System

Abstract

A system is provided.SOLUTION: The system of claim 1, wherein the AI life plan simulation engine generates an initial life plan simulation and returns the initial life plan simulation to the server, the server transmits the generated initial life plan to the user device, the user inputs feedback to the life plan and transmits the feedback to the server, and the server transmits the received feedback to the AI life plan simulation engine to update the AI life plan.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] In modern society, many people face financial anxiety and uncertainty about their future. Many people worry about how to manage their finances and create optimal plans, especially for major life events like marriage, their children's education, and buying a home. Traditionally, the most common way to resolve these issues has been to consult with a financial planner (FP), but finding a trustworthy FP can be quite stressful. Furthermore, FP advice is personal, and time and opportunity are limited, making it difficult for users to receive adequate support. Given these circumstances, there is a demand for a system that allows users to independently create and manage a reliable life plan. [Means for solving the problem]

[0005] The present invention provides a system in which an AI life plan simulation engine generates an initial life plan based on initial data input from a user terminal and dynamically updates the plan by receiving user feedback on the plan. Specifically, the system includes a means for a user to input initial data about the life plan and transmit the data to a server, a means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine, a means for the AI ​​life plan simulation engine to generate an initial life plan simulation and the server to transmit it to the user terminal, a means for the user to input feedback about the life plan and transmit the feedback to the server, and a means for the server to analyze the received feedback and transmit it to the AI ​​life plan simulation engine to update the plan. This system is also applicable when a user requests advice or simulates future scenarios, and can support users in creating an optimal life plan through an expert advice generation engine and future scenario generation. This allows users to independently adjust and manage their life plans without relying on a trusted financial planner.

[0006] A "user terminal" is an electronic device through which a user inputs data and interacts with the life plan via an interface.

[0007] The "server" is a central management system that analyzes data received from user terminals and sends necessary requests to each engine.

[0008] The "dialogue management server" is a system with server functions that receives data from users and manages collaboration with the AI ​​life plan simulation engine and the expert advice generation engine.

[0009] The "AI Life Plan Simulation Engine" is an AI module that generates and updates life plan simulations based on the user's initial data and feedback.

[0010] The "Expert Advice Generation Engine" is an AI module that generates advice in specialized fields (finance, insurance, real estate, etc.) based on specific requests from users.

[0011] "Initial data" refers to basic information (e.g., age, income, family structure, desired plan) that a user enters when starting a life plan simulation.

[0012] "Feedback" is data including opinions, requests, and correction requests provided by the user regarding the generated life plan.

[0013] A "life plan simulation" is a simulation result that visually shows future economic situations and financial plans, generated based on user input data and feedback.

[0014] A "request" is a request entered by a user when the user seeks specific advice or requests an update of a simulation.

[0015] "Future scenarios" are simulation results that simulate multiple future economic situations and living environments and identify scenarios that are favorable for the user and risks that should be avoided. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention relates to a system that enables users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[0038] System Overview

[0039] 1. User terminal: The user inputs initial data about their life plan (age, income, family structure, desired life events, etc.) through an interface. It is also an input device for providing feedback on the generated life plan and requesting specific advice.

[0040] 2. Server: A central system that analyzes data received from user devices and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user devices.

[0041] 3. Dialogue Management Server: This is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue.

[0042] 4. AI Life Plan Simulation Engine: This is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[0043] 5. Expert Advice Generation Engine: An AI module with expertise in specific fields such as finance, insurance, real estate, etc. It receives requests from users and generates relevant advice.

[0044] Program processing

[0045] Entering and submitting initial data

[0046] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[0047] The terminal receives the data entered by the user and transmits it to the server.

[0048] Analysis of initial data and generation of initial life plan

[0049] The server analyzes the received user initial data and transfers it to the dialogue management server.

[0050] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[0051] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[0052] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[0053] Enter feedback and update your plan

[0054] The user inputs feedback (e.g., requests for corrections or additions) on the presented life plan.

[0055] The terminal receives the user's feedback and transmits it to the server.

[0056] The server forwards the feedback to the interaction management server.

[0057] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[0058] The AI ​​life plan simulation engine updates the plan based on the new feedback and sends it back to the server.

[0059] The server transmits the updated life plan to the user terminal and displays it again.

[0060] Providing expert advice

[0061] A user enters a request for advice in a particular area (eg, mortgage, insurance).

[0062] The terminal receives the request and sends it to the server.

[0063] The server sends the request to the expert advice generation engine.

[0064] The expert advice generation engine generates expert advice based on the user's request and sends it back to the server.

[0065] The server transmits the generated advice to the user terminal and displays it to the user.

[0066] Generating future scenarios

[0067] A user inputs a request to simulate a future scenario.

[0068] The terminal receives the request and sends it to the server.

[0069] The server sends the request to the AI ​​life plan simulation engine.

[0070] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable for the user and those that require caution.

[0071] The server transmits the generated scenario to the user terminal and displays it to the user.

[0072] Specific examples

[0073] Example 1: Creating a life plan for buying a home

[0074] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[0075] The terminal transmits the input information to the server.

[0076] The server forwards the received information to the dialogue management server.

[0077] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[0078] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[0079] The server transmits the generated plan to the user terminal.

[0080] The user enters feedback on the plan and submits it again.

[0081] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[0082] Example 2: Educational Expenses Scenario Generation

[0083] A user enters a request to simulate a scenario regarding their child's education expenses.

[0084] The terminal sends a request to the server.

[0085] The server sends the request to the AI ​​life plan simulation engine.

[0086] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[0087] The server transmits the generated scenario to the user terminal.

[0088] The user selects the most suitable training plan based on multiple scenarios.

[0089] This allows users to independently create specific and reliable life plans, reduce anxiety about the future, and advance systematic life planning.

[0090] The processing flow will be explained below.

[0091] Step 1:

[0092] The user launches the life plan simulation app and enters personal information (age, income, family composition, desired life events, etc.).

[0093] Step 2:

[0094] The terminal receives the data entered by the user and transmits the data to the server.

[0095] Step 3:

[0096] The server transfers the received data to the dialogue management server.

[0097] Step 4:

[0098] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[0099] Step 5:

[0100] The AI ​​life plan simulation engine generates an initial life plan simulation based on the user's initial data.

[0101] Step 6:

[0102] The server receives the generated initial life plan and transmits it to the user terminal.

[0103] Step 7:

[0104] The user checks the life plan they received and enters feedback, corrections, and additional requests.

[0105] Step 8:

[0106] The terminal receives the user's feedback and transmits the feedback to the server.

[0107] Step 9:

[0108] The server forwards the received feedback to the interaction management server.

[0109] Step 10:

[0110] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[0111] Step 11:

[0112] The AI ​​life plan simulation engine updates the plan to reflect the new feedback and sends it back to the server.

[0113] Step 12:

[0114] The server transmits the updated life plan to the user terminal.

[0115] Step 13:

[0116] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[0117] Step 14:

[0118] The terminal receives the request and sends it to the server.

[0119] Step 15:

[0120] The server forwards the received request to the expert advice generation engine.

[0121] Step 16:

[0122] The expert advice generation engine generates expert advice based on the user's request and returns the results to the server.

[0123] Step 17:

[0124] The server transmits the generated advice to the user terminal.

[0125] Step 18:

[0126] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[0127] Step 19:

[0128] The terminal receives the simulation request and sends it to the server.

[0129] Step 20:

[0130] The server sends the request to the AI ​​life plan simulation engine.

[0131] Step 21:

[0132] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[0133] Step 22:

[0134] The server transmits the generated scenario to the user terminal.

[0135] Step 23:

[0136] The user reviews the provided scenarios, selects the most suitable life plan, and enters that selection into the system.

[0137] Step 24:

[0138] The terminal receives the user's final selection and transmits it to the server.

[0139] Step 25:

[0140] The server sends the final selection to the dialogue management server, requesting the generation of a final life plan.

[0141] Step 26:

[0142] The AI ​​life plan simulation engine generates the final life plan and sends it back to the server.

[0143] Step 27:

[0144] The server transmits the final life plan to the user terminal and displays it to the user.

[0145] Through these steps, we have created a system that allows users to dynamically and interactively create and update their life plans and receive expert advice to form the optimal life plan.

