizes data

[0572] The server receives the user's responses and organizes and stores them, i.e., converts each response into a format that can be stored in a database, and prepares the database for querying in the next step.

[0573] Input: User response

[0574] Data processing: Organizing responses and converting them into a format suitable for database storage

[0575] Output: Organized response data

[0576] Step 6:

[0577] Server queries database and selects solution

[0578] The server queries the database based on the organized response data to find the appropriate solution. The database contains past cases and materials, and the server selects the optimal solution.

[0579] Input: Organized response data

[0580] Data processing: database queries and result analysis

[0581] Output: Selected solution

[0582] Step 7:

[0583] Server provides solutions

[0584] The server sends the selected solution to the user's device, which then displays it to the user. For example, the device provides specific instructions such as, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0585] Input: Selected Solution

[0586] Output: The solution presented to the user

[0587] (Application example 1)

[0588] Next, a description will be given of Application 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."

[0589] When users of autonomous vehicles encounter problems such as accidents or breakdowns, there is a need for a system that can collect information and provide solutions to respond quickly and accurately. However, currently, there is a lack of means to efficiently collect problem information and quickly provide appropriate instructions to users. In addition, there are few examples of applications that combine situation-specific question generation and natural language processing technology, and comprehensive solution systems are insufficient. Furthermore, there is no database specialized in measures for autonomous vehicles, making it difficult to derive solutions based on specialized information. Improving this situation is a challenge.

[0590] 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.

[0591] In this invention, the server includes means for receiving information about daily life troubles entered by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving responses from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for presenting the selected solution to the user, and means for quickly collecting trouble information when the autonomous vehicle encounters a breakdown or accident, asking for appropriate additional information, and analyzing the collected information. This allows for a prompt and accurate response even when the user encounters trouble with the autonomous vehicle, as the necessary information is quickly collected and appropriate questions and solutions are presented. Furthermore, the use of a specialized database allows for the provision of solutions based on more accurate information.

[0592] A "user terminal" is a device that users use to input information about troubles in their daily lives, such as a smartphone or computer.

[0593] A "server" is a computer system that has the function of analyzing trouble information received from a user terminal, generating appropriate questions, and presenting them to the user.

[0594] The "database" is an information collection system that stores reliable information such as past trouble cases, legal documents, insurance policies, car accident-related information, and repair procedures.

[0595] A "questionnaire" is a series of questions presented to a user to clarify the details of the problem, with the aim of gathering information to provide an appropriate solution.

[0596] "Natural language processing technology" is a technology that allows a machine to understand the text entered by the user and generate appropriate questions and solutions.

[0597] An "autonomous vehicle" is a vehicle that can drive autonomously.

[0598] "Trouble information" is information recorded when an autonomous vehicle encounters a problem such as a breakdown or accident.

[0599] A "solution" is a specific method of dealing with a problem that is presented to the user based on the collected information and database.

[0600] A "prompt" is a sentence that is input into a generative AI model and is used as the basis for deriving appropriate questions and solutions.

[0601] The system for implementing this invention comprises a user terminal, a server, and a database. The user terminal is a device for inputting information about the trouble a user encounters, such as a smartphone or computer. The trouble information input by the user is sent to the server.

[0602] The server is a Python server using the Flask framework that analyzes trouble information received from the user's device. Based on the analysis results, the server identifies the type of trouble and generates appropriate questions to present to the user's device. Natural language processing technology is used to generate the questions, and prompts are used to ask specific and appropriate questions.

[0603] For example, if a self-driving vehicle collides with another vehicle at an intersection, the server generates the following question:

[0604] "What type of accident was it (e.g., car collision, breakdown)?"

[0605] Please tell us the date, time and location of the accident.

[0606] "Please provide details about the victim or perpetrator."

[0607] Once the user answers these questions, the server collects and stores the answers and searches a database to find the optimal solution. The database includes reliable information such as past trouble cases, legal documents, insurance policies, car accident information, and repair procedures. Based on this information, the server selects the optimal solution and displays it on the user's device.

[0608] The specific software and hardware used are as follows:

[0609] Server: Python server using the Flask framework

[0610] Database: SQLite

[0611] Frontend: Smartphone client app

[0612] Data processing and data calculations include steps such as receiving user input, analyzing it, generating questions, collecting and storing answer information, searching a database, and selecting a solution.

[0613] Examples of specific prompts include:

[0614] Accident information: An autonomous vehicle collided with another vehicle at an intersection

[0615] Question 1: What type of accident was it (e.g. car collision, breakdown)?

[0616] Question 2: Please tell us the date, time and location of the accident.

[0617] Question 3: Please provide details about the victim or perpetrator.

[0618] This means that even if a user encounters a problem with an autonomous vehicle, the necessary information will be collected quickly and the appropriate questions and solutions will be presented, enabling a quick and accurate response.In addition, by using a specialized database, solutions can be provided based on more accurate information.

[0619] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0620] Step 1:

[0621] The user uses the device to input trouble information. This information may include, for example, "The autonomous vehicle collided with another vehicle at an intersection." The device receives this input information and sends it to the server.

[0622] Input: Trouble information entered by the user on the device

[0623] Output: Trouble information sent from the device to the server

[0624] Step 2:

[0625] The server analyzes the trouble information received from the device, identifies the type of trouble, and generates appropriate questions. This process uses natural language processing technology to create the necessary prompts.

[0626] Input: Trouble information sent from the device

[0627] Output: Generated questions and prompts

[0628] Specific operation: The server analyzes the trouble information and generates questions such as: "What type of accident was it (e.g., car collision, breakdown)?", "What time and place did the accident occur?", "Please provide details of the victim or perpetrator."

[0629] Step 3:

[0630] The server sends the generated questions to the user's terminal, where the user answers the questions and inputs the answer information.

[0631] Input: Server-generated questionnaire

[0632] Output: Questions presented to the user's device

[0633] Specific operation: The user answers questions on the device and inputs the following information: "Car collision," "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim suffered a broken arm."

[0634] Step 4:

[0635] The user terminal sends the user's answer information to the server, which collects and stores the received answer information.

[0636] Input: Answer information entered by the user on the device

[0637] Output: Answer information sent to the server

[0638] Specific operation: The user terminal sends the answer information to the server, and the server stores the information in a database.

[0639] Step 5:

[0640] The server uses the collected information to search databases, including law firm documents, court records, insurance policies, car accident information, and repair procedures, to find the best solution.

[0641] Input: Answer information saved on the server

[0642] Output: The correct solution retrieved from the database

[0643] What happens: The server queries the database to find and select the most appropriate solution.

[0644] Step 6:

[0645] The server generates the selected solution and presents the information to the user terminal.

[0646] Input: Solutions retrieved from the database

[0647] Output: The solution presented to the user

[0648] Specific operation: The server generates a solution and sends it to the user's device, displaying the following message to the user: "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0649] Furthermore, 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.

[0650] This is a consultation system that provides reliable solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also recognize the user's emotional state and respond accordingly.

[0651] System Overview

[0652] The system consists of the following elements:

[0653] 1. User Device

[0654] 2. Server

[0655] 3. Database

[0656] 4. Emotion Engine

[0657] Program processing flow

[0658] User device behavior

[0659] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[0660] Server Operation

[0661] The server analyzes the trouble information received from the user's device, generates appropriate questions to present to the user, and collects and stores the user's responses, searching the database based on that information to select and present the optimal solution.

[0662] The role of the emotional engine

[0663] The emotion engine analyzes the user's input and responses to identify the user's emotional state. Based on the identified emotional state, the server adjusts the wording of the solutions and questions it presents.

[0664] The role of the database

[0665] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[0666] Program processing example

[0667] The operation of the system will be explained below using a specific example of a problem.

[0668] Example: A child hits an elderly person on a bicycle and injures them.

[0669] 1. User device operation

[0670] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[0671] The user terminal transmits this information to the server.

[0672] 2. Server Operation

[0673] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[0674] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[0675] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[0676] 3. Operation of the Emotion Engine

[0677] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[0678] The emotion engine reports the user's emotional state to the server.

[0679] 4. Server Data Processing

[0680] The server also takes into account information from the emotion engine when deciding how to respond to the user. For example, if a user is feeling anxious, the server will ask questions and give advice in a gentle and polite manner.

[0681] The server then generates a query to search the database based on the user's response information.

[0682] 5. Querying the Server

[0683] The server uses the generated query to search databases, which may include law firm files, court records, and insurance policies.

[0684] 6. Server Solution Selection

[0685] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[0686] The way solutions are presented is also adjusted based on the results of the emotion engine's analysis of user emotions.

[0687] 7. Server Solution Proposal

[0688] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps.

[0689] For example, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0690] Key Details

[0691] This system recognizes the user's emotions and adjusts its response accordingly, providing more appropriate and reliable support. The built-in emotion engine allows users to receive specific and appropriate advice to help them stay calm. The database contains a wealth of past cases, and natural language processing technology enables accurate analysis and response of user input.

[0692] The processing flow will be explained below.

[0693] Step 1:

[0694] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[0695] Step 2:

[0696] The terminal transmits the input information to the server, which includes details of the problem.

[0697] Step 3:

[0698] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[0699] Step 4:

[0700] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[0701] Step 5:

[0702] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[0703] Step 6:

[0704] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[0705] Step 7:

[0706] The device sends the user's response to the server, which includes detailed information about the accident.

[0707] Step 8:

[0708] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[0709] Step 9:

[0710] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[0711] Step 10:

[0712] The emotion engine reports the identified emotional state to the server, so that the server can take the emotional state into account.

[0713] Step 11:

[0714] The server takes into account the information from the emotion engine and decides how to respond to the user. For example, if a user feels anxious, it will ask questions and give advice in a gentle and polite manner.

[0715] Step 12:

[0716] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[0717] Step 13:

[0718] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[0719] Step 14:

[0720] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps. For example, "Promptly administer first aid to the victim and have them receive appropriate medical treatment at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[0721] Step 15:

[0722] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[0723] Example 2

[0724] Next, a description will be given of 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."

[0725] In modern life, providing users with quick and appropriate solutions to the various problems they face is a major challenge. Providing an appropriate response can be particularly difficult depending on the specific nature of the problem and the user's emotional state. Conventional systems often provide only bureaucratic information without considering the user's emotions, so there is a need for a system that provides user-friendly and reliable solutions.

[0726] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving information about troubles in daily life input by the user, a means for presenting the user with questions according to the type of trouble, a means for collecting and saving answers from the user, a means for searching a database based on the collected information and selecting an appropriate solution, a means for identifying the emotional state of the user using an emotion analysis engine, and a means for adjusting questions to the user and solutions based on the identified emotional state. This allows a reliable solution according to the user's emotional state to be quickly provided, allowing the user to deal with the problem more calmly.

[0727] "Information entered by users regarding troubles in daily life" refers to details of problems and annoyances related to daily life that users enter using their own devices.

[0728] "Questions according to the type of problem" are questions that are automatically generated to collect necessary additional information based on the problem information entered by the user.

[0729] "Means for collecting and storing answers from users" refers to a function that receives answers entered by users to questions presented to them and stores them in storage such as a database.

[0730] "Means of searching the database and selecting the appropriate solution" is the process of searching related information in the database based on the collected information and finding the optimal solution.

[0731] "Means for presenting the selected solution to the user" refers to a function that sends the optimal solution selected through a database search to the user's terminal and displays it.

[0732] An "emotion analysis engine" is a software engine that analyzes user input and identifies the user's emotional state (e.g., anxiety, fear, joy, etc.).

[0733] "Means for adjusting questions and solutions to the user based on the identified emotional state" refers to a function that changes the wording of the questions and solutions presented to the user, taking into account the emotional state of the user identified by the emotion analysis engine.

[0734] "Natural language processing technology" refers to technology for analyzing and understanding natural language text entered by a user, and examples include text classification, sentiment analysis, and name recognition.

[0735] This invention is a consultation system that provides quick and appropriate solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also analyze the user's emotional state and respond accordingly. The system consists of a user terminal, a server, a database, and an emotion analysis engine.