[0146] Example 1

[0147] 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."

[0148] Conventional life plan creation systems have the problem that it is difficult for users to obtain appropriate advice when they do not have specialized knowledge or when they have limited access to advice, and they are unable to fully meet the needs of users. Another problem is that simulating and updating a life plan is time-consuming and tedious. The purpose of this invention is to solve these problems and enable users to effectively create and manage their life plans on their own.

[0149] 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.

[0150] In this invention, the server includes: means for a user terminal to input initial data regarding a life plan and transmit the data to the server; means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine via the dialogue management server; means for the AI ​​life plan simulation engine to generate an initial life plan simulation and transmit it back to the server; means for the server to transmit the generated initial life plan to the user terminal; means for the user to input feedback regarding the life plan and transmit the feedback to the server; and means for transmitting the feedback received by the server to the AI ​​life plan simulation engine via the dialogue management server to update the plan. This enables the AI ​​to dynamically generate and update a life plan and obtain expert advice based on the initial data and feedback input by the user.

[0151] A "user terminal" is a device through which a user inputs data related to their life plan and communicates with the server.

[0152] The "server" is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management server and various engines.

[0153] The "dialogue management server" is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine.

[0154] The "AI Life Plan Simulation Engine" is an AI module that generates and updates life plan simulations based on the user's initial data and feedback.

[0155] An "expert advice generation engine" is an AI module that has expertise in a specific field and generates expert advice based on requests from users.

[0156] "Initial data" refers to basic information that a user inputs to create a life plan, and includes age, income, family structure, desired life events, and the like.

[0157] "Feedback" refers to opinions and requests, such as corrections and additions, provided by the user regarding the generated life plan.

[0158] A "request" is input data that a user inputs to the server, requesting specific advice or a simulation of a future scenario.

[0159] "Simulation" refers to the process of predicting and generating future life plans and multiple future scenarios carried out by an AI life plan simulation engine.

[0160] This invention relates to a system that allows users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[0161] System Overview

[0162] User terminal

[0163] The user terminal is a device where a user inputs initial data about their life plan and transmits that data to a server. The user terminal has an interface through which the user inputs initial data such as age, income, family composition, and desired life events through an application. The user terminal is also an input device for providing feedback on the generated life plan and requesting specific advice.

[0164] server

[0165] The server is a central system that analyzes data received from user terminals and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user terminal. The server also collaborates with the expert advice generation engine to provide expert advice.

[0166] Dialogue Management Server

[0167] The dialogue management server is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue and sends the initial data and feedback received from users to each engine.

[0168] AI life plan simulation engine

[0169] The AI ​​life plan simulation engine is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[0170] Expert Advice Generation Engine

[0171] An expert advice generation engine is an AI module with specialized knowledge in a specific field, such as finance, insurance, or real estate, that receives requests from users and generates relevant advice.

[0172] Specific examples

[0173] Example 1: Creating a life plan for buying a home

[0174] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[0175] The terminal transmits the input information to the server.

[0176] The server forwards the received information to the dialogue management server.

[0177] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[0178] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[0179] The server transmits the generated plan to the user terminal.

[0180] The user enters feedback on the plan and submits it again.

[0181] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[0182] Example 2: Educational Expenses Scenario Generation

[0183] A user enters a request to simulate a scenario regarding their child's education expenses.

[0184] The terminal sends a request to the server.

[0185] The server sends the request to the AI ​​life plan simulation engine.

[0186] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[0187] The server transmits the generated scenario to the user terminal.

[0188] The user selects the most suitable training plan based on multiple scenarios.

[0189] Prompt Sentence Examples

[0190] 1. "Generate a life plan based on your home buying budget and desired area."

[0191] 2. "Simulate several scenarios for your child's education expenses."

[0192] This system allows users to independently create specific and reliable life plans, reducing anxiety about the future and enabling them to plan their lives in a planned manner.

[0193] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0194] Step 1: Enter initial data

[0195] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[0196] Input: Any initial data that a user enters into an app form.

[0197] Output: The input data is compiled as JSON format data.

[0198] What happens: Data is collected when a user fills out a form on the app and clicks the "Submit" button.

[0199] Step 2: Sending initial data

[0200] The terminal receives the initial data entered by the user and transmits it to the server.

[0201] Input: Initial data in JSON format.

[0202] Output: The initial data sent to the server.

[0203] Specific operation: The terminal's data transmission module sends the initial data to the server using an HTTPS request.

[0204] Step 3: Analyze the initial data

[0205] The server analyzes the received initial data and forwards it to the dialogue management server.

[0206] Input: The initial data received by the server in JSON format.

[0207] Output: The parsed data is transferred to the dialogue management server.

[0208] Specific operation: The server analyzes the initial data using a data analysis algorithm, and then reformats and transmits the analysis results to the dialogue management server.

[0209] Step 4: Submitting a simulation request

[0210] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[0211] Input: Analysis results based on initial data.

[0212] Output: The request sent to the AI ​​life plan simulation engine.

[0213] Specific operation: The dialogue management server formats the analysis results into a format that the AI ​​engine can understand and submits a request via API.

[0214] Step 5: Generate an initial life plan

[0215] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[0216] Input: The request data received from the server.

[0217] Output: Generated initial life plan.

[0218] How it works: The AI ​​engine uses past data and statistical models to generate a life plan that best suits the user's initial data.

[0219] Step 6: Displaying your initial life plan

[0220] The server transmits the generated initial life plan to the user terminal.

[0221] Input: Initial life plan returned from the AI ​​life plan simulation engine.

[0222] Output: The initial life plan sent to the user's device.

[0223] Specific operation: The server re-encodes the life plan data into JSON format and sends it to the user's device as an HTTPS response.

[0224] Step 7: Provide feedback

[0225] The user inputs feedback (e.g., requests for corrections or additions) on the presented life plan.

[0226] Input: Feedback based on the life plan provided.

[0227] Output: The input feedback data.

[0228] Specific behavior: A user fills in the required information in the app's feedback form and clicks the "Submit Feedback" button.

[0229] Step 8: Submit your feedback

[0230] The terminal receives the user's feedback and transmits it to the server.

[0231] Input: User feedback data.

[0232] Output: Feedback data sent to the server.

[0233] Specific operation: The device obtains the feedback data and issues an HTTPS request to the server.

[0234] Step 9: Analyze feedback

[0235] The server forwards the feedback to the interaction management server.

[0236] Input: The feedback data received by the server.

[0237] Output: Feedback data transmitted to the dialogue management server.

[0238] Specific operation: The server checks the received feedback data and notifies the dialogue management server.

[0239] Step 10: Submit a plan renewal request

[0240] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[0241] Input: User feedback data.

[0242] Output: Update request to the AI ​​life plan simulation engine.

[0243] Specific operation: Based on the feedback received, the dialogue management server issues an API request to send an update instruction.

[0244] Step 11: Update your plan

[0245] The AI ​​life plan simulation engine updates the plan based on the new feedback and sends it back to the server.

[0246] Input: The update request received from the server.

[0247] Output: Updated life plan.

[0248] What it does: The AI ​​engine generates an updated simulation, taking into account new data inputs.

[0249] Step 12: View the updated plan

[0250] The server transmits the updated life plan to the user terminal and displays it again.

[0251] Input: Updated life plan returned from the AI ​​life plan simulation engine.

[0252] Output: The updated life plan sent to the user device.

[0253] Specific operation: The server notifies the user device of the received update plan data and sends it again as display data.

[0254] Step 13: Fill out your advice request

[0255] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[0256] Input: The content of your advice request.

[0257] Output: The input advice request.

[0258] What happens: A user fills out the "Advice Request" form in the app and clicks the "Submit" button.

[0259] Step 14: Submitting the Request

[0260] The terminal receives the request and sends it to the server.

[0261] Input: User advice request data.

[0262] Output: The advice request data sent to the server.

[0263] Specific operation: The device obtains the request data and issues an HTTPS request to the server.

[0264] Step 15: Submitting an Advice Generation Request

[0265] The server sends the request to the expert advice generation engine via the dialogue management server.

[0266] Input: User advice request data.

[0267] Output: A request to the Expert Advice generation engine.

[0268] What happens: The server formats the request data appropriately and makes an API call to the Expert Advice generation engine.

[0269] Step 16: Generating Advice

[0270] The expert advice generation engine generates expert advice based on the user's request and sends it back to the server.

[0271] Input: The request data received from the server.

[0272] Output: The generated advice.

[0273] Specific behavior: The engine references relational databases and knowledge bases to generate specific advice tailored to the user's situation.

[0274] Step 17: Viewing Advice

[0275] The server transmits the generated advice to the user terminal and displays it to the user.

[0276] Input: Advice returned from the Expert Advice generation engine.

[0277] Output: Advice sent to the user's terminal.

[0278] Specific operation: The server transfers the received advice data to the user's device and displays it within the app.

[0279] Step 18: Entering Scenario Requests

[0280] A user inputs a request to simulate a future scenario.

[0281] Input: The contents of the scenario request.

[0282] Output: The input scenario request.

[0283] Specific behavior: The user fills out the app's "Scenario Simulation" form and clicks the "Submit" button.

[0284] Step 19: Submitting the Request

[0285] The terminal receives the request and sends it to the server.

[0286] Input: User's scenario request data.

[0287] Output: The scenario request data sent to the server.

[0288] Specific operation: The device obtains the request data and issues an HTTPS request to the server.

[0289] Step 20: Submitting a Simulation Request

[0290] The server sends the request to the AI ​​life plan simulation engine via the dialogue management server.

[0291] Input: User's scenario request data.

[0292] Output: A request to the AI ​​life plan simulation engine.

[0293] Specific operation: The server formats the request data appropriately and makes an API call to the AI ​​engine.

[0294] Step 21: Generate scenarios

[0295] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable for the user and those that require caution.

[0296] Input: Scenario request data received from the server.

[0297] Output: Generated future scenarios.

[0298] How it works: The AI ​​engine uses statistical models and predictive algorithms to simulate different future scenarios and assess the benefits and risks of each.

[0299] Step 22: Viewing the scenario

[0300] The server transmits the generated scenario to the user terminal and displays it to the user.

[0301] Input: Scenario returned from the AI ​​life plan simulation engine.

[0302] Output: The scenario sent to the user's device.

[0303] Specific operation: The server transfers the received scenario data to the user's device and displays it within the app.

[0304] (Application example 1)

[0305] 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."

[0306] In modern society, it is extremely important for individuals to effectively manage their own life plans and financial plans. However, it is difficult for ordinary users without specialized knowledge to do this on their own, as they are required to understand complex information and analyze vast amounts of data. To solve this problem, there is a need for a system that allows users to easily create and manage their life plans and receive professional financial advice.

[0307] 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.

[0308] In this invention, the server includes means for a user terminal to input initial data regarding a life plan and transmit the data to the server, means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine, means for the AI ​​life plan simulation engine to generate an initial life plan simulation and transmit it back to the server, means for the server to transmit the generated initial life plan to the user terminal, means for the user to input feedback regarding the life plan and transmit the feedback to the server, means for the server to transmit the received feedback to the AI ​​life plan simulation engine to update the plan, and means for the user terminal to input financial data and transmit the data to the AI ​​life plan simulation engine. The system includes a means for transmitting the financial plan to a cloud server, a means for the cloud server to analyze the received data and transmit it to an AI life plan simulation engine, a means for the AI ​​life plan simulation engine to generate a financial plan and return it to the cloud server, a means for the cloud server to transmit the generated financial plan to a user terminal, a means for the user terminal to request advice on a specific field and transmit the request to the server, a means for the server to transmit the received request to an expert advice generation engine, a means for the expert advice generation engine to generate expert advice based on the user request and transmit it back to the server, and a means for the server to transmit the generated advice to the user terminal. This allows users to create their own life plans and easily receive expert advice. It also allows users to understand their own financial situation and effectively manage their future plans.

[0309] A "user terminal" is a device that allows a user to input, send, and receive life plans and financial data.

[0310] A "server" is a central control device that analyzes data received from user terminals and coordinates with other engines and servers.

[0311] The "AI Life Plan Simulation Engine" is an artificial intelligence module that generates and updates life plans and financial plans based on the user's initial data and feedback.

[0312] A "cloud server" is a remote server on the Internet for receiving data from a user terminal and transmitting the analyzed and generated plan to the user terminal.

[0313] An "expert advice generation engine" is an artificial intelligence module that generates expert advice on a specific subject based on a user's request.

[0314] A "life plan" is a plan for a user's life planning, and is an overall strategy that takes into consideration age, income, family structure, desired life events, and the like.

[0315] "Feedback" refers to inputting corrections or additional requests for plans or proposals provided by the user.

[0316] "Specific fields" refer to areas requiring specialized knowledge, such as finance, insurance, real estate, and education expenses.

[0317] "Financial Data" is information related to a user's personal financial situation, such as their income, expenses, and savings goals.

[0318] A "financial plan" is a plan for short-term and long-term income and expenditure management and asset formation that is generated based on the user's financial data.

[0319] A "future financial scenario" is a simulation of future income and expenditures and asset status that is generated based on the user's financial data.

[0320] A "request" is a request submitted by a user for a particular piece of advice or simulation.

[0321] "Analysis" is the process of processing received data and extracting meaningful information.

[0322] A "system" is a structure in which multiple hardware and software components work together to provide a specific function.

[0323] The present invention is a system that allows users to conveniently create and manage their own life plans and financial plans. This system consists of a user terminal, a cloud server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[0324] System Overview

[0325] 1. User Device:

[0326] The user terminal is a device where users input, send, and receive their life plan and financial data. Users input initial data such as age, income, family composition, and desired life events through a smartphone app and send the data to the cloud server.

[0327] 2. Cloud Server:

[0328] The cloud server is a central control unit that analyzes data received from user devices and coordinates with other engines and servers. The cloud server transmits the received data to the dialogue management server and sends requests for analysis and calculation.

[0329] 3. Dialogue Management Server:

[0330] The dialogue management server is responsible for linking the AI ​​life plan simulation engine and the expert advice generation engine based on user input data, and plays a role in appropriately distributing user requests and sending them to each engine.

[0331] 4. AI Life Plan Simulation Engine:

[0332] The AI ​​Life Plan Simulation Engine is an artificial intelligence module that generates and updates initial life plans and financial plans based on the user's initial data and feedback. The engine is implemented using machine learning frameworks such as TensorFlow or PyTorch.

[0333] 5. Expert advice generation engine:

[0334] An expert advice generation engine is an AI module that generates expert advice on a specific subject based on user requests, using natural language processing models such as GPT-3 or BERT.

[0335] Specific examples

[0336] Example 1: Creating a life plan for buying a home

[0337] The user enters information such as their home purchase budget, loan amount, and desired area through a smartphone app. The smartphone app sends the entered information to a cloud server, which then sends the data to the AI ​​life plan simulation engine via a dialogue management server. The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the cloud server. The cloud server then sends the generated plan to the smartphone app and displays it to the user. The user then enters feedback on this plan and submits it again. This allows the plan to be dynamically updated based on the feedback, and the final plan is finalized.

[0338] Prompt Sentence Examples

[0339] "The user is 35 years old, has an annual income of 6 million yen, and consists of a couple and two children. If they plan to purchase a home within the next five years, please provide specific advice on what type of loan and financial management they should take, and which area would be suitable."

[0340] This system allows users to create their own life plans and easily receive professional advice, while also helping users understand their own financial situation and effectively manage their future plans.

[0341] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0342] Step 1:

[0343] The user launches the smartphone app and enters initial data such as age, income, family composition, and desired life events. The entered data is temporarily stored in the smartphone app's local storage. The user then presses the "Send" button, which sends the data to the cloud server.

[0344] Input: Age, income, family structure, desired life events

[0345] Output: Initial data sent to the cloud server

[0346] Step 2:

[0347] The cloud server analyzes the initial data received from the user terminal and sends it to the dialogue management server, which converts the received data into a format required to send it as a request to the AI ​​life plan simulation engine.