[0736] System Components

[0737] 1. User terminal: Provides an interface for users to enter trouble information. Specifically, it is provided in the form of a web page or mobile application, and sends the information entered by the user to the server.

[0738] 2. Server: Receives and analyzes the trouble information. In particular, the server uses natural language processing technology to determine the nature of the trouble and generate appropriate questions. Examples of natural language processing technology used include SpaCy and NLTK. The server also collects and stores responses from users and searches a database based on that information.

[0739] 3. Database: Stores reliable sources of information such as past cases, legal documents, court information, insurance policies, etc. The server queries this database to find the best solution.

[0740] 4. Sentiment analysis engine: Analyzes the user's input and responses to identify their emotional state (anxiety, fear, joy, etc.). The sentiment analysis engine uses IBM Watson Tone Analyzer and Microsoft Azure Text Analytics.

[0741] Program operation explanation

[0742] 1. User device operation: The user is presented with a form to enter details of the incident, and the data is sent to the server. For example, the user might enter, "My child hit an elderly person on his bicycle and injured him."

[0743] 2. Server operation:

[0744] Analyze trouble information to determine the type of accident and the characteristics of those involved.

[0745] Generate appropriate questions and present them to the user.

[0746] 3. Collecting user responses: The user enters answers to questions presented to them, such as "date, time and location of the accident," "age and condition of the victim and assailant," and "whether there were any witnesses."

[0747] 4. Sentiment analysis engine operation: Analyzes the user's input and answers to identify their emotional state. For example, if the user is feeling anxious, it reports that emotional state to the server.

[0748] 5. Database search: The server searches the database based on the user's answers and emotional information and selects the optimal solution.

[0749] 6. Emotional adjustment of the solution: Based on the results of the emotion analysis engine, the way the solution is expressed is adjusted, for example, to use gentler and more polite language.

[0750] 7. Solution Presentation: The server sends the selected solution to the user's device and presents it to the user, showing specific steps and next actions to take.

[0751] Prompt sentence examples

[0752] "What should you do if your child hits an elderly person on a bicycle and injures them?"

[0753] Specific examples

[0754] For example, if a user types into their device, "At 10:00 AM on October 10, 2023, a 10-year-old child hit a 70-year-old man on a park's bicycle path, breaking his arm," the server receives and analyzes this information. Detailed questions, such as the date, time, and location of the accident, the ages and conditions of the victim and assailant, and whether there were any witnesses, are then generated and presented to the user. When the user answers these questions, the system searches a database based on the user's answers and presents optimal solutions, such as first aid, reporting the incident to the police, contacting an insurance company, or consulting a law firm. Furthermore, if the emotion analysis engine determines that the user's emotions are unstable, the solution is adjusted to be more polite and reassuring.

[0755] As described above, the system of the present invention provides a quick and appropriate response while taking the user's feelings into consideration, thereby realizing more reliable support for the user.

[0756] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0757] Step 1:

[0758] Input: The user enters details of the problem into the terminal.

[0759] How it works: The user opens the device and inputs information about a problem in their daily life, such as "A child hit an elderly person on a bicycle and injured him." The device receives this information and sends it to the server in a format.

[0760] Output: Trouble information is sent from the terminal to the server.

[0761] Step 2:

[0762] Input: The server receives the trouble information sent by the user.

[0763] How it works: The server uses natural language processing techniques (e.g., SpaCy, NLTK) to analyze the received trouble information and identify the type of trouble and its key elements.

[0764] Output: The type of problem and the identified elements are stored on the server.

[0765] Step 3:

[0766] Input: Type of trouble analyzed and key factors.

[0767] How it works: Based on the type of problem identified, the server automatically generates questions to gather additional information. This can be done using a rule-based or template-based approach.

[0768] Output: The generated questionnaires are stored in the server.

[0769] Step 4:

[0770] Input: The generated questionnaire.

[0771] Operation: The server sends the generated questionnaire to the user's terminal and presents the questionnaire to the user.

[0772] Output: The questionnaire is displayed on the user's terminal.

[0773] Step 5:

[0774] Input: The user answers the questions posed.

[0775] How it works: The user answers questions by entering specific details, such as "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching." The device then sends these answers to the server.

[0776] Output: Answer information is sent from the user terminal to the server.

[0777] Step 6:

[0778] Input: User response information.

[0779] How it works: The server analyzes the received user responses and inputs them into a sentiment analysis engine, which uses tools such as IBM Watson Tone Analyzer and Microsoft Azure Text Analytics to identify the user's emotional state.

[0780] Output: The identified emotional state is stored in the server.

[0781] Step 7:

[0782] Input: User response information and emotional state from the sentiment analysis engine.

[0783] How it works: The server generates a query for database search based on the response information and emotional state. The query is formulated as an SQL statement or a NoSQL query.

[0784] Output: The generated queries are stored in the server.

[0785] Step 8:

[0786] Input: The generated query.

[0787] How it works: The server runs the generated query against a database to retrieve relevant information, such as legal documents, court information, and insurance policies.

[0788] Output: The relevant information is returned to the server.

[0789] Step 9:

[0790] Input: Relevant information returned from the database.

[0791] How it works: The server analyzes the relevant information it has obtained and selects an appropriate solution to the user's problem, such as "first aid," "reporting to the police," "contacting your insurance company," or "consulting a law firm."

[0792] Output: The selected solution is stored in the server.

[0793] Step 10:

[0794] Input: Selected solution and emotional state from the sentiment analysis engine.

[0795] How it works: The server adjusts the way the solution is phrased based on the user's emotional state. If the user is feeling anxious, the solution is phrased more gently and politely.

[0796] Output: The adjusted solution is stored in the server.

[0797] Step 11:

[0798] Input: Adjusted solution.

[0799] Operation: The server sends the final solution to the user's terminal and presents it to the user.

[0800] Output: The adjusted solution is displayed on the user's terminal.

[0801] (Application example 2)

[0802] Next, a description will be given of Application 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."

[0803] This invention is a consultation system that provides fast and reliable solutions to purchase-related problems and questions when users are searching for products on an online shopping site. However, current systems often cause dissatisfaction and anxiety because they are unable to respond appropriately while taking into account the user's emotional state. Furthermore, they do not fully utilize data such as past support cases and order history, making it difficult to provide optimal solutions.

[0804] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for analyzing the user's emotional state, and means for adjusting the way the solution is presented based on the analyzed emotional state. This enables an appropriate response according to the user's emotional state and makes it possible to provide a quick and reliable solution.

[0805] "Means for receiving information entered by users about troubles in daily life" refers to an interface or function that allows users to enter information about troubles or questions they have encountered and for the system to receive that information.

[0806] "Means for presenting questions to the user according to the type of trouble" is a function that automatically generates questions appropriate to the content of the trouble based on the information entered by the user and presents them to the user.

[0807] The "means for collecting and storing responses from users" refers to a system for collecting, recording, and storing responses entered by users to questions presented to them.

[0808] "Means of searching the database based on collected information and selecting an appropriate solution" is a function that uses information collected from the user to search for appropriate information in the database and selects the optimal solution from the results.

[0809] "Means for analyzing a user's emotional state" refers to an algorithm or system that analyzes a user's input and responses to identify their current emotional state.

[0810] The "means for adjusting the way in which a solution is presented based on the analyzed emotional state" is a function that changes the presentation of the solution provided depending on the user's emotional state, thereby providing a more appropriate and reassuring response.

[0811] "Law firm documents, court records, insurance policies, past order history, delivery status, and support case studies" are a wide range of data sources that are referenced when selecting solutions and provide reliable responses to user problems.

[0812] This is a consultation system that provides quick and reliable solutions to problems and questions about purchases when users are searching for products on online shopping sites. The system is composed of elements such as a user terminal, a server, a database, and a sentiment analysis engine.

[0813] System configuration

[0814] 1. User Device

[0815] The user terminal is a mobile device such as a smartphone or tablet, and provides an interface for users to input information about the problem. Users access the system by inputting information about their purchase or problem.

[0816] 2. Server

[0817] The server receives and analyzes information entered by users. Specifically, it generates questions based on the user's trouble information and presents them to the user. It also collects and stores the user's responses, uses this information to search a database, and selects the appropriate solution.

[0818] 3. Database

[0819] The database contains law firm documents, court records, insurance policies, as well as past order history, delivery status, support case studies, etc. The server searches this database to find the best solution for the user's problem.

[0820] 4. Sentiment Analysis Engine

[0821] The emotion analysis engine analyzes the user's input and identifies their emotional state. Based on the detected emotional state, the server adjusts its response to the user and presents a solution expression appropriate to the user's emotional state.

[0822] Implementation example

[0823] User device behavior

[0824] The user uses their smartphone to input information about the problem of not receiving the purchased product, and the user's device sends this information to the server.

[0825] Server Operation

[0826] The server analyzes the trouble information received from the user and identifies the type of trouble. For example, it determines that the product has not arrived, and generates questions to present to the user. Specific examples of questions include, "What is your order number?" and "When is the product expected to arrive?" When the user answers these questions, the information is collected and stored.

[0827] How the sentiment analysis engine works

[0828] The emotion analysis engine analyzes and identifies the user's emotional state from their input. For example, it may detect that the user is feeling anxious or irritated. The emotion analysis engine provides this information to the server, which then determines how to respond based on the user's emotional state.

[0829] Server data processing

[0830] The server searches a database based on the user's response information and emotional state to select an appropriate solution. The database includes information such as past order history, delivery status, and support case studies, so specific and reliable solutions can be obtained.

[0831] Proposing a solution

[0832] The selected solution is then presented to the user in a way that eases their concerns, such as, "Order number 123456 is currently on its way. If you do not receive your order within one week of the expected delivery date of October 15, 2023, please contact customer support. Additional notifications can be found within the app."

[0833] Specific prompts include "What is your order number?" and "When is the expected delivery date?"

[0834] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0835] Step 1:

[0836] The user device receives input information from the user. Specifically, the user enters details about the problem into the smartphone interface. For example, the input information, such as "The purchased product has not arrived," is sent to the server. The input at this stage is the details of the problem, and the output is the transmission of the problem information to the server.

[0837] Step 2:

[0838] The server analyzes the trouble information received from the user. The server uses natural language processing technology to analyze the input text and identify the type of trouble. In this step, the input trouble information is analyzed and the trouble category, for example, "item not delivered," is clarified. The output is the generation of questions based on the type of trouble.

[0839] Step 3:

[0840] The server generates questions according to the type of problem identified and sends them to the user's device. A generative AI model is used to generate specific questions. For example, questions such as "What is your order number?" or "When is the expected delivery date for the product?" are generated. The input for this step is the type of problem, and the output is the specific questions.

[0841] Step 4:

[0842] The user terminal presents the generated questions to the user and accepts the user's answers. The user inputs answers to the presented questions. For example, the user might input answers such as "The order number is 123456" or "The product is scheduled to arrive on October 15, 2023." The input at this stage is the answer to the questions, and the output is the transmission of the answer information to the server.

[0843] Step 5:

[0844] The server collects and stores the answers received from the user. Here, the user's answer data is stored in a database and the necessary information is extracted. The input of this step is the user's answer information, and the output is storage in the database.

[0845] Step 6:

[0846] The server searches the database based on the collected information and selects an appropriate solution. The server queries the database for past cases and related information to identify the optimal solution. The input for this step is the user's response information and the contents of the database, and the output is the selection of a solution.

[0847] Step 7:

[0848] The emotion analysis engine analyzes the user's emotional state. The server uses the emotion analysis engine to identify the user's emotional state from their input and responses. For example, it can detect that the user is feeling anxious or angry. The input for this step is the user's input and responses, and the output is the identified emotional state.

[0849] Step 8:

[0850] The server adjusts the way the solution is presented based on the analyzed emotional state. The server presents the solution in a gentle and polite manner depending on the user's emotional state. For example, the solution is adjusted to be something like, "Don't worry. Order number 123456 is currently being delivered. If you have any questions, please contact customer support." The input of this step is the emotional state and the selected solution, and the output is the presentation of the adjusted solution.