[0348] Input: Initial data from the user's terminal

[0349] Output: Data in request format to the dialogue management server

[0350] Step 3:

[0351] The dialogue management server sends the received initial data to the AI ​​life plan simulation engine, which performs calculations to generate an initial life plan based on the data. Specifically, an algorithm is executed to generate an optimal financial plan based on the user's age, income, and family structure.

[0352] Input: Initial data from the dialogue management server

[0353] Output: Generated initial life plan

[0354] Step 4:

[0355] The AI ​​life plan simulation engine returns the generated initial life plan to the cloud server, which then transmits the generated life plan to the user's device.

[0356] Input: Initial life plan

[0357] Output: Data sent to the user terminal

[0358] Step 5:

[0359] The user checks the initial life plan presented on the smartphone app and enters feedback as necessary. Feedback can include requests for revisions or additions to the plan. When the user presses the "Send Feedback" button, the feedback data is sent to the cloud server.

[0360] Input: User feedback

[0361] Output: Feedback data to the cloud server

[0362] Step 6:

[0363] The cloud server analyzes the feedback received from the user and sends it to the AI ​​life plan simulation engine via the dialogue management server. The AI ​​life plan simulation engine generates a new life plan that reflects the feedback.

[0364] Input: Feedback data

[0365] Output: Updated Life Plan

[0366] Step 7:

[0367] The updated life plan is sent to the user's device via the cloud server. The user reviews the life plan again and provides additional feedback if necessary. This process is repeated until a plan that satisfies the user is generated.

[0368] Input: Updated Life Plan

[0369] Output: Data sent to the user terminal

[0370] Step 8:

[0371] When a user requests advice on a specific topic, they input the request through a smartphone app and send it to a cloud server. For example, they can ask for advice on investment strategies or how to choose a loan.

[0372] Input: Request for advice on a specific subject

[0373] Output: Request data to the cloud server

[0374] Step 9:

[0375] The cloud server sends the received request to an expert advice generation engine, which generates expert advice based on the request and sends it back to the cloud server.

[0376] Input: Request for advice

[0377] Output: Generated expert advice

[0378] Step 10:

[0379] The cloud server sends the generated expert advice to the user's device, where the user can check the expert advice on the smartphone app and decide on the next action to take if necessary.

[0380] Enter: Expert Advice

[0381] Output: Data sent to the user terminal

[0382] 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.

[0383] This invention relates to a system that enables users to independently create and manage their life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine.

[0384] System Overview

[0385] 1. User Device:

[0386] Through the interface, users input initial data about their life plan (age, income, family composition, desired life events, etc.).

[0387] The user terminal receives the user's input data and transmits it to the server.

[0388] An input device that allows a user to enter a request for feedback or specific advice.

[0389] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[0390] 2. Server:

[0391] It is a central system that analyzes data received from user terminals and manages collaboration with the dialogue management server and various engines.

[0392] The initial data, feedback, and emotion data are transferred to the dialogue management server, and the response is sent to the user terminal.

[0393] 3. Dialogue Management Server:

[0394] It is an interface server that receives and analyzes data from users and links with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[0395] 4. AI Life Plan Simulation Engine:

[0396] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[0397] It has the ability to verbalize and quantify users' vague anxieties and requests.

[0398] 5. Expert advice generation engine:

[0399] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[0400] It receives requests from users and generates relevant advice.

[0401] 6. Emotion Engine:

[0402] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to the dialogue management server.

[0403] Optimize the results of life plan simulations and expert advice based on emotional data.

[0404] Program processing

[0405] Enter and submit initial data:

[0406] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[0407] The user terminal receives the data entered by the user and transmits it to the server.

[0408] Analysis of initial data and generation of life plan:

[0409] The server transfers the received data to the dialogue management server.

[0410] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[0411] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[0412] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[0413] Leave feedback and update your plan:

[0414] The user enters feedback about the plan (e.g., correction requests, additional requests).

[0415] The user terminal receives the feedback data and causes the emotion engine to analyze the emotion data.

[0416] The device sends the feedback along with the emotion data to the server.

[0417] The server forwards the feedback and emotion data to the dialogue management server.

[0418] The dialogue management server analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[0419] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[0420] The server transmits the updated life plan to the user terminal and displays it again.

[0421] Requesting and Providing Expert Advice:

[0422] A user enters a request for expert advice in a particular area (e.g., mortgage, insurance).

[0423] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[0424] The device sends the emotion data along with the request to the server.

[0425] The server sends the request and emotion data to the expert advice generation engine.

[0426] An expert advice generation engine generates advice based on the emotion data and returns it to the server.

[0427] The server transmits the generated advice to the user terminal and displays it to the user.

[0428] Generate future scenarios:

[0429] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[0430] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[0431] The device sends the request and emotion data to the server.

[0432] The server sends the request and emotion data to the dialogue management server.

[0433] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[0434] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[0435] The server transmits the generated scenario to the user terminal and displays it to the user.

[0436] Specific examples

[0437] Example 1: Creating a life plan for buying a home

[0438] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[0439] The user terminal transmits the input information to the server.

[0440] The server forwards the received information to the dialogue management server.

[0441] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[0442] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[0443] The server transmits the generated plan to the user terminal.

[0444] The user provides feedback on the plan.

[0445] The user terminal causes the emotion engine to analyze the emotion data along with the feedback, and transmits it to the server.

[0446] From then on, the plan is dynamically updated based on user feedback and emotion data, and the final plan is finalized.

[0447] Example 2: Educational Expenses Scenario Generation

[0448] A user enters a request to simulate a scenario regarding their child's education expenses.

[0449] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[0450] The device sends the request and emotion data to the server.

[0451] The server forwards the request to the interaction management server.

[0452] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[0453] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school chosen, and identifies the appropriate scenario for the user.

[0454] The server transmits the generated scenario to the user terminal.

[0455] The user selects the most suitable educational plan based on the provided scenario.

[0456] This allows users to independently create specific and reliable life plans, reducing future anxiety and promoting systematic life planning. Furthermore, the emotion engine takes the user's emotional state into account, enabling more personalized and appropriate planning.

[0457] The processing flow will be explained below.

[0458] Step 1:

[0459] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[0460] Step 2:

[0461] The terminal receives the data entered by the user and transmits the data to the server.

[0462] Step 3:

[0463] The emotion engine collects emotional data from the user's facial expressions, voice, and text input.

[0464] Step 4:

[0465] The terminal receives the emotion data and transmits it to the server together with the initial data.

[0466] Step 5:

[0467] The server transfers the received initial data and emotion data to the dialogue management server.

[0468] Step 6:

[0469] The dialogue management server analyzes the initial data and emotional data and sends a request to the AI ​​life plan simulation engine.

[0470] Step 7:

[0471] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and emotional data and sends it back to the server.

[0472] Step 8:

[0473] The server transmits the generated initial life plan to the user terminal.

[0474] Step 9:

[0475] The user reviews the initial life plan and enters feedback, corrections, and additional requests.

[0476] Step 10:

[0477] The terminal receives the user's feedback and runs the emotion engine again to update the emotion data.

[0478] Step 11:

[0479] The device sends the user's feedback and updated emotion data to the server.

[0480] Step 12:

[0481] The server transfers the received feedback and emotion data to the dialogue management server.

[0482] Step 13:

[0483] The dialogue management server analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[0484] Step 14:

[0485] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[0486] Step 15:

[0487] The server transmits the updated life plan to the user terminal.

[0488] Step 16:

[0489] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[0490] Step 17:

[0491] The terminal receives the request and causes the emotion engine to update the emotion data.

[0492] Step 18:

[0493] The device sends the request and emotion data to the server.

[0494] Step 19:

[0495] The server sends the request and emotion data to the expert advice generation engine.

[0496] Step 20:

[0497] An expert advice generation engine generates expert advice based on the emotion data and sends it back to the server.

[0498] Step 21:

[0499] The server transmits the generated advice to the user terminal.

[0500] Step 22:

[0501] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[0502] Step 23:

[0503] The terminal receives the simulation request and causes the emotion engine to update the emotion data.

[0504] Step 24:

[0505] The device sends the request and emotion data to the server.

[0506] Step 25:

[0507] The server transfers the request and the emotion data to the dialogue management server.

[0508] Step 26:

[0509] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[0510] Step 27:

[0511] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[0512] Step 28:

[0513] The server transmits the generated scenario to the user terminal.