[0851] Step 9:

[0852] The server sends the adjusted solution to the user terminal and presents it to the user. The user terminal displays the adjusted solution, and the user can take action based on it. The input of this step is the adjusted solution, and the output is the solution presented to the user.

[0853] 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 audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio 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 audio data.

[0854] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with 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.

[0855] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0856] [Third embodiment]

[0857] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0858] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0859] 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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0860] 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.

[0861] 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 audio in accordance with instructions from the processor 46.

[0862] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and 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 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0863] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0864] Fig. 6 shows an example of the 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.

[0865] 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.

[0866] 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.

[0867] In the headset type terminal 314, a 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.

[0868] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0869] This invention is a consultation system for dealing with various troubles that occur in daily life. This system presents reliable solutions based on information about the trouble entered by the user. The basic flow of the system is explained below.

[0870] System Overview

[0871] The system mainly consists of the following components:

[0872] 1. User Device

[0873] 2. Server

[0874] 3. Database

[0875] Program processing flow

[0876] User device behavior

[0877] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[0878] Server Operation

[0879] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. The server also collects and stores the user's answers, searches the database based on that information, and selects the optimal solution based on the search results and presents it to the user.

[0880] The role of the database

[0881] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[0882] Program processing example

[0883] The operation of the system will be explained below using a specific example of a problem.

[0884] Example: A child hits an elderly person on a bicycle and injures them.

[0885] 1. User device operation

[0886] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[0887] The user terminal transmits this information to the server.

[0888] 2. Server Operation

[0889] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[0890] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[0891] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[0892] 3. Server Data Processing

[0893] The server organizes and stores the collected information and queries the database based on that information.

[0894] The server analyzes the results from the database and selects the most appropriate solution.

[0895] 4. Server Solution Presentation

[0896] The server generates a selected solution and presents it to the user: "Promptly administer first aid to the victim and seek appropriate medical attention at a hospital. Next, report the accident to the police and don't forget to notify your insurance company. We also recommend that you consult a law firm."

[0897] Key Details

[0898] Each component of the system works together to quickly and reliably provide optimal solutions to problems users face. The database contains a wealth of past cases, and natural language processing technology is used to accurately analyze and respond to user input. This system configuration allows users to receive reliable advice and respond calmly.

[0899] The processing flow will be explained below.

[0900] Step 1:

[0901] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[0902] Step 2:

[0903] The terminal transmits the input information to the server, which includes details of the problem.

[0904] Step 3:

[0905] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[0906] Step 4:

[0907] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[0908] Step 5:

[0909] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[0910] Step 6:

[0911] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[0912] Step 7:

[0913] The device sends the user's response to the server, which includes detailed information about the accident.

[0914] Step 8:

[0915] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[0916] Step 9:

[0917] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[0918] Step 10:

[0919] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[0920] Step 11:

[0921] The server summarizes the selected solution in an easy-to-understand format and sends it to the web terminal. The summarized solution includes specific steps.

[0922] Step 12:

[0923] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[0924] Example 1

[0925] Next, a description will be given of 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."

[0926] Nowadays, many people face various problems in their daily lives. These problems range from legal issues to traffic accidents and insurance claims, and it is difficult to find an appropriate solution quickly and accurately. To deal with such situations, a system that can efficiently present reliable solutions is needed.

[0927] 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.

[0928] In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for analyzing the received trouble information and identifying the type of trouble, means for generating questions according to the type of trouble and presenting them to the user, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, and means for presenting the selected solution to the user. This makes it possible to provide quick and accurate solutions to the troubles that users face.

[0929] A "user terminal" is a device that allows a user to input information about troubles in their daily lives and communicate with the server.

[0930] The "server" is a device that analyzes received trouble information, generates necessary questions, collects and organizes responses from users, and selects and presents appropriate solutions.

[0931] A "database" is a storage device that stores reliable sources of information such as past cases, legal documents, court records, and insurance policies.

[0932] "Trouble information" is information entered by users about various problems and incidents in their daily lives.

[0933] "Questions" are questions that the server asks the user to gather additional information in order to resolve the issue.

[0934] "Natural language processing technology" is an artificial intelligence technology used to analyze and understand the meaning of trouble information and answers entered by users.

[0935] A "solution" is a proposal for the optimal procedure or countermeasure for a problem, selected from a database based on collected information.

[0936] A "collection means" is a method or device used to store and later analyze responses from users.

[0937] The present invention is a consultation system for helping users deal with various problems they encounter in their daily lives. This system is configured using the following hardware and software.

[0938] System Components

[0939] 1. User Device

[0940] A user terminal is a device that allows a user to input information about a problem and send it to a server. Examples include a PC or smartphone. A web browser or dedicated application is installed on the user terminal, and the user can access the system through this.

[0941] 2. Server

[0942] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. It also collects and stores the user's responses, queries the data against a database, and selects and presents the optimal solution. The server is equipped with a generative AI model incorporating natural language processing (NLP) technology, allowing it to accurately analyze user input.

[0943] 3. Database

[0944] The database contains reliable sources of information such as past cases, legal documents, court records, insurance policies, etc. The server queries this database to find the appropriate solution to the user's problem.

[0945] Program processing

[0946] 1. Information input and analysis

[0947] The user uses the device to input information about the incident. For example, they might input information like, "My child hit an elderly person on his bicycle and injured him." The device then sends this information to the server.

[0948] 2. Question generation and presentation

[0949] The server uses NLP technology to analyze the received accident information and identify the type of accident. It then generates questions to confirm the details of the accident. For example, it presents questions such as "Please tell us the date, time, and location of the accident," "Please tell us the ages and conditions of the victim and assailant," and "Are there any witnesses?"

[0950] 3. Response collection and database search

[0951] Users answer questions posed to them, and their devices send their answers to a server, which then organizes the collected information and queries a database to find relevant past cases and solutions.

[0952] 4. Solution selection and presentation

[0953] The server selects the optimal solution based on the information retrieved from the database. It then sends the solution to the user's device and presents it to the user. For example, it provides specific instructions such as, "Promptly administer first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend consulting a law firm."

[0954] Examples of specific examples and prompts

[0955] Below are some examples and prompts:

[0956] Examples:

[0957] Answers to the questions, "10:00 a.m. on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim suffered a broken arm," and "Yes, other parents and children were watching."

[0958] Example prompt sentence:

[0959] "What should I do if my child hits an elderly person on a bicycle and injures them?"

[0960] "If your household pet is destroying your neighbor's yard, what are the specific steps you can take to fix the problem?"

[0961] The system's components work together to provide accurate and prompt solutions to problems users encounter. By utilizing the abundant information stored in the database and natural language processing technology, users can receive reliable advice.

[0962] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0963] Step 1:

[0964] Entering information via user terminal

[0965] The user inputs information about a trouble in their daily life, for example, "A child hit an elderly person on a bicycle and injured them," using a web browser or a dedicated application interface. This information is sent to the server via the API endpoint on the user's device.

[0966] Input: Trouble information entered by the user (e.g., "A child hit an elderly person on a bicycle and injured them")

[0967] Output: Sending trouble information from the terminal to the server

[0968] Step 2:

[0969] Server-based information analysis

[0970] The server analyzes the incident information received from the user's device and uses an NLP model to identify the type of incident and understand its details. For example, it identifies a "bicycle accident" based on the input information.

[0971] Input: Trouble information sent by the user

[0972] Data processing: Analyze information using an NLP model to identify the type and details of the problem

[0973] Output: Analyzed trouble information (e.g. "Bicycle accident")

[0974] Step 3:

[0975] Server-generated questionnaire

[0976] Based on the analyzed incident information, the server generates questions to gather additional information. Generative AI models are used to dynamically create questions, such as "Please tell us the date, time, and location of the accident," or "Please tell us the ages and conditions of the victim and assailant."

[0977] Input: Analyzed trouble information

[0978] Data processing: Question generation using generative AI models

[0979] Output: Generated questionnaire

[0980] Step 4:

[0981] Posting questions and collecting answers on user devices

[0982] The user device receives questions from the server and presents them to the user. The user then inputs answers to these questions. For example, the user can input answers such as "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," or "Yes, another parent and child were watching."

[0983] Input: Questions sent from the server

[0984] Output: User response (e.g., "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," "Yes, another parent and child were watching.")

[0985] Step 5:

[0986] Server collects answers and organizes data

[0987] The server receives the user's responses and organizes and stores them, i.e., converts each response into a format that can be stored in a database, and prepares the database for querying in the next step.

[0988] Input: User response

[0989] Data processing: Organizing responses and converting them into a format suitable for database storage

[0990] Output: Organized response data

[0991] Step 6:

[0992] Server queries database and selects solution

[0993] The server queries the database based on the organized response data to find the appropriate solution. The database contains past cases and materials, and the server selects the optimal solution.

[0994] Input: Organized response data

[0995] Data processing: database queries and result analysis

[0996] Output: Selected solution

[0997] Step 7:

[0998] Server provides solutions

[0999] The server sends the selected solution to the user's device, which then displays it to the user. For example, the device provides specific instructions such as, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1000] Input: Selected Solution

[1001] Output: The solution presented to the user

[1002] (Application example 1)

[1003] Next, a description will be given of Application 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."

[1004] When users of autonomous vehicles encounter problems such as accidents or breakdowns, there is a need for a system that can collect information and provide solutions to respond quickly and accurately. However, currently, there is a lack of means to efficiently collect problem information and quickly provide appropriate instructions to users. In addition, there are few examples of applications that combine situation-specific question generation and natural language processing technology, and comprehensive solution systems are insufficient. Furthermore, there is no database specialized in measures for autonomous vehicles, making it difficult to derive solutions based on specialized information. Improving this situation is a challenge.

[1005] 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.

[1006] In this invention, the server includes means for receiving information about daily life troubles entered by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving responses from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for presenting the selected solution to the user, and means for quickly collecting trouble information when the autonomous vehicle encounters a breakdown or accident, asking for appropriate additional information, and analyzing the collected information. This allows for a prompt and accurate response even when the user encounters trouble with the autonomous vehicle, as the necessary information is quickly collected and appropriate questions and solutions are presented. Furthermore, the use of a specialized database allows for the provision of solutions based on more accurate information.

[1007] A "user terminal" is a device that users use to input information about troubles in their daily lives, such as a smartphone or computer.

[1008] A "server" is a computer system that has the function of analyzing trouble information received from a user terminal, generating appropriate questions, and presenting them to the user.

[1009] The "database" is an information collection system that stores reliable information such as past trouble cases, legal documents, insurance policies, car accident-related information, and repair procedures.

[1010] A "questionnaire" is a series of questions presented to a user to clarify the details of the problem, with the aim of gathering information to provide an appropriate solution.

[1011] "Natural language processing technology" is a technology that allows a machine to understand the text entered by the user and generate appropriate questions and solutions.

[1012] An "autonomous vehicle" is a vehicle that can drive autonomously.

[1013] "Trouble information" is information recorded when an autonomous vehicle encounters a problem such as a breakdown or accident.

[1014] A "solution" is a specific method of dealing with a problem that is presented to the user based on the collected information and database.

[1015] A "prompt" is a sentence that is input into a generative AI model and is used as the basis for deriving appropriate questions and solutions.

[1016] The system for implementing this invention comprises a user terminal, a server, and a database. The user terminal is a device for inputting information about the trouble a user encounters, such as a smartphone or computer. The trouble information input by the user is sent to the server.

[1017] The server is a Python server using the Flask framework that analyzes trouble information received from the user's device. Based on the analysis results, the server identifies the type of trouble and generates appropriate questions to present to the user's device. Natural language processing technology is used to generate the questions, and prompts are used to ask specific and appropriate questions.

[1018] For example, if a self-driving vehicle collides with another vehicle at an intersection, the server generates the following question:

[1019] "What type of accident was it (e.g., car collision, breakdown)?"

[1020] Please tell us the date, time and location of the accident.

[1021] "Please provide details about the victim or perpetrator."

[1022] Once the user answers these questions, the server collects and stores the answers and searches a database to find the optimal solution. The database includes reliable information such as past trouble cases, legal documents, insurance policies, car accident information, and repair procedures. Based on this information, the server selects the optimal solution and displays it on the user's device.