[0514] Step 29:

[0515] The user reviews the provided scenarios, selects the most suitable life plan, and inputs the selection into the terminal.

[0516] Step 30:

[0517] The terminal receives the user's final selection and causes the emotion engine to update the emotion data.

[0518] Step 31:

[0519] The terminal transmits the user's final selection and emotion data to the server.

[0520] Step 32:

[0521] The server sends the final selection and emotion data to the dialogue management server, requesting it to generate a final life plan.

[0522] Step 33:

[0523] The AI ​​life plan simulation engine generates the final life plan and returns the results, taking into account emotional data, to the server.

[0524] Step 34:

[0525] The server transmits the final life plan to the user terminal and displays it to the user.

[0526] Through these steps, users can dynamically and interactively create and update their life plans, and receive expert advice to create the optimal life plan. Furthermore, the introduction of an emotion engine enables personalized planning that takes into account the user's emotional state.

[0527] Example 2

[0528] 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."

[0529] Conventional life plan creation systems make it difficult for users to independently create a balanced life plan, and it is difficult to achieve optimal planning when users lack specialized knowledge. Furthermore, there are insufficient means to consider users' emotions and feedback, making it difficult to provide personalized advice.

[0530] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0531] In this invention, the server includes a means for inputting initial data related to a life plan from a user terminal and transmitting the data to the server, a means for the server to analyze the received initial data and transfer it to a dialogue management computer, and a means for the dialogue management computer to analyze the received data and send a request to the AI ​​life plan simulation engine. This allows users to independently create a well-balanced life plan without specialized knowledge. Furthermore, a system is realized that takes into account the user's emotions and feedback and provides personalized advice.

[0532] A "user terminal" is an interface through which a user inputs data related to a life plan and transmits the data to a server.

[0533] A "server" is a central system that analyzes data received from user terminals and transfers the data to various engines and computers.

[0534] The "dialogue management computer" is a computer system that has the function of analyzing data received from the server and sending requests to the AI ​​life plan simulation engine.

[0535] The "AI Life Plan Simulation Engine" is an artificial intelligence module that generates and updates life plans based on the user's initial data and feedback.

[0536] An "expert advice generation engine" is an artificial intelligence module that generates advice based on user requests and emotional data, using specialized knowledge in a specific field.

[0537] "Emotion data" is data that indicates the emotional state of the user, obtained from facial expressions, voice, text input, and the like.

[0538] "Feedback" is data that indicates opinions and requests for revisions regarding the life plan and advice provided by the user.

[0539] A "future scenario" is a plan for simulating various situations in the future, such as fluctuations in income and changes in economic conditions.

[0540] "Initial data" refers to data such as age, income, family structure, and desired life events that the user inputs as basic information for creating a life plan.

[0541] This invention relates to a system that allows users to independently create and manage their own life plans. This system is composed of the following components: a user terminal, a server, a dialogue management computer, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine.

[0542] System configuration

[0543] 1. User Device:

[0544] Users use the life plan simulation app to input initial data such as age, income, family composition, and desired life events.

[0545] The user terminal receives and transmits input data to the server, and is also an input device for inputting user feedback and specific advice requests.

[0546] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[0547] 2. Server:

[0548] The server is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management computer and various engines.

[0549] The server transfers the initial data, feedback, and emotion data to the dialogue management computer, and sends the response to the user terminal.

[0550] 3. Dialogue Management Computer:

[0551] The dialogue management computer is an interface server that analyzes data from the server and works with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[0552] 4. AI Life Plan Simulation Engine:

[0553] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[0554] It has the ability to verbalize and quantify users' vague anxieties and requests.

[0555] 5. Expert advice generation engine:

[0556] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[0557] It receives requests from users and generates relevant advice.

[0558] 6. Emotion Engine:

[0559] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to a dialogue management computer.

[0560] Optimize the results of life plan simulations and expert advice based on emotional data.

[0561] Specific examples

[0562] Example 1: Creating a life plan for buying a home

[0563] The user enters the following information: "30 years old, annual income 5 million yen, family composition 1 spouse, 2 children, desired life event is to buy a home at age 35."

[0564] The user terminal transmits this data to the server.

[0565] The server transfers the user's input data to the dialogue management computer.

[0566] The dialogue management computer analyzes the data and sends requests to the AI ​​life plan simulation engine.

[0567] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[0568] The server transmits the generated plan to the user terminal.

[0569] The user provides feedback on the plan.

[0570] The user terminal causes the emotion engine to analyze the emotion data along with the feedback, and transmits it to the server.

[0571] From then on, the plan is dynamically updated based on user feedback and emotion data, and the final plan is finalized.

[0572] Example prompt: "User's initial life plan data: age 30, annual income 5 million yen, family composition: 1 spouse, 2 children, desired event: purchase a home at age 35."

[0573] Example 2: Educational Expense Scenario Generation

[0574] A user inputs a request to simulate a scenario regarding a child's education expenses.

[0575] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[0576] The device sends the request and emotion data to the server.

[0577] The server forwards the request to the dialogue management computer.

[0578] The dialogue management computer sends requests and emotional data to the AI ​​life plan simulation engine.

[0579] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school chosen, and identifies the appropriate scenario for the user.

[0580] The server transmits the generated scenario to the user terminal.

[0581] The user selects the most suitable educational plan based on the provided scenario.

[0582] Example prompt: "Future income change scenario: Generate a life plan taking into account income changes over the next 10 years."

[0583] This allows users to independently create specific and reliable life plans, reducing future anxiety and promoting systematic life planning. Furthermore, the emotion engine takes the user's emotional state into account, enabling more personalized and appropriate planning.

[0584] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0585] Program processing flow

[0586] Entering and submitting initial data

[0587] Step 1:

[0588] The user launches the life plan simulation app.

[0589] Specific actions: Open the simulation app on your smartphone or PC and access the app's login screen.

[0590] Input: None

[0591] Output: Login screen displayed

[0592] Step 2:

[0593] The user enters initial data such as age, income, family composition, and desired life events.

[0594] Specific actions: Enter the required information into the app's input form (e.g., "30 years old, annual income of 5 million yen, family composition of one spouse and two children, desired life event is to purchase a home at age 35") and press the submit button.

[0595] Input: Initial data (age, income, family structure, desired life events)

[0596] Output: Submit button click event

[0597] Step 3:

[0598] The user terminal receives the data entered by the user and transmits it to the server.

[0599] Specific operation: Save input data locally and send it to the server using an API.

[0600] Input: User initial data

[0601] Output: Initial data sent to the server

[0602] Analysis of initial data and generation of life plans

[0603] Step 4:

[0604] The server receives the data from the user terminal.

[0605] Specific operation: The server receives data sent from the user device via API.

[0606] Input: Initial data from the user's terminal

[0607] Output: Initial data received by the server

[0608] Step 5:

[0609] The server transfers the received data to the dialogue management computer.

[0610] Specific operation: The server analyzes the received data, converts it into an appropriate format, and transfers it to the dialogue management computer.

[0611] Input: Initial data received

[0612] Output: Data transferred to the dialogue management computer

[0613] Step 6:

[0614] The dialogue management computer analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[0615] What it does: Parses the data and sends the request in the appropriate format to the AI ​​life plan simulation engine.

[0616] Input: Received data

[0617] Output: Request data

[0618] Step 7:

[0619] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[0620] What it does: Generates an initial life plan based on input data and known algorithms.

[0621] Input: Request data

[0622] Output: Initial life plan

[0623] Step 8:

[0624] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[0625] Specific operation: The generated life plan is sent to the user's device and the results are displayed on the app screen.

[0626] Input: Initial Life Plan

[0627] Output: Initial life plan sent to user device

[0628] Enter feedback and update your plan

[0629] Step 9:

[0630] The user enters feedback on the plan (requests for corrections, additions, etc.).

[0631] Specific actions: Enter desired changes or additional requests in the feedback field and submit.

[0632] Input: Feedback data

[0633] Output: Submit button click event

[0634] Step 10:

[0635] The user terminal receives the feedback data and causes the emotion engine to analyze the emotion data.

[0636] Specific behavior: Passes feedback data to the emotion engine and analyzes the user's emotions.