[1023] The specific software and hardware used are as follows:

[1024] Server: Python server using the Flask framework

[1025] Database: SQLite

[1026] Frontend: Smartphone client app

[1027] Data processing and data calculations include steps such as receiving user input, analyzing it, generating questions, collecting and storing answer information, searching a database, and selecting a solution.

[1028] Examples of specific prompts include:

[1029] Accident information: An autonomous vehicle collided with another vehicle at an intersection

[1030] Question 1: What type of accident was it (e.g. car collision, breakdown)?

[1031] Question 2: Please tell us the date, time and location of the accident.

[1032] Question 3: Please provide details about the victim or perpetrator.

[1033] This means that even if a user encounters a problem with an autonomous vehicle, the necessary information will be collected quickly and the appropriate questions and solutions will be presented, enabling a quick and accurate response.In addition, by using a specialized database, solutions can be provided based on more accurate information.

[1034] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1035] Step 1:

[1036] The user uses the device to input trouble information. This information may include, for example, "The autonomous vehicle collided with another vehicle at an intersection." The device receives this input information and sends it to the server.

[1037] Input: Trouble information entered by the user on the device

[1038] Output: Trouble information sent from the device to the server

[1039] Step 2:

[1040] The server analyzes the trouble information received from the device, identifies the type of trouble, and generates appropriate questions. This process uses natural language processing technology to create the necessary prompts.

[1041] Input: Trouble information sent from the device

[1042] Output: Generated questions and prompts

[1043] Specific operation: The server analyzes the trouble information and generates questions such as: "What type of accident was it (e.g., car collision, breakdown)?", "What time and place did the accident occur?", "Please provide details of the victim or perpetrator."

[1044] Step 3:

[1045] The server sends the generated questions to the user's terminal, where the user answers the questions and inputs the answer information.

[1046] Input: Server-generated questionnaire

[1047] Output: Questions presented to the user's device

[1048] Specific operation: The user answers questions on the device and inputs the following information: "Car collision," "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim suffered a broken arm."

[1049] Step 4:

[1050] The user terminal sends the user's answer information to the server, which collects and stores the received answer information.

[1051] Input: Answer information entered by the user on the device

[1052] Output: Answer information sent to the server

[1053] Specific operation: The user terminal sends the answer information to the server, and the server stores the information in a database.

[1054] Step 5:

[1055] The server uses the collected information to search databases, including law firm documents, court records, insurance policies, car accident information, and repair procedures, to find the best solution.

[1056] Input: Answer information saved on the server

[1057] Output: The correct solution retrieved from the database

[1058] What happens: The server queries the database to find and select the most appropriate solution.

[1059] Step 6:

[1060] The server generates the selected solution and presents the information to the user terminal.

[1061] Input: Solutions retrieved from the database

[1062] Output: The solution presented to the user

[1063] Specific operation: The server generates a solution and sends it to the user's device, displaying the following message to the user: "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1064] Furthermore, 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.

[1065] This is a consultation system that provides reliable solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also recognize the user's emotional state and respond accordingly.

[1066] System Overview

[1067] The system consists of the following elements:

[1068] 1. User Device

[1069] 2. Server

[1070] 3. Database

[1071] 4. Emotion Engine

[1072] Program processing flow

[1073] User device behavior

[1074] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[1075] Server Operation

[1076] The server analyzes the trouble information received from the user's device, generates appropriate questions to present to the user, and collects and stores the user's responses, searching the database based on that information to select and present the optimal solution.

[1077] The role of the emotional engine

[1078] The emotion engine analyzes the user's input and responses to identify the user's emotional state. Based on the identified emotional state, the server adjusts the wording of the solutions and questions it presents.

[1079] The role of the database

[1080] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[1081] Program processing example

[1082] The operation of the system will be explained below using a specific example of a problem.

[1083] Example: A child hits an elderly person on a bicycle and injures them.

[1084] 1. User device operation

[1085] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[1086] The user terminal transmits this information to the server.

[1087] 2. Server Operation

[1088] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[1089] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[1090] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[1091] 3. Operation of the Emotion Engine

[1092] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[1093] The emotion engine reports the user's emotional state to the server.

[1094] 4. Server Data Processing

[1095] The server also takes into account information from the emotion engine when deciding how to respond to the user. For example, if a user is feeling anxious, the server will ask questions and give advice in a gentle and polite manner.

[1096] The server then generates a query to search the database based on the user's response information.

[1097] 5. Querying the Server

[1098] The server uses the generated query to search databases, which may include law firm files, court records, and insurance policies.

[1099] 6. Server Solution Selection

[1100] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[1101] The way solutions are presented is also adjusted based on the results of the emotion engine's analysis of user emotions.

[1102] 7. Server Solution Proposal

[1103] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps.

[1104] For example, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1105] Key Details

[1106] This system recognizes the user's emotions and adjusts its response accordingly, providing more appropriate and reliable support. The built-in emotion engine allows users to receive specific and appropriate advice to help them stay calm. The database contains a wealth of past cases, and natural language processing technology enables accurate analysis and response of user input.

[1107] The processing flow will be explained below.

[1108] Step 1:

[1109] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[1110] Step 2:

[1111] The terminal transmits the input information to the server, which includes details of the problem.

[1112] Step 3:

[1113] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[1114] Step 4:

[1115] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[1116] Step 5:

[1117] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[1118] Step 6:

[1119] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[1120] Step 7:

[1121] The device sends the user's response to the server, which includes detailed information about the accident.

[1122] Step 8:

[1123] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[1124] Step 9:

[1125] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[1126] Step 10:

[1127] The emotion engine reports the identified emotional state to the server, so that the server can take the emotional state into account.

[1128] Step 11:

[1129] The server takes into account the information from the emotion engine and decides how to respond to the user. For example, if a user feels anxious, it will ask questions and give advice in a gentle and polite manner.

[1130] Step 12:

[1131] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[1132] Step 13:

[1133] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[1134] Step 14:

[1135] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps. For example, "Promptly administer first aid to the victim and have them receive appropriate medical treatment at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1136] Step 15:

[1137] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[1138] Example 2

[1139] Next, a description will be given of 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."

[1140] In modern life, providing users with quick and appropriate solutions to the various problems they face is a major challenge. Providing an appropriate response can be particularly difficult depending on the specific nature of the problem and the user's emotional state. Conventional systems often provide only bureaucratic information without considering the user's emotions, so there is a need for a system that provides user-friendly and reliable solutions.

[1141] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving information about troubles in daily life input by the user, a means for presenting the user with questions according to the type of trouble, a means for collecting and saving answers from the user, a means for searching a database based on the collected information and selecting an appropriate solution, a means for identifying the emotional state of the user using an emotion analysis engine, and a means for adjusting questions to the user and solutions based on the identified emotional state. This allows a reliable solution according to the user's emotional state to be quickly provided, allowing the user to deal with the problem more calmly.

[1142] "Information entered by users regarding troubles in daily life" refers to details of problems and annoyances related to daily life that users enter using their own devices.

[1143] "Questions according to the type of problem" are questions that are automatically generated to collect necessary additional information based on the problem information entered by the user.

[1144] "Means for collecting and storing answers from users" refers to a function that receives answers entered by users to questions presented to them and stores them in storage such as a database.

[1145] "Means of searching the database and selecting the appropriate solution" is the process of searching related information in the database based on the collected information and finding the optimal solution.

[1146] "Means for presenting the selected solution to the user" refers to a function that sends the optimal solution selected through a database search to the user's terminal and displays it.

[1147] An "emotion analysis engine" is a software engine that analyzes user input and identifies the user's emotional state (e.g., anxiety, fear, joy, etc.).

[1148] "Means for adjusting questions and solutions to the user based on the identified emotional state" refers to a function that changes the wording of the questions and solutions presented to the user, taking into account the emotional state of the user identified by the emotion analysis engine.

[1149] "Natural language processing technology" refers to technology for analyzing and understanding natural language text entered by a user, and examples include text classification, sentiment analysis, and name recognition.

[1150] This invention is a consultation system that provides quick and appropriate solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also analyze the user's emotional state and respond accordingly. The system consists of a user terminal, a server, a database, and an emotion analysis engine.

[1151] System Components

[1152] 1. User terminal: Provides an interface for users to enter trouble information. Specifically, it is provided in the form of a web page or mobile application, and sends the information entered by the user to the server.

[1153] 2. Server: Receives and analyzes the trouble information. In particular, the server uses natural language processing technology to determine the nature of the trouble and generate appropriate questions. Examples of natural language processing technology used include SpaCy and NLTK. The server also collects and stores responses from users and searches a database based on that information.

[1154] 3. Database: Stores reliable sources of information such as past cases, legal documents, court information, insurance policies, etc. The server queries this database to find the best solution.

[1155] 4. Sentiment analysis engine: Analyzes the user's input and responses to identify their emotional state (anxiety, fear, joy, etc.). The sentiment analysis engine uses IBM Watson Tone Analyzer and Microsoft Azure Text Analytics.

[1156] Program operation explanation

[1157] 1. User device operation: The user is presented with a form to enter details of the incident, and the data is sent to the server. For example, the user might enter, "My child hit an elderly person on his bicycle and injured him."

[1158] 2. Server operation:

[1159] Analyze trouble information to determine the type of accident and the characteristics of those involved.

[1160] Generate appropriate questions and present them to the user.

[1161] 3. Collecting user responses: The user enters answers to questions presented to them, such as "date, time and location of the accident," "age and condition of the victim and assailant," and "whether there were any witnesses."

[1162] 4. Sentiment analysis engine operation: Analyzes the user's input and answers to identify their emotional state. For example, if the user is feeling anxious, it reports that emotional state to the server.

[1163] 5. Database search: The server searches the database based on the user's answers and emotional information and selects the optimal solution.

[1164] 6. Emotional adjustment of the solution: Based on the results of the emotion analysis engine, the way the solution is expressed is adjusted, for example, to use gentler and more polite language.

[1165] 7. Solution Presentation: The server sends the selected solution to the user's device and presents it to the user, showing specific steps and next actions to take.

[1166] Prompt sentence examples

[1167] "What should you do if your child hits an elderly person on a bicycle and injures them?"

[1168] Specific examples

[1169] For example, if a user types into their device, "At 10:00 AM on October 10, 2023, a 10-year-old child hit a 70-year-old man on a park's bicycle path, breaking his arm," the server receives and analyzes this information. Detailed questions, such as the date, time, and location of the accident, the ages and conditions of the victim and assailant, and whether there were any witnesses, are then generated and presented to the user. When the user answers these questions, the system searches a database based on the user's answers and presents optimal solutions, such as first aid, reporting the incident to the police, contacting an insurance company, or consulting a law firm. Furthermore, if the emotion analysis engine determines that the user's emotions are unstable, the solution is adjusted to be more polite and reassuring.

[1170] As described above, the system of the present invention provides a quick and appropriate response while taking the user's feelings into consideration, thereby realizing more reliable support for the user.

[1171] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1172] Step 1:

[1173] Input: The user enters details of the problem into the terminal.

[1174] How it works: The user opens the device and inputs information about a problem in their daily life, such as "A child hit an elderly person on a bicycle and injured him." The device receives this information and sends it to the server in a format.

[1175] Output: Trouble information is sent from the terminal to the server.

[1176] Step 2:

[1177] Input: The server receives the trouble information sent by the user.

[1178] How it works: The server uses natural language processing techniques (e.g., SpaCy, NLTK) to analyze the received trouble information and identify the type of trouble and its key elements.

[1179] Output: The type of problem and the identified elements are stored on the server.

[1180] Step 3:

[1181] Input: Type of trouble analyzed and key factors.

[1182] How it works: Based on the type of problem identified, the server automatically generates questions to gather additional information. This can be done using a rule-based or template-based approach.

[1183] Output: The generated questionnaires are stored in the server.

[1184] Step 4:

[1185] Input: The generated questionnaire.

[1186] Operation: The server sends the generated questionnaire to the user's terminal and presents the questionnaire to the user.

[1187] Output: The questionnaire is displayed on the user's terminal.

[1188] Step 5:

[1189] Input: The user answers the questions posed.

[1190] How it works: The user answers questions by entering specific details, such as "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching." The device then sends these answers to the server.

[1191] Output: Answer information is sent from the user terminal to the server.

[1192] Step 6:

[1193] Input: User response information.

[1194] How it works: The server analyzes the received user responses and inputs them into a sentiment analysis engine, which uses tools such as IBM Watson Tone Analyzer and Microsoft Azure Text Analytics to identify the user's emotional state.

[1195] Output: The identified emotional state is stored in the server.

[1196] Step 7:

[1197] Input: User response information and emotional state from the sentiment analysis engine.

[1198] How it works: The server generates a query for database search based on the response information and emotional state. The query is formulated as an SQL statement or a NoSQL query.

[1199] Output: The generated queries are stored in the server.

[1200] Step 8:

[1201] Input: The generated query.

[1202] How it works: The server runs the generated query against a database to retrieve relevant information, such as legal documents, court information, and insurance policies.

[1203] Output: The relevant information is returned to the server.

[1204] Step 9:

[1205] Input: Relevant information returned from the database.

[1206] How it works: The server analyzes the relevant information it has obtained and selects an appropriate solution to the user's problem, such as "first aid," "reporting to the police," "contacting your insurance company," or "consulting a law firm."

[1207] Output: The selected solution is stored in the server.

[1208] Step 10:

[1209] Input: Selected solution and emotional state from the sentiment analysis engine.

[1210] How it works: The server adjusts the way the solution is phrased based on the user's emotional state. If the user is feeling anxious, the solution is phrased more gently and politely.

[1211] Output: The adjusted solution is stored in the server.

[1212] Step 11:

[1213] Input: Adjusted solution.

[1214] Operation: The server sends the final solution to the user's terminal and presents it to the user.

[1215] Output: The adjusted solution is displayed on the user's terminal.

[1216] (Application example 2)

[1217] Next, a description will be given of Application 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."

[1218] This invention is a consultation system that provides fast and reliable solutions to purchase-related problems and questions when users are searching for products on an online shopping site. However, current systems often cause dissatisfaction and anxiety because they are unable to respond appropriately while taking into account the user's emotional state. Furthermore, they do not fully utilize data such as past support cases and order history, making it difficult to provide optimal solutions.

[1219] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for analyzing the user's emotional state, and means for adjusting the way the solution is presented based on the analyzed emotional state. This enables an appropriate response according to the user's emotional state and makes it possible to provide a quick and reliable solution.

[1220] "Means for receiving information entered by users about troubles in daily life" refers to an interface or function that allows users to enter information about troubles or questions they have encountered and for the system to receive that information.

[1221] "Means for presenting questions to the user according to the type of trouble" is a function that automatically generates questions appropriate to the content of the trouble based on the information entered by the user and presents them to the user.

[1222] The "means for collecting and storing responses from users" refers to a system for collecting, recording, and storing responses entered by users to questions presented to them.

[1223] "Means of searching the database based on collected information and selecting an appropriate solution" is a function that uses information collected from the user to search for appropriate information in the database and selects the optimal solution from the results.

[1224] "Means for analyzing a user's emotional state" refers to an algorithm or system that analyzes a user's input and responses to identify their current emotional state.

[1225] The "means for adjusting the way in which a solution is presented based on the analyzed emotional state" is a function that changes the presentation of the solution provided depending on the user's emotional state, thereby providing a more appropriate and reassuring response.

[1226] "Law firm documents, court records, insurance policies, past order history, delivery status, and support case studies" are a wide range of data sources that are referenced when selecting solutions and provide reliable responses to user problems.

[1227] This is a consultation system that provides quick and reliable solutions to problems and questions about purchases when users are searching for products on online shopping sites. The system is composed of elements such as a user terminal, a server, a database, and a sentiment analysis engine.

[1228] System configuration

[1229] 1. User Device

[1230] The user terminal is a mobile device such as a smartphone or tablet, and provides an interface for users to input information about the problem. Users access the system by inputting information about their purchase or problem.

[1231] 2. Server

[1232] The server receives and analyzes information entered by users. Specifically, it generates questions based on the user's trouble information and presents them to the user. It also collects and stores the user's responses, uses this information to search a database, and selects the appropriate solution.

[1233] 3. Database

[1234] The database contains law firm documents, court records, insurance policies, as well as past order history, delivery status, support case studies, etc. The server searches this database to find the best solution for the user's problem.

[1235] 4. Sentiment Analysis Engine

[1236] The emotion analysis engine analyzes the user's input and identifies their emotional state. Based on the detected emotional state, the server adjusts its response to the user and presents a solution expression appropriate to the user's emotional state.

[1237] Implementation example

[1238] User device behavior

[1239] The user uses their smartphone to input information about the problem of not receiving the purchased product, and the user's device sends this information to the server.

[1240] Server Operation

[1241] The server analyzes the trouble information received from the user and identifies the type of trouble. For example, it determines that the product has not arrived, and generates questions to present to the user. Specific examples of questions include, "What is your order number?" and "When is the product expected to arrive?" When the user answers these questions, the information is collected and stored.

[1242] How the sentiment analysis engine works

[1243] The emotion analysis engine analyzes and identifies the user's emotional state from their input. For example, it may detect that the user is feeling anxious or irritated. The emotion analysis engine provides this information to the server, which then determines how to respond based on the user's emotional state.

[1244] Server data processing

[1245] The server searches a database based on the user's response information and emotional state to select an appropriate solution. The database includes information such as past order history, delivery status, and support case studies, so specific and reliable solutions can be obtained.

[1246] Proposing a solution

[1247] The selected solution is then presented to the user in a way that eases their concerns, such as, "Order number 123456 is currently on its way. If you do not receive your order within one week of the expected delivery date of October 15, 2023, please contact customer support. Additional notifications can be found within the app."

[1248] Specific prompts include "What is your order number?" and "When is the expected delivery date?"

[1249] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1250] Step 1:

[1251] The user device receives input information from the user. Specifically, the user enters details about the problem into the smartphone interface. For example, the input information, such as "The purchased product has not arrived," is sent to the server. The input at this stage is the details of the problem, and the output is the transmission of the problem information to the server.

[1252] Step 2:

[1253] The server analyzes the trouble information received from the user. The server uses natural language processing technology to analyze the input text and identify the type of trouble. In this step, the input trouble information is analyzed and the trouble category, for example, "item not delivered," is clarified. The output is the generation of questions based on the type of trouble.

[1254] Step 3:

[1255] The server generates questions according to the type of problem identified and sends them to the user's device. A generative AI model is used to generate specific questions. For example, questions such as "What is your order number?" or "When is the expected delivery date for the product?" are generated. The input for this step is the type of problem, and the output is the specific questions.

[1256] Step 4:

[1257] The user terminal presents the generated questions to the user and accepts the user's answers. The user inputs answers to the presented questions. For example, the user might input answers such as "The order number is 123456" or "The product is scheduled to arrive on October 15, 2023." The input at this stage is the answer to the questions, and the output is the transmission of the answer information to the server.

[1258] Step 5:

[1259] The server collects and stores the answers received from the user. Here, the user's answer data is stored in a database and the necessary information is extracted. The input of this step is the user's answer information, and the output is storage in the database.

[1260] Step 6:

[1261] The server searches the database based on the collected information and selects an appropriate solution. The server queries the database for past cases and related information to identify the optimal solution. The input for this step is the user's response information and the contents of the database, and the output is the selection of a solution.

[1262] Step 7:

[1263] The emotion analysis engine analyzes the user's emotional state. The server uses the emotion analysis engine to identify the user's emotional state from their input and responses. For example, it can detect that the user is feeling anxious or angry. The input for this step is the user's input and responses, and the output is the identified emotional state.

[1264] Step 8:

[1265] The server adjusts the way the solution is presented based on the analyzed emotional state. The server presents the solution in a gentle and polite manner depending on the user's emotional state. For example, the solution is adjusted to be something like, "Don't worry. Order number 123456 is currently being delivered. If you have any questions, please contact customer support." The input of this step is the emotional state and the selected solution, and the output is the presentation of the adjusted solution.

[1266] Step 9:

[1267] The server sends the adjusted solution to the user terminal and presents it to the user. The user terminal displays the adjusted solution, and the user can take action based on it. The input of this step is the adjusted solution, and the output is the solution presented to the user.

[1268] 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 audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio 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 audio data.

[1269] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with 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.

[1270] 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.

[1271] [Fourth embodiment]

[1272] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1273] 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.

[1274] 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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1275] 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. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1276] 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 audio in accordance with instructions from the processor 46.

[1277] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and 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 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1278] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1279] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. 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.

[1280] Fig. 8 shows an example of the 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.

[1281] 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.

[1282] 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.

[1283] In the robot 414, the processor 46 performs the reception output process. 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.

[1284] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. 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."

[1285] This invention is a consultation system for dealing with various troubles that occur in daily life. This system presents reliable solutions based on information about the trouble entered by the user. The basic flow of the system is explained below.

[1286] System Overview

[1287] The system mainly consists of the following components:

[1288] 1. User Device

[1289] 2. Server

[1290] 3. Database

[1291] Program processing flow

[1292] User device behavior

[1293] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[1294] Server Operation

[1295] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. The server also collects and stores the user's answers, searches the database based on that information, and selects the optimal solution based on the search results and presents it to the user.

[1296] The role of the database

[1297] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[1298] Program processing example

[1299] The operation of the system will be explained below using a specific example of a problem.

[1300] Example: A child hits an elderly person on a bicycle and injures them.

[1301] 1. User device operation

[1302] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[1303] The user terminal transmits this information to the server.

[1304] 2. Server Operation

[1305] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[1306] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[1307] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[1308] 3. Server Data Processing

[1309] The server organizes and stores the collected information and queries the database based on that information.

[1310] The server analyzes the results from the database and selects the most appropriate solution.

[1311] 4. Server Solution Presentation

[1312] The server generates a selected solution and presents it to the user: "Promptly administer first aid to the victim and seek appropriate medical attention at a hospital. Next, report the accident to the police and don't forget to notify your insurance company. We also recommend that you consult a law firm."

[1313] Key Details

[1314] Each component of the system works together to quickly and reliably provide optimal solutions to problems users face. The database contains a wealth of past cases, and natural language processing technology is used to accurately analyze and respond to user input. This system configuration allows users to receive reliable advice and respond calmly.

[1315] The processing flow will be explained below.

[1316] Step 1:

[1317] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[1318] Step 2:

[1319] The terminal transmits the input information to the server, which includes details of the problem.

[1320] Step 3:

[1321] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[1322] Step 4:

[1323] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[1324] Step 5:

[1325] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[1326] Step 6:

[1327] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[1328] Step 7:

[1329] The device sends the user's response to the server, which includes detailed information about the accident.

[1330] Step 8:

[1331] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[1332] Step 9:

[1333] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[1334] Step 10:

[1335] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[1336] Step 11:

[1337] The server summarizes the selected solution in an easy-to-understand format and sends it to the web terminal. The summarized solution includes specific steps.

[1338] Step 12:

[1339] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[1340] Example 1

[1341] Next, a description will be given of 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."

[1342] Nowadays, many people face various problems in their daily lives. These problems range from legal issues to traffic accidents and insurance claims, and it is difficult to find an appropriate solution quickly and accurately. To deal with such situations, a system that can efficiently present reliable solutions is needed.

[1343] 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.

[1344] In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for analyzing the received trouble information and identifying the type of trouble, means for generating questions according to the type of trouble and presenting them to the user, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, and means for presenting the selected solution to the user. This makes it possible to provide quick and accurate solutions to the troubles that users face.

[1345] A "user terminal" is a device that allows a user to input information about troubles in their daily lives and communicate with the server.

[1346] The "server" is a device that analyzes received trouble information, generates necessary questions, collects and organizes responses from users, and selects and presents appropriate solutions.