[0637] Input: Feedback data

[0638] Output: Emotion data

[0639] Step 11:

[0640] The terminal transmits the feedback together with the emotion data to the server.

[0641] Specific operation: Sends the analyzed data to the server.

[0642] Input: Feedback data, emotion data

[0643] Output: Feedback and emotion data sent to the server

[0644] Step 12:

[0645] The server transfers the feedback and emotion data to the dialogue management computer.

[0646] Specific operation: The server sends feedback and emotion data to the dialogue management computer.

[0647] Input: Feedback data, emotion data

[0648] Output: Feedback and emotion data transmitted to the dialogue management computer

[0649] Step 13:

[0650] The dialogue management computer analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[0651] Specific operation: Analyzes the feedback content and emotional data, and sends an update request to the AI ​​life plan simulation engine.

[0652] Input: Feedback data, emotion data

[0653] Output: Update request

[0654] Step 14:

[0655] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[0656] What it does: Update your life plan with new data.

[0657] Input: Update request

[0658] Output: Updated Life Plan

[0659] Step 15:

[0660] The server transmits the updated life plan to the user terminal and displays it again.

[0661] Specific operation: The updated plan is sent to the user's device and displayed again on the app screen.

[0662] Enter: Updated Life Plan

[0663] Output: Updated life plan sent to user device

[0664] Requesting and Providing Expert Advice

[0665] Step 16:

[0666] A user enters a request for expert advice in a particular area (e.g., mortgage, insurance, etc.).

[0667] What you do: Select the area of ​​advice you need, enter details, and submit your request.

[0668] Input: Advice request

[0669] Output: Submit button click event

[0670] Step 17:

[0671] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[0672] Specific operation: Receives request data and requests the emotion engine to analyze it.

[0673] Input: Advice request

[0674] Output: Emotion data

[0675] Step 18:

[0676] The terminal transmits the emotion data together with the request to the server.

[0677] Specific behavior: Sends request and emotion data to the server.

[0678] Input: Advice request, emotion data

[0679] Output: Advice request and emotion data sent to the server

[0680] Step 19:

[0681] The server sends the request and the emotion data to the expert advice generation engine.

[0682] Specific operation: The server sends the request content and emotion data to the expert advice generation engine.

[0683] Input: Advice request, emotion data

[0684] Output: Expert Advice Request

[0685] Step 20:

[0686] An expert advice generation engine generates advice based on the emotion data and sends it back to the server.

[0687] Specific behavior: Generate optimal advice taking into account emotional data.

[0688] Input: Advice request, emotion data

[0689] Output: Expert advice

[0690] Step 21:

[0691] The server transmits the generated advice to the user terminal and displays it to the user.

[0692] Specific operation: The generated advice is sent to the user's device and displayed on the app screen.

[0693] Enter: Expert Advice

[0694] Output: Expert advice sent to the user's device

[0695] Generating future scenarios

[0696] Step 22:

[0697] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[0698] Specific Action: Enter details of the future scenario and submit a simulation request.

[0699] Input: Simulation request

[0700] Output: Submit button click event

[0701] Step 23:

[0702] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[0703] Specific operation: Receives request data and requests the emotion engine to analyze it.

[0704] Input: Simulation request

[0705] Output: Emotion data

[0706] Step 24:

[0707] The terminal transmits the emotion data together with the request to the server.

[0708] Specific behavior: Sends request and emotion data to the server.

[0709] Input: Simulation request, emotion data

[0710] Output: Simulation request and emotion data sent to the server

[0711] Step 25:

[0712] The server sends the request and emotion data to the dialogue management computer.

[0713] Specific operation: The server sends the request content and emotion data to the dialogue management computer.

[0714] Input: Simulation request, emotion data

[0715] Output: Request and emotion data transmitted to the dialogue management computer

[0716] Step 26:

[0717] The dialogue management computer sends requests and emotional data to the AI ​​life plan simulation engine.

[0718] Specific operation: Sends a request and emotion data and requests scenario generation.

[0719] Input: Request, emotion data

[0720] Output: Simulation request

[0721] Step 27:

[0722] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[0723] Specific operation: Generate multiple future scenarios based on various data and identify scenarios that are advantageous or require caution.

[0724] Input: Simulation request

[0725] Output: Future scenario

[0726] Step 28:

[0727] The server transmits the generated scenario to the user terminal and displays it to the user.

[0728] Specific operation: The generated scenario is sent to the user's device and displayed on the app screen.

[0729] Input: Future scenario

[0730] Output: Future scenario sent to the user device

[0731] (Application example 2)

[0732] 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."

[0733] Currently, many users struggle with managing income and expenses and simulating future scenarios when creating their future life plans. In particular, the lack of professional advice and the ability to adjust plans to accommodate fluctuations in income and expenses makes it difficult to create accurate and effective life plans. Furthermore, the lack of consideration for user emotions in planning makes it difficult to provide plans that are satisfactory. A system that solves these problems is needed.

[0734] 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 a user terminal to input initial data related to a life plan and transmit the data to the server; means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine; means for the AI ​​life plan simulation engine to generate an initial life plan simulation and return it to the server; means for the server to transmit the generated initial life plan to the user terminal; means for the user to input feedback on the life plan and transmit the feedback to the server; means for the server to transmit the received feedback to the AI ​​life plan simulation engine to update the plan; means for the user terminal to input data for managing daily income and expenses and transmit the data to the server; means for the server to analyze the received income and expense data and provide the user with saving tips and investment suggestions; and means for the emotion engine to analyze the user's emotion data and transmit the data to the server to reflect the results. This allows the user to update their life plan as needed to reflect fluctuations in income and expenses and receive expert advice. Furthermore, users can receive personalized feedback that takes emotional data into account, which is expected to help create a more satisfying life plan.

[0735] A "user terminal" is a device that allows a user to input data related to life plans and income / expense management and transmit it to the server.

[0736] The "server" is a central management system that analyzes data received from users and executes processing in cooperation with other engines, such as the AI ​​life plan simulation engine.

[0737] The "AI Life Plan Simulation Engine" is an artificial intelligence module that analyzes the initial data and feedback provided by users to generate and update life plans.

[0738] "Feedback" is information such as desired modifications or additions that the user inputs to the generated life plan.

[0739] The "emotion engine" is a software module that recognizes emotions from the user's facial expressions, voice, and text input, analyzes the emotional data, and reflects it in simulation results and feedback.

[0740] An "expert advice generation engine" is an artificial intelligence module that generates appropriate advice for users based on specialized knowledge in a particular field.

[0741] "Income" refers to financial resources such as monetary income or salary that a user receives within a certain period of time.

[0742] "Expenses" refers to all payments made by a user within a certain period of time, including living expenses and money spent on hobbies.

[0743] "Savings Tips" are suggestions and advice to help users reduce wasteful spending and manage their money efficiently.

[0744] An "investment proposal" is a proposal for specific investment destinations and methods that will enable users to effectively manage their funds and earn profits.

[0745] A "prompt" is text data input to a generative AI model, and is an instruction that enables the model to generate appropriate answers or advice.

[0746] The present invention relates to a system that allows users to independently create and manage their own life plans. This system is composed of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine. Specific embodiments for implementing the present invention are described below.

[0747] System Overview

[0748] 1. User Device:

[0749] Through the interface, users input initial data about their life plan (age, income, family composition, desired life events, etc.).

[0750] You can also enter data to manage your daily income and expenses.

[0751] The user terminal transmits this data to the server.

[0752] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[0753] 2. Server:

[0754] The server is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management server and various engines.

[0755] Initial data, feedback, and emotional data are transferred to the dialogue management server, and the analysis results are sent to the user's terminal.

[0756] It analyzes income and expenditure data and provides users with savings tips and investment suggestions.

[0757] 3. Dialogue Management Server:

[0758] It is an interface server that receives and analyzes data from users and links with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[0759] 4. AI Life Plan Simulation Engine:

[0760] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[0761] Generate an initial life plan and update the plan based on daily income and expenditure.

[0762] It is built using TensorFlow.

[0763] 5. Expert advice generation engine:

[0764] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[0765] Using OpenAI GPT-3, it generates relevant expert advice based on user requests.