[1347] A "database" is a storage device that stores reliable sources of information such as past cases, legal documents, court records, and insurance policies.

[1348] "Trouble information" is information entered by users about various problems and incidents in their daily lives.

[1349] "Questions" are questions that the server asks the user to gather additional information in order to resolve the issue.

[1350] "Natural language processing technology" is an artificial intelligence technology used to analyze and understand the meaning of trouble information and answers entered by users.

[1351] A "solution" is a proposal for the optimal procedure or countermeasure for a problem, selected from a database based on collected information.

[1352] A "collection means" is a method or device used to store and later analyze responses from users.

[1353] The present invention is a consultation system for helping users deal with various problems they encounter in their daily lives. This system is configured using the following hardware and software.

[1354] System Components

[1355] 1. User Device

[1356] A user terminal is a device that allows a user to input information about a problem and send it to a server. Examples include a PC or smartphone. A web browser or dedicated application is installed on the user terminal, and the user can access the system through this.

[1357] 2. Server

[1358] The server analyzes the trouble information received from the user's device, generates appropriate questions, and presents them to the user. It also collects and stores the user's responses, queries the data against a database, and selects and presents the optimal solution. The server is equipped with a generative AI model incorporating natural language processing (NLP) technology, allowing it to accurately analyze user input.

[1359] 3. Database

[1360] The database contains reliable sources of information such as past cases, legal documents, court records, insurance policies, etc. The server queries this database to find the appropriate solution to the user's problem.

[1361] Program processing

[1362] 1. Information input and analysis

[1363] The user uses the device to input information about the incident. For example, they might input information like, "My child hit an elderly person on his bicycle and injured him." The device then sends this information to the server.

[1364] 2. Question generation and presentation

[1365] The server uses NLP technology to analyze the received accident information and identify the type of accident. It then generates questions to confirm the details of the accident. For example, it presents questions such as "Please tell us the date, time, and location of the accident," "Please tell us the ages and conditions of the victim and assailant," and "Are there any witnesses?"

[1366] 3. Response collection and database search

[1367] Users answer questions posed to them, and their devices send their answers to a server, which then organizes the collected information and queries a database to find relevant past cases and solutions.

[1368] 4. Solution selection and presentation

[1369] The server selects the optimal solution based on the information retrieved from the database. It then sends the solution to the user's device and presents it to the user. For example, it provides specific instructions such as, "Promptly administer first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend consulting a law firm."

[1370] Examples of specific examples and prompts

[1371] Below are some examples and prompts:

[1372] Examples:

[1373] Answers to the questions, "10:00 a.m. on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim suffered a broken arm," and "Yes, other parents and children were watching."

[1374] Example prompt sentence:

[1375] "What should I do if my child hits an elderly person on a bicycle and injures them?"

[1376] "If your household pet is destroying your neighbor's yard, what are the specific steps you can take to fix the problem?"

[1377] The system's components work together to provide accurate and prompt solutions to problems users encounter. By utilizing the abundant information stored in the database and natural language processing technology, users can receive reliable advice.

[1378] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1379] Step 1:

[1380] Entering information via user terminal

[1381] The user inputs information about a trouble in their daily life, for example, "A child hit an elderly person on a bicycle and injured them," using a web browser or a dedicated application interface. This information is sent to the server via the API endpoint on the user's device.

[1382] Input: Trouble information entered by the user (e.g., "A child hit an elderly person on a bicycle and injured them")

[1383] Output: Sending trouble information from the terminal to the server

[1384] Step 2:

[1385] Server-based information analysis

[1386] The server analyzes the incident information received from the user's device and uses an NLP model to identify the type of incident and understand its details. For example, it identifies a "bicycle accident" based on the input information.

[1387] Input: Trouble information sent by the user

[1388] Data processing: Analyze information using an NLP model to identify the type and details of the problem

[1389] Output: Analyzed trouble information (e.g. "Bicycle accident")

[1390] Step 3:

[1391] Server-generated questionnaire

[1392] Based on the analyzed incident information, the server generates questions to gather additional information. Generative AI models are used to dynamically create questions, such as "Please tell us the date, time, and location of the accident," or "Please tell us the ages and conditions of the victim and assailant."

[1393] Input: Analyzed trouble information

[1394] Data processing: Question generation using generative AI models

[1395] Output: Generated questionnaire

[1396] Step 4:

[1397] Posting questions and collecting answers on user devices

[1398] The user device receives questions from the server and presents them to the user. The user then inputs answers to these questions. For example, the user can input answers such as "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," or "Yes, another parent and child were watching."

[1399] Input: Questions sent from the server

[1400] Output: User response (e.g., "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," "Yes, another parent and child were watching.")

[1401] Step 5:

[1402] Server collects answers and organizes data

[1403] The server receives the user's responses and organizes and stores them, i.e., converts each response into a format that can be stored in a database, and prepares the database for querying in the next step.

[1404] Input: User response

[1405] Data processing: Organizing responses and converting them into a format suitable for database storage

[1406] Output: Organized response data

[1407] Step 6:

[1408] Server queries database and selects solution

[1409] The server queries the database based on the organized response data to find the appropriate solution. The database contains past cases and materials, and the server selects the optimal solution.

[1410] Input: Organized response data

[1411] Data processing: database queries and result analysis

[1412] Output: Selected solution

[1413] Step 7:

[1414] Server provides solutions

[1415] The server sends the selected solution to the user's device, which then displays it to the user. For example, the device provides specific instructions such as, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1416] Input: Selected Solution

[1417] Output: The solution presented to the user

[1418] (Application example 1)

[1419] Next, a description will be given of Application 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."

[1420] When users of autonomous vehicles encounter problems such as accidents or breakdowns, there is a need for a system that can collect information and provide solutions to respond quickly and accurately. However, currently, there is a lack of means to efficiently collect problem information and quickly provide appropriate instructions to users. In addition, there are few examples of applications that combine situation-specific question generation and natural language processing technology, and comprehensive solution systems are insufficient. Furthermore, there is no database specialized in measures for autonomous vehicles, making it difficult to derive solutions based on specialized information. Improving this situation is a challenge.

[1421] 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.

[1422] In this invention, the server includes means for receiving information about daily life troubles entered by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving responses from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for presenting the selected solution to the user, and means for quickly collecting trouble information when the autonomous vehicle encounters a breakdown or accident, asking for appropriate additional information, and analyzing the collected information. This allows for a prompt and accurate response even when the user encounters trouble with the autonomous vehicle, as the necessary information is quickly collected and appropriate questions and solutions are presented. Furthermore, the use of a specialized database allows for the provision of solutions based on more accurate information.

[1423] A "user terminal" is a device that users use to input information about troubles in their daily lives, such as a smartphone or computer.

[1424] A "server" is a computer system that has the function of analyzing trouble information received from a user terminal, generating appropriate questions, and presenting them to the user.

[1425] The "database" is an information collection system that stores reliable information such as past trouble cases, legal documents, insurance policies, car accident-related information, and repair procedures.

[1426] A "questionnaire" is a series of questions presented to a user to clarify the details of the problem, with the aim of gathering information to provide an appropriate solution.

[1427] "Natural language processing technology" is a technology that allows a machine to understand the text entered by the user and generate appropriate questions and solutions.

[1428] An "autonomous vehicle" is a vehicle that can drive autonomously.

[1429] "Trouble information" is information recorded when an autonomous vehicle encounters a problem such as a breakdown or accident.

[1430] A "solution" is a specific method of dealing with a problem that is presented to the user based on the collected information and database.

[1431] A "prompt" is a sentence that is input into a generative AI model and is used as the basis for deriving appropriate questions and solutions.

[1432] The system for implementing this invention comprises a user terminal, a server, and a database. The user terminal is a device for inputting information about the trouble a user encounters, such as a smartphone or computer. The trouble information input by the user is sent to the server.

[1433] The server is a Python server using the Flask framework that analyzes trouble information received from the user's device. Based on the analysis results, the server identifies the type of trouble and generates appropriate questions to present to the user's device. Natural language processing technology is used to generate the questions, and prompts are used to ask specific and appropriate questions.

[1434] For example, if a self-driving vehicle collides with another vehicle at an intersection, the server generates the following question:

[1435] "What type of accident was it (e.g., car collision, breakdown)?"

[1436] Please tell us the date, time and location of the accident.

[1437] "Please provide details about the victim or perpetrator."

[1438] Once the user answers these questions, the server collects and stores the answers and searches a database to find the optimal solution. The database includes reliable information such as past trouble cases, legal documents, insurance policies, car accident information, and repair procedures. Based on this information, the server selects the optimal solution and displays it on the user's device.

[1439] The specific software and hardware used are as follows:

[1440] Server: Python server using the Flask framework

[1441] Database: SQLite

[1442] Frontend: Smartphone client app

[1443] Data processing and data calculations include steps such as receiving user input, analyzing it, generating questions, collecting and storing answer information, searching a database, and selecting a solution.

[1444] Examples of specific prompts include:

[1445] Accident information: An autonomous vehicle collided with another vehicle at an intersection

[1446] Question 1: What type of accident was it (e.g. car collision, breakdown)?

[1447] Question 2: Please tell us the date, time and location of the accident.

[1448] Question 3: Please provide details about the victim or perpetrator.

[1449] This means that even if a user encounters a problem with an autonomous vehicle, the necessary information will be collected quickly and the appropriate questions and solutions will be presented, enabling a quick and accurate response.In addition, by using a specialized database, solutions can be provided based on more accurate information.

[1450] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1451] Step 1:

[1452] The user uses the device to input trouble information. This information may include, for example, "The autonomous vehicle collided with another vehicle at an intersection." The device receives this input information and sends it to the server.

[1453] Input: Trouble information entered by the user on the device

[1454] Output: Trouble information sent from the device to the server

[1455] Step 2:

[1456] The server analyzes the trouble information received from the device, identifies the type of trouble, and generates appropriate questions. This process uses natural language processing technology to create the necessary prompts.

[1457] Input: Trouble information sent from the device

[1458] Output: Generated questions and prompts

[1459] Specific operation: The server analyzes the trouble information and generates questions such as: "What type of accident was it (e.g., car collision, breakdown)?", "What time and place did the accident occur?", "Please provide details of the victim or perpetrator."

[1460] Step 3:

[1461] The server sends the generated questions to the user's terminal, where the user answers the questions and inputs the answer information.

[1462] Input: Server-generated questionnaire

[1463] Output: Questions presented to the user's device

[1464] Specific operation: The user answers questions on the device and inputs the following information: "Car collision," "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim suffered a broken arm."

[1465] Step 4:

[1466] The user terminal sends the user's answer information to the server, which collects and stores the received answer information.

[1467] Input: Answer information entered by the user on the device

[1468] Output: Answer information sent to the server

[1469] Specific operation: The user terminal sends the answer information to the server, and the server stores the information in a database.

[1470] Step 5:

[1471] The server uses the collected information to search databases, including law firm documents, court records, insurance policies, car accident information, and repair procedures, to find the best solution.

[1472] Input: Answer information saved on the server

[1473] Output: The correct solution retrieved from the database

[1474] What happens: The server queries the database to find and select the most appropriate solution.

[1475] Step 6:

[1476] The server generates the selected solution and presents the information to the user terminal.

[1477] Input: Solutions retrieved from the database

[1478] Output: The solution presented to the user

[1479] Specific operation: The server generates a solution and sends it to the user's device, displaying the following message to the user: "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1480] Furthermore, 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.

[1481] This is a consultation system that provides reliable solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also recognize the user's emotional state and respond accordingly.

[1482] System Overview

[1483] The system consists of the following elements:

[1484] 1. User Device

[1485] 2. Server

[1486] 3. Database

[1487] 4. Emotion Engine

[1488] Program processing flow

[1489] User device behavior

[1490] The user terminal provides an interface for the user to input information about the trouble. The user terminal displays an input form and receives information from the user.

[1491] Server Operation

[1492] The server analyzes the trouble information received from the user's device, generates appropriate questions to present to the user, and collects and stores the user's responses, searching the database based on that information to select and present the optimal solution.

[1493] The role of the emotional engine

[1494] The emotion engine analyzes the user's input and responses to identify the user's emotional state. Based on the identified emotional state, the server adjusts the wording of the solutions and questions it presents.

[1495] The role of the database

[1496] The database stores reliable sources such as past cases, law firm files, court records, insurance policies, etc. The server queries this database to find the best solution to the user's problem.

[1497] Program processing example

[1498] The operation of the system will be explained below using a specific example of a problem.

[1499] Example: A child hits an elderly person on a bicycle and injures them.

[1500] 1. User device operation

[1501] A user opens a web terminal and types in, "My child hit an elderly person on his bicycle and injured him."

[1502] The user terminal transmits this information to the server.

[1503] 2. Server Operation

[1504] The server analyzes the trouble information and identifies the type of accident as a "bicycle accident."

[1505] The server presents the user with the following questions: "Please tell us the date, time and location of the accident," "Please tell us the ages and conditions of the victim and perpetrator," and "Are there any witnesses?"

[1506] Users answer these questions and submit information: "10:00 AM on October 10, 2023, on the bike path in the park," "The victim was 70 years old and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching."

[1507] 3. Operation of the Emotion Engine

[1508] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[1509] The emotion engine reports the user's emotional state to the server.

[1510] 4. Server Data Processing

[1511] The server also takes into account information from the emotion engine when deciding how to respond to the user. For example, if a user is feeling anxious, the server will ask questions and give advice in a gentle and polite manner.

[1512] The server then generates a query to search the database based on the user's response information.

[1513] 5. Querying the Server

[1514] The server uses the generated query to search databases, which may include law firm files, court records, and insurance policies.

[1515] 6. Server Solution Selection

[1516] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[1517] The way solutions are presented is also adjusted based on the results of the emotion engine's analysis of user emotions.

[1518] 7. Server Solution Proposal

[1519] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps.

[1520] For example, "Promptly provide first aid to the victim and have them receive appropriate medical attention at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1521] Key Details

[1522] This system recognizes the user's emotions and adjusts its response accordingly, providing more appropriate and reliable support. The built-in emotion engine allows users to receive specific and appropriate advice to help them stay calm. The database contains a wealth of past cases, and natural language processing technology enables accurate analysis and response of user input.

[1523] The processing flow will be explained below.

[1524] Step 1:

[1525] A user opens a web terminal and enters information about the incident. For example, they might enter, "My child hit an elderly person on his bicycle and injured him."

[1526] Step 2:

[1527] The terminal transmits the input information to the server, which includes details of the problem.

[1528] Step 3:

[1529] The server analyzes the received trouble information using natural language processing technology, thereby identifying the type of trouble. For example, it identifies it as a "bicycle accident."

[1530] Step 4:

[1531] The server generates questions according to the type of accident. In the case of a bicycle accident, questions are generated such as the date and time of the accident, the location, the ages and conditions of those involved, and whether there were any witnesses.

[1532] Step 5:

[1533] The server sends the generated questions to the web terminal and presents them to the user. The presented questions are displayed on the web terminal screen.

[1534] Step 6:

[1535] The user enters answers to the questions displayed. For example, "The date and time of the accident was October 10, 2023, the location was a bicycle path in a park, the victim was 70 years old, the child was 10 years old, the victim had a broken arm, and the witnesses were another parent and child."

[1536] Step 7:

[1537] The device sends the user's response to the server, which includes detailed information about the accident.

[1538] Step 8:

[1539] The server organizes and stores the responses it receives from users, then uses this information to generate queries to search the database.

[1540] Step 9:

[1541] The emotion engine analyzes the user's input and responses to identify their emotional state, for example, detecting whether they are feeling anxious or scared.

[1542] Step 10:

[1543] The emotion engine reports the identified emotional state to the server, so that the server can take the emotional state into account.

[1544] Step 11:

[1545] The server takes into account the information from the emotion engine and decides how to respond to the user. For example, if a user feels anxious, it will ask questions and give advice in a gentle and polite manner.

[1546] Step 12:

[1547] The server generates a query and searches databases that include law firm files, court records, and insurance policies.

[1548] Step 13:

[1549] The server analyzes the information retrieved from the database and selects the optimal solution to the user's problem, such as "first aid," "reporting to the police," "contacting the insurance company," or "consulting a law firm."

[1550] Step 14:

[1551] The server summarizes the selected solutions in an easy-to-understand format and sends them to the web terminal. The summarized solutions include specific steps. For example, "Promptly administer first aid to the victim and have them receive appropriate medical treatment at a hospital. Next, report the accident to the police station and don't forget to report it to your insurance company. We also recommend that you consult a law firm."

[1552] Step 15:

[1553] The device displays solutions to the user, and the user takes appropriate action based on the advice provided, such as "Go to the police station to report the accident" or "Provide first aid to the victim."

[1554] Example 2

[1555] Next, a description will be given of 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."

[1556] In modern life, providing users with quick and appropriate solutions to the various problems they face is a major challenge. Providing an appropriate response can be particularly difficult depending on the specific nature of the problem and the user's emotional state. Conventional systems often provide only bureaucratic information without considering the user's emotions, so there is a need for a system that provides user-friendly and reliable solutions.

[1557] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving information about troubles in daily life input by the user, a means for presenting the user with questions according to the type of trouble, a means for collecting and saving answers from the user, a means for searching a database based on the collected information and selecting an appropriate solution, a means for identifying the emotional state of the user using an emotion analysis engine, and a means for adjusting questions to the user and solutions based on the identified emotional state. This allows a reliable solution according to the user's emotional state to be quickly provided, allowing the user to deal with the problem more calmly.

[1558] "Information entered by users regarding troubles in daily life" refers to details of problems and annoyances related to daily life that users enter using their own devices.

[1559] "Questions according to the type of problem" are questions that are automatically generated to collect necessary additional information based on the problem information entered by the user.

[1560] "Means for collecting and storing answers from users" refers to a function that receives answers entered by users to questions presented to them and stores them in storage such as a database.

[1561] "Means of searching the database and selecting the appropriate solution" is the process of searching related information in the database based on the collected information and finding the optimal solution.

[1562] "Means for presenting the selected solution to the user" refers to a function that sends the optimal solution selected through a database search to the user's terminal and displays it.

[1563] An "emotion analysis engine" is a software engine that analyzes user input and identifies the user's emotional state (e.g., anxiety, fear, joy, etc.).

[1564] "Means for adjusting questions and solutions to the user based on the identified emotional state" refers to a function that changes the wording of the questions and solutions presented to the user, taking into account the emotional state of the user identified by the emotion analysis engine.

[1565] "Natural language processing technology" refers to technology for analyzing and understanding natural language text entered by a user, and examples include text classification, sentiment analysis, and name recognition.

[1566] This invention is a consultation system that provides quick and appropriate solutions to problems users face in their daily lives. The system generates questions based on information input by the user and presents appropriate solutions by comparing the answers with a database. It can also analyze the user's emotional state and respond accordingly. The system consists of a user terminal, a server, a database, and an emotion analysis engine.

[1567] System Components

[1568] 1. User terminal: Provides an interface for users to enter trouble information. Specifically, it is provided in the form of a web page or mobile application, and sends the information entered by the user to the server.

[1569] 2. Server: Receives and analyzes the trouble information. In particular, the server uses natural language processing technology to determine the nature of the trouble and generate appropriate questions. Examples of natural language processing technology used include SpaCy and NLTK. The server also collects and stores responses from users and searches a database based on that information.

[1570] 3. Database: Stores reliable sources of information such as past cases, legal documents, court information, insurance policies, etc. The server queries this database to find the best solution.

[1571] 4. Sentiment analysis engine: Analyzes the user's input and responses to identify their emotional state (anxiety, fear, joy, etc.). The sentiment analysis engine uses IBM Watson Tone Analyzer and Microsoft Azure Text Analytics.

[1572] Program operation explanation

[1573] 1. User device operation: The user is presented with a form to enter details of the incident, and the data is sent to the server. For example, the user might enter, "My child hit an elderly person on his bicycle and injured him."

[1574] 2. Server operation:

[1575] Analyze trouble information to determine the type of accident and the characteristics of those involved.

[1576] Generate appropriate questions and present them to the user.

[1577] 3. Collecting user responses: The user enters answers to questions presented to them, such as "date, time and location of the accident," "age and condition of the victim and assailant," and "whether there were any witnesses."

[1578] 4. Sentiment analysis engine operation: Analyzes the user's input and answers to identify their emotional state. For example, if the user is feeling anxious, it reports that emotional state to the server.

[1579] 5. Database search: The server searches the database based on the user's answers and emotional information and selects the optimal solution.

[1580] 6. Emotional adjustment of the solution: Based on the results of the emotion analysis engine, the way the solution is expressed is adjusted, for example, to use gentler and more polite language.

[1581] 7. Solution Presentation: The server sends the selected solution to the user's device and presents it to the user, showing specific steps and next actions to take.

[1582] Prompt sentence examples

[1583] "What should you do if your child hits an elderly person on a bicycle and injures them?"

[1584] Specific examples

[1585] For example, if a user types into their device, "At 10:00 AM on October 10, 2023, a 10-year-old child hit a 70-year-old man on a park's bicycle path, breaking his arm," the server receives and analyzes this information. Detailed questions, such as the date, time, and location of the accident, the ages and conditions of the victim and assailant, and whether there were any witnesses, are then generated and presented to the user. When the user answers these questions, the system searches a database based on the user's answers and presents optimal solutions, such as first aid, reporting the incident to the police, contacting an insurance company, or consulting a law firm. Furthermore, if the emotion analysis engine determines that the user's emotions are unstable, the solution is adjusted to be more polite and reassuring.

[1586] As described above, the system of the present invention provides a quick and appropriate response while taking the user's feelings into consideration, thereby realizing more reliable support for the user.

[1587] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1588] Step 1:

[1589] Input: The user enters details of the problem into the terminal.

[1590] How it works: The user opens the device and inputs information about a problem in their daily life, such as "A child hit an elderly person on a bicycle and injured him." The device receives this information and sends it to the server in a format.

[1591] Output: Trouble information is sent from the terminal to the server.

[1592] Step 2:

[1593] Input: The server receives the trouble information sent by the user.

[1594] How it works: The server uses natural language processing techniques (e.g., SpaCy, NLTK) to analyze the received trouble information and identify the type of trouble and its key elements.

[1595] Output: The type of problem and the identified elements are stored on the server.

[1596] Step 3:

[1597] Input: Type of trouble analyzed and key factors.

[1598] How it works: Based on the type of problem identified, the server automatically generates questions to gather additional information. This can be done using a rule-based or template-based approach.

[1599] Output: The generated questionnaires are stored in the server.

[1600] Step 4:

[1601] Input: The generated questionnaire.

[1602] Operation: The server sends the generated questionnaire to the user's terminal and presents the questionnaire to the user.

[1603] Output: The questionnaire is displayed on the user's terminal.

[1604] Step 5:

[1605] Input: The user answers the questions posed.

[1606] How it works: The user answers questions by entering specific details, such as "October 10, 2023, 10:00 AM, on the bike path in the park," "The victim was 70 years old, and the child was 10 years old. The victim had a broken arm," and "Yes, another parent and child were watching." The device then sends these answers to the server.

[1607] Output: Answer information is sent from the user terminal to the server.

[1608] Step 6:

[1609] Input: User response information.

[1610] How it works: The server analyzes the received user responses and inputs them into a sentiment analysis engine, which uses tools such as IBM Watson Tone Analyzer and Microsoft Azure Text Analytics to identify the user's emotional state.

[1611] Output: The identified emotional state is stored in the server.

[1612] Step 7:

[1613] Input: User response information and emotional state from the sentiment analysis engine.

[1614] How it works: The server generates a query for database search based on the response information and emotional state. The query is formulated as an SQL statement or a NoSQL query.

[1615] Output: The generated queries are stored in the server.

[1616] Step 8:

[1617] Input: The generated query.

[1618] How it works: The server runs the generated query against a database to retrieve relevant information, such as legal documents, court information, and insurance policies.