[0766] 6. Emotion Engine:

[0767] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to the dialogue management server.

[0768] It is built using the Microsoft Azure Emotion Recognition API.

[0769] Optimize the results of life plan simulations and expert advice based on emotional data.

[0770] Specific example explanation

[0771] Example 1: Creating a life plan for buying a home

[0772] When a user is planning to purchase a home, they use the system in the following steps: The user launches the life plan simulation app and enters information such as age, income, family composition, budget, loan amount, and desired area. The user's device sends the entered information to the server, which then forwards it to the dialogue management server. The dialogue management server sends the received data to the AI ​​life plan simulation engine, which generates an initial life plan. The user then enters feedback on the plan and sends emotional data along with the feedback to the server. The server analyzes this data and dynamically updates the plan.

[0773] Example 2: Educational Expenses Scenario Generation

[0774] This is the procedure when a user wants to simulate a scenario regarding their child's education expenses. The user inputs a request and the request is sent to the server on the user's device. The server forwards the request to the dialogue management server, which then sends it to the AI ​​life plan simulation engine. The engine generates scenarios based on changes in education expenses and the school to which the user will advance, and the user can then select the optimal education plan based on these scenarios.

[0775] Prompt Sentence Examples

[0776] For example, if you are 35 years old, have a family of four, earn 7 million yen a year, and your desired life events are buying a house and educating your children, the user would use the following prompt:

[0777] User data: {"age": 35, "income": 7000000, "family": {"members": 4}, "events": ["buy_house", "child_education"]}. Provide financial advice.

[0778] By inputting this prompt into a generative AI model, expert advice can be generated, providing the user with an appropriate life plan.

[0779] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0780] Step 1:

[0781] The user's terminal inputs initial data related to their life plan and sends that data to the server. Specifically, the user enters data about their age, income, family structure, and desired life events (e.g., buying a home, children's education, etc.) into an input form. Once this initial data is sent, it is received by the server.

[0782] Step 2:

[0783] The server analyzes the received initial data and transfers it to the dialogue management server. The server converts the initial data into JSON format and sends it to the dialogue management server. This data specifically includes the user's age, income, desired events, etc.

[0784] Step 3:

[0785] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine. The dialogue management server formats the data appropriately and constructs and sends a request to the AI ​​life plan simulation engine.

[0786] Step 4:

[0787] The AI ​​life plan simulation engine generates an initial life plan and sends it back to the server. The AI ​​life plan simulation engine uses TensorFlow to analyze and generate an initial life plan based on the user's data. The results are sent back to the server.

[0788] Step 5:

[0789] The server transmits the generated initial life plan to the user terminal. The server receives the initial life plan returned from the dialogue management server and transmits it to the user terminal. The user terminal displays the received life plan on its screen.

[0790] Step 6:

[0791] The user inputs feedback about the life plan and sends the feedback to the server. The user checks the life plan and inputs any necessary corrections or additions as feedback. This feedback is sent from the user terminal to the server.

[0792] Step 7:

[0793] The server sends the received feedback to the AI ​​life plan simulation engine to update the plan. The server analyzes the feedback data and sends it to the AI ​​life plan simulation engine. The engine updates the plan based on it and sends the result back to the server.

[0794] Step 8:

[0795] The user's terminal inputs data for managing daily income and expenses and transmits the data to the server. The user inputs details of daily income and expenses into the application, and the data is transmitted to the server.

[0796] Step 9:

[0797] The server analyzes the received income and expenditure data and provides the user with savings tips and investment suggestions. Based on this data, the server uses a generative AI model such as OpenAI GPT-3 to generate prompts and provide appropriate savings and investment advice. This advice is then sent to the user's device.

[0798] Step 10:

[0799] The emotion engine analyzes the user's emotional data and sends that data to the server, which reflects the results. The emotion engine recognizes emotions from the user's facial expressions, voice, text input, etc. and sends that emotional data to the server. The server adjusts the life plan and proposal content based on this data.

[0800] This process allows users to create and manage their life plans in real time and with a personalized interface. For example, if a 35-year-old user with an annual income of 7 million yen plans to buy a home, specific advice and updates to the plan will be automatically provided based on that plan. The generative AI model also provides advice using prompts such as:

[0801] User data: {"age": 35, "income": 7000000, "family": {"members": 4}, "events": ["buy_house", "child_education"]}. Provide financial advice.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] [Second embodiment]

[0806] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0807] 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.

[0808] 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).

[0809] 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.

[0810] 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.

[0811] 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).

[0812] 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. 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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."

[0818] This invention relates to a system that enables users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[0819] System Overview

[0820] 1. User terminal: The user inputs initial data about their life plan (age, income, family structure, desired life events, etc.) through an interface. It is also an input device for providing feedback on the generated life plan and requesting specific advice.

[0821] 2. Server: A central system that analyzes data received from user devices and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user devices.

[0822] 3. Dialogue Management Server: This is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue.

[0823] 4. AI Life Plan Simulation Engine: This is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[0824] 5. Expert Advice Generation Engine: An AI module with expertise in specific fields such as finance, insurance, real estate, etc. It receives requests from users and generates relevant advice.

[0825] Program processing

[0826] Entering and submitting initial data

[0827] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[0828] The terminal receives the data entered by the user and transmits it to the server.

[0829] Analysis of initial data and generation of initial life plan

[0830] The server analyzes the received user initial data and transfers it to the dialogue management server.

[0831] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[0832] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[0833] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[0834] Enter feedback and update your plan

[0835] The user inputs feedback (e.g., requests for corrections or additions) on the presented life plan.

[0836] The terminal receives the user's feedback and transmits it to the server.

[0837] The server forwards the feedback to the interaction management server.

[0838] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[0839] The AI ​​life plan simulation engine updates the plan based on the new feedback and sends it back to the server.

[0840] The server transmits the updated life plan to the user terminal and displays it again.

[0841] Providing expert advice

[0842] A user enters a request for advice in a particular area (eg, mortgage, insurance).

[0843] The terminal receives the request and sends it to the server.

[0844] The server sends the request to the expert advice generation engine.

[0845] The expert advice generation engine generates expert advice based on the user's request and sends it back to the server.

[0846] The server transmits the generated advice to the user terminal and displays it to the user.

[0847] Generating future scenarios

[0848] A user inputs a request to simulate a future scenario.

[0849] The terminal receives the request and sends it to the server.

[0850] The server sends the request to the AI ​​life plan simulation engine.

[0851] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable for the user and those that require caution.

[0852] The server transmits the generated scenario to the user terminal and displays it to the user.

[0853] Specific examples

[0854] Example 1: Creating a life plan for buying a home

[0855] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[0856] The terminal transmits the input information to the server.

[0857] The server forwards the received information to the dialogue management server.

[0858] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[0859] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[0860] The server transmits the generated plan to the user terminal.

[0861] The user enters feedback on the plan and submits it again.

[0862] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[0863] Example 2: Educational Expenses Scenario Generation

[0864] A user enters a request to simulate a scenario regarding their child's education expenses.

[0865] The terminal sends a request to the server.

[0866] The server sends the request to the AI ​​life plan simulation engine.

[0867] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[0868] The server transmits the generated scenario to the user terminal.

[0869] The user selects the most suitable training plan based on multiple scenarios.

[0870] This allows users to independently create specific and reliable life plans, reduce anxiety about the future, and advance systematic life planning.

[0871] The processing flow will be explained below.

[0872] Step 1:

[0873] The user launches the life plan simulation app and enters personal information (age, income, family composition, desired life events, etc.).

[0874] Step 2:

[0875] The terminal receives the data entered by the user and transmits the data to the server.

[0876] Step 3:

[0877] The server transfers the received data to the dialogue management server.

[0878] Step 4:

[0879] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[0880] Step 5:

[0881] The AI ​​life plan simulation engine generates an initial life plan simulation based on the user's initial data.

[0882] Step 6:

[0883] The server receives the generated initial life plan and transmits it to the user terminal.

[0884] Step 7:

[0885] The user checks the life plan they received and enters feedback, corrections, and additional requests.

[0886] Step 8:

[0887] The terminal receives the user's feedback and transmits the feedback to the server.

[0888] Step 9:

[0889] The server forwards the received feedback to the interaction management server.