[1619] Output: The relevant information is returned to the server.

[1620] Step 9:

[1621] Input: Relevant information returned from the database.

[1622] How it works: The server analyzes the relevant information it has obtained and selects an appropriate solution to the user's problem, such as "first aid," "reporting to the police," "contacting your insurance company," or "consulting a law firm."

[1623] Output: The selected solution is stored in the server.

[1624] Step 10:

[1625] Input: Selected solution and emotional state from the sentiment analysis engine.

[1626] How it works: The server adjusts the way the solution is phrased based on the user's emotional state. If the user is feeling anxious, the solution is phrased more gently and politely.

[1627] Output: The adjusted solution is stored in the server.

[1628] Step 11:

[1629] Input: Adjusted solution.

[1630] Operation: The server sends the final solution to the user's terminal and presents it to the user.

[1631] Output: The adjusted solution is displayed on the user's terminal.

[1632] (Application example 2)

[1633] Next, a description will be given of Application 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."

[1634] This invention is a consultation system that provides fast and reliable solutions to purchase-related problems and questions when users are searching for products on an online shopping site. However, current systems often cause dissatisfaction and anxiety because they are unable to respond appropriately while taking into account the user's emotional state. Furthermore, they do not fully utilize data such as past support cases and order history, making it difficult to provide optimal solutions.

[1635] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information about troubles in daily life input by the user, means for presenting the user with questions according to the type of trouble, means for collecting and saving answers from the user, means for searching a database based on the collected information and selecting an appropriate solution, means for analyzing the user's emotional state, and means for adjusting the way the solution is presented based on the analyzed emotional state. This enables an appropriate response according to the user's emotional state and makes it possible to provide a quick and reliable solution.

[1636] "Means for receiving information entered by users about troubles in daily life" refers to an interface or function that allows users to enter information about troubles or questions they have encountered and for the system to receive that information.

[1637] "Means for presenting questions to the user according to the type of trouble" is a function that automatically generates questions appropriate to the content of the trouble based on the information entered by the user and presents them to the user.

[1638] The "means for collecting and storing responses from users" refers to a system for collecting, recording, and storing responses entered by users to questions presented to them.

[1639] "Means of searching the database based on collected information and selecting an appropriate solution" is a function that uses information collected from the user to search for appropriate information in the database and selects the optimal solution from the results.

[1640] "Means for analyzing a user's emotional state" refers to an algorithm or system that analyzes a user's input and responses to identify their current emotional state.

[1641] The "means for adjusting the way in which a solution is presented based on the analyzed emotional state" is a function that changes the presentation of the solution provided depending on the user's emotional state, thereby providing a more appropriate and reassuring response.

[1642] "Law firm documents, court records, insurance policies, past order history, delivery status, and support case studies" are a wide range of data sources that are referenced when selecting solutions and provide reliable responses to user problems.

[1643] This is a consultation system that provides quick and reliable solutions to problems and questions about purchases when users are searching for products on online shopping sites. The system is composed of elements such as a user terminal, a server, a database, and a sentiment analysis engine.

[1644] System configuration

[1645] 1. User Device

[1646] The user terminal is a mobile device such as a smartphone or tablet, and provides an interface for users to input information about the problem. Users access the system by inputting information about their purchase or problem.

[1647] 2. Server

[1648] The server receives and analyzes information entered by users. Specifically, it generates questions based on the user's trouble information and presents them to the user. It also collects and stores the user's responses, uses this information to search a database, and selects the appropriate solution.

[1649] 3. Database

[1650] The database contains law firm documents, court records, insurance policies, as well as past order history, delivery status, support case studies, etc. The server searches this database to find the best solution for the user's problem.

[1651] 4. Sentiment Analysis Engine

[1652] The emotion analysis engine analyzes the user's input and identifies their emotional state. Based on the detected emotional state, the server adjusts its response to the user and presents a solution expression appropriate to the user's emotional state.

[1653] Implementation example

[1654] User device behavior

[1655] The user uses their smartphone to input information about the problem of not receiving the purchased product, and the user's device sends this information to the server.

[1656] Server Operation

[1657] The server analyzes the trouble information received from the user and identifies the type of trouble. For example, it determines that the product has not arrived, and generates questions to present to the user. Specific examples of questions include, "What is your order number?" and "When is the product expected to arrive?" When the user answers these questions, the information is collected and stored.

[1658] How the sentiment analysis engine works

[1659] The emotion analysis engine analyzes and identifies the user's emotional state from their input. For example, it may detect that the user is feeling anxious or irritated. The emotion analysis engine provides this information to the server, which then determines how to respond based on the user's emotional state.

[1660] Server data processing

[1661] The server searches a database based on the user's response information and emotional state to select an appropriate solution. The database includes information such as past order history, delivery status, and support case studies, so specific and reliable solutions can be obtained.

[1662] Proposing a solution

[1663] The selected solution is then presented to the user in a way that eases their concerns, such as, "Order number 123456 is currently on its way. If you do not receive your order within one week of the expected delivery date of October 15, 2023, please contact customer support. Additional notifications can be found within the app."

[1664] Specific prompts include "What is your order number?" and "When is the expected delivery date?"

[1665] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1666] Step 1:

[1667] The user device receives input information from the user. Specifically, the user enters details about the problem into the smartphone interface. For example, the input information, such as "The purchased product has not arrived," is sent to the server. The input at this stage is the details of the problem, and the output is the transmission of the problem information to the server.

[1668] Step 2:

[1669] The server analyzes the trouble information received from the user. The server uses natural language processing technology to analyze the input text and identify the type of trouble. In this step, the input trouble information is analyzed and the trouble category, for example, "item not delivered," is clarified. The output is the generation of questions based on the type of trouble.

[1670] Step 3:

[1671] The server generates questions according to the type of problem identified and sends them to the user's device. A generative AI model is used to generate specific questions. For example, questions such as "What is your order number?" or "When is the expected delivery date for the product?" are generated. The input for this step is the type of problem, and the output is the specific questions.

[1672] Step 4:

[1673] The user terminal presents the generated questions to the user and accepts the user's answers. The user inputs answers to the presented questions. For example, the user might input answers such as "The order number is 123456" or "The product is scheduled to arrive on October 15, 2023." The input at this stage is the answer to the questions, and the output is the transmission of the answer information to the server.

[1674] Step 5:

[1675] The server collects and stores the answers received from the user. Here, the user's answer data is stored in a database and the necessary information is extracted. The input of this step is the user's answer information, and the output is storage in the database.

[1676] Step 6:

[1677] The server searches the database based on the collected information and selects an appropriate solution. The server queries the database for past cases and related information to identify the optimal solution. The input for this step is the user's response information and the contents of the database, and the output is the selection of a solution.

[1678] Step 7:

[1679] The emotion analysis engine analyzes the user's emotional state. The server uses the emotion analysis engine to identify the user's emotional state from their input and responses. For example, it can detect that the user is feeling anxious or angry. The input for this step is the user's input and responses, and the output is the identified emotional state.

[1680] Step 8:

[1681] The server adjusts the way the solution is presented based on the analyzed emotional state. The server presents the solution in a gentle and polite manner depending on the user's emotional state. For example, the solution is adjusted to be something like, "Don't worry. Order number 123456 is currently being delivered. If you have any questions, please contact customer support." The input of this step is the emotional state and the selected solution, and the output is the presentation of the adjusted solution.

[1682] Step 9:

[1683] The server sends the adjusted solution to the user terminal and presents it to the user. The user terminal displays the adjusted solution, and the user can take action based on it. The input of this step is the adjusted solution, and the output is the solution presented to the user.

[1684] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding 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.

[1685] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with 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.

[1686] 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 robot 414.

[1687] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1688] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1689] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1690] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1691] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1692] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1693] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1694] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1695] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1696] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1697] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1698] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1699] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1700] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1701] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1702] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1703] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1704] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1705] The following is further disclosed regarding the above embodiment.

[1706] (Claim 1)

[1707] A means for receiving information about troubles in daily life input by a user;

[1708] A means for presenting questions to the user according to the type of trouble;

[1709] A means of collecting and storing responses from users;

[1710] A means of searching the database based on the collected information and selecting an appropriate solution;

[1711] a means for presenting the selected solution to the user; and

[1712] A system including:

[1713] (Claim 2)

[1714] 10. The system of claim 1, wherein the database includes law firm files, court records, insurance policies, and the like.

[1715] (Claim 3)

[1716] The system of claim 1, wherein natural language processing techniques are used in generating the questionnaire.

[1717] "Example 1"

[1718] (Claim 1)

[1719] A means for receiving information about troubles in daily life input by a user;

[1720] A means for analyzing the received trouble information and identifying the type of trouble;

[1721] A means for generating questions according to the type of trouble and presenting them to the user;

[1722] A means of collecting and storing responses from users;

[1723] A means of searching the database based on the collected information and selecting an appropriate solution;

[1724] a means for presenting the selected solution to the user; and

[1725] A system including:

[1726] (Claim 2)

[1727] 2. The system of claim 1, wherein the database includes past cases, legal documents, court records, insurance policies, etc.

[1728] (Claim 3)

[1729] The system of claim 1, wherein natural language processing techniques are used in generating the questionnaire.

[1730] "Application Example 1"

[1731] (Claim 1)

[1732] A means for receiving information about troubles in daily life input by a user;

[1733] A means for presenting questions to the user according to the type of trouble;

[1734] A means of collecting and storing responses from users;

[1735] A means of searching the database based on the collected information and selecting an appropriate solution;

[1736] a means for presenting the selected solution to the user; and

[1737] A means to quickly collect trouble information when an autonomous vehicle encounters a breakdown or accident, ask for appropriate additional information, and analyze the collected information;

[1738] A system including:

[1739] (Claim 2)

[1740] 10. The system of claim 1, wherein the database includes law firm files, court records, insurance policies, automobile accident related information, repair procedures, and the like.

[1741] (Claim 3)

[1742] The system of claim 1 , wherein natural language processing techniques and prompt sentences are used in generating the questionnaire.

[1743] "Example 2: Combining Emotion Engines"

[1744] (Claim 1)

[1745] A means for receiving information about troubles in daily life input by a user;

[1746] A means for presenting questions to the user according to the type of trouble;

[1747] A means of collecting and storing responses from users;

[1748] A means of searching the database based on the collected information and selecting an appropriate solution;

[1749] a means for presenting the selected solution to the user; and

[1750] a means for identifying the emotional state of a user using a sentiment analysis engine;

[1751] A means of tailoring user questions and solutions based on the identified emotional state; and

[1752] A system including:

[1753] (Claim 2)

[1754] 10. The system of claim 1, wherein the database includes legal documents, court information, insurance policies, and the like.

[1755] (Claim 3)

[1756] The system of claim 1, wherein natural language processing techniques are used in generating the questionnaire.

[1757] "Application example 2 when combining emotion engines"

[1758] (Claim 1)

[1759] A means for receiving information about troubles in daily life input by a user;

[1760] A means for presenting questions to the user according to the type of trouble;

[1761] A means of collecting and storing responses from users;

[1762] A means of searching the database based on the collected information and selecting an appropriate solution;

[1763] a means for presenting the selected solution to the user; and

[1764] a means for analyzing the emotional state of a user;

[1765] a means for adjusting the presentation of the solution based on the analyzed emotional state;

[1766] A system including:

[1767] (Claim 2)

[1768] 2. The system of claim 1, wherein the database includes law firm documents, court records, insurance policies, past order history, delivery status, support case studies, and the like.

[1769] (Claim 3)

[1770] The system of claim 1, wherein natural language processing techniques are used in generating the questionnaire. [Explanation of symbols]

[1771] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving information about troubles in daily life input by a user; A means for presenting questions to the user according to the type of trouble; A means of collecting and storing responses from users; A means of searching the database based on the collected information and selecting an appropriate solution; a means for presenting the selected solution to the user; and A system including:

2. 10. The system of claim 1, wherein said database includes law firm files, court records, insurance policies, and the like.

3. The system of claim 1 , wherein natural language processing techniques are used in generating the questionnaire.

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