[0890] Step 10:

[0891] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[0892] Step 11:

[0893] The AI ​​life plan simulation engine updates the plan to reflect the new feedback and sends it back to the server.

[0894] Step 12:

[0895] The server transmits the updated life plan to the user terminal.

[0896] Step 13:

[0897] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[0898] Step 14:

[0899] The terminal receives the request and sends it to the server.

[0900] Step 15:

[0901] The server forwards the received request to the expert advice generation engine.

[0902] Step 16:

[0903] The expert advice generation engine generates expert advice based on the user's request and returns the results to the server.

[0904] Step 17:

[0905] The server transmits the generated advice to the user terminal.

[0906] Step 18:

[0907] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[0908] Step 19:

[0909] The terminal receives the simulation request and sends it to the server.

[0910] Step 20:

[0911] The server sends the request to the AI ​​life plan simulation engine.

[0912] Step 21:

[0913] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[0914] Step 22:

[0915] The server transmits the generated scenario to the user terminal.

[0916] Step 23:

[0917] The user reviews the provided scenarios, selects the most suitable life plan, and enters that selection into the system.

[0918] Step 24:

[0919] The terminal receives the user's final selection and transmits it to the server.

[0920] Step 25:

[0921] The server sends the final selection to the dialogue management server, requesting the generation of a final life plan.

[0922] Step 26:

[0923] The AI ​​life plan simulation engine generates the final life plan and sends it back to the server.

[0924] Step 27:

[0925] The server transmits the final life plan to the user terminal and displays it to the user.

[0926] Through these steps, we have created a system that allows users to dynamically and interactively create and update their life plans and receive expert advice to form the optimal life plan.

[0927] Example 1

[0928] 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."

[0929] Conventional life plan creation systems have the problem that it is difficult for users to obtain appropriate advice when they do not have specialized knowledge or when they have limited access to advice, and they are unable to fully meet the needs of users. Another problem is that simulating and updating a life plan is time-consuming and tedious. The purpose of this invention is to solve these problems and enable users to effectively create and manage their life plans on their own.

[0930] 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.

[0931] In this invention, the server includes: means for a user terminal to input initial data regarding a life plan and transmit the data to the server; means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine via the dialogue management server; means for the AI ​​life plan simulation engine to generate an initial life plan simulation and transmit it back to the server; means for the server to transmit the generated initial life plan to the user terminal; means for the user to input feedback regarding the life plan and transmit the feedback to the server; and means for transmitting the feedback received by the server to the AI ​​life plan simulation engine via the dialogue management server to update the plan. This enables the AI ​​to dynamically generate and update a life plan and obtain expert advice based on the initial data and feedback input by the user.

[0932] A "user terminal" is a device through which a user inputs data related to their life plan and communicates with the server.

[0933] The "server" is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management server and various engines.

[0934] The "dialogue management server" is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine.

[0935] The "AI Life Plan Simulation Engine" is an AI module that generates and updates life plan simulations based on the user's initial data and feedback.

[0936] An "expert advice generation engine" is an AI module that has expertise in a specific field and generates expert advice based on requests from users.

[0937] "Initial data" refers to basic information that a user inputs to create a life plan, and includes age, income, family structure, desired life events, and the like.

[0938] "Feedback" refers to opinions and requests, such as corrections and additions, provided by the user regarding the generated life plan.

[0939] A "request" is input data that a user inputs to the server, requesting specific advice or a simulation of a future scenario.

[0940] "Simulation" refers to the process of predicting and generating future life plans and multiple future scenarios carried out by an AI life plan simulation engine.

[0941] This invention relates to a system that allows users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[0942] System Overview

[0943] User terminal

[0944] The user terminal is a device where a user inputs initial data about their life plan and transmits that data to a server. The user terminal has an interface through which the user inputs initial data such as age, income, family composition, and desired life events through an application. The user terminal is also an input device for providing feedback on the generated life plan and requesting specific advice.

[0945] server

[0946] The server is a central system that analyzes data received from user terminals and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user terminal. The server also collaborates with the expert advice generation engine to provide expert advice.

[0947] Dialogue Management Server

[0948] The dialogue management server is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue and sends the initial data and feedback received from users to each engine.

[0949] AI life plan simulation engine

[0950] The AI ​​life plan simulation engine is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[0951] Expert Advice Generation Engine

[0952] An expert advice generation engine is an AI module with specialized knowledge in a specific field, such as finance, insurance, or real estate, that receives requests from users and generates relevant advice.

[0953] Specific examples

[0954] Example 1: Creating a life plan for buying a home

[0955] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[0956] The terminal transmits the input information to the server.

[0957] The server forwards the received information to the dialogue management server.

[0958] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[0959] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[0960] The server transmits the generated plan to the user terminal.

[0961] The user enters feedback on the plan and submits it again.

[0962] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[0963] Example 2: Educational Expenses Scenario Generation

[0964] A user enters a request to simulate a scenario regarding their child's education expenses.

[0965] The terminal sends a request to the server.

[0966] The server sends the request to the AI ​​life plan simulation engine.

[0967] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[0968] The server transmits the generated scenario to the user terminal.

[0969] The user selects the most suitable training plan based on multiple scenarios.

[0970] Prompt Sentence Examples

[0971] 1. "Generate a life plan based on your home buying budget and desired area."

[0972] 2. "Simulate several scenarios for your child's education expenses."

[0973] This system allows users to independently create specific and reliable life plans, reducing anxiety about the future and enabling them to plan their lives in a planned manner.

[0974] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0975] Step 1: Enter initial data

[0976] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[0977] Input: Any initial data that a user enters into an app form.

[0978] Output: The input data is compiled as JSON format data.

[0979] What happens: Data is collected when a user fills out a form on the app and clicks the "Submit" button.

[0980] Step 2: Sending initial data

[0981] The terminal receives the initial data entered by the user and transmits it to the server.

[0982] Input: Initial data in JSON format.

[0983] Output: The initial data sent to the server.

[0984] Specific operation: The terminal's data transmission module sends the initial data to the server using an HTTPS request.

[0985] Step 3: Analyze the initial data

[0986] The server analyzes the received initial data and forwards it to the dialogue management server.

[0987] Input: The initial data received by the server in JSON format.

[0988] Output: The parsed data is transferred to the dialogue management server.

[0989] Specific operation: The server analyzes the initial data using a data analysis algorithm, and then reformats and transmits the analysis results to the dialogue management server.

[0990] Step 4: Submitting a simulation request

[0991] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[0992] Input: Analysis results based on initial data.

[0993] Output: The request sent to the AI ​​life plan simulation engine.

[0994] Specific operation: The dialogue management server formats the analysis results into a format that the AI ​​engine can understand and submits a request via API.

[0995] Step 5: Generate an initial life plan

[0996] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[0997] Input: The request data received from the server.

[0998] Output: Generated initial life plan.

[0999] How it works: The AI ​​engine uses past data and statistical models to generate a life plan that best suits the user's initial data.

[1000] Step 6: Displaying your initial life plan

[1001] The server transmits the generated initial life plan to the user terminal.

[1002] Input: Initial life plan returned from the AI ​​life plan simulation engine.

[1003] Output: The initial life plan sent to the user's device.

[1004] Specific operation: The server re-encodes the life plan data into JSON format and sends it to the user's device as an HTTPS response.

[1005] Step 7: Provide feedback

[1006] The user inputs feedback (e.g., requests for corrections or additions) on the presented life plan.

[1007] Input: Feedback based on the life plan provided.

[1008] Output: The input feedback data.

[1009] Specific behavior: A user fills in the required information in the app's feedback form and clicks the "Submit Feedback" button.

[1010] Step 8: Submit your feedback

[1011] The terminal receives the user's feedback and transmits it to the server.

[1012] Input: User feedback data.

[1013] Output: Feedback data sent to the server.

[1014] Specific operation: The device obtains the feedback data and issues an HTTPS request to the server.

[1015] Step 9: Analyze feedback

[1016] The server forwards the feedback to the interaction management server.

[1017] Input: The feedback data received by the server.

[1018] Output: Feedback data transmitted to the dialogue management server.

[1019] Specific operation: The server checks the received feedback data and notifies the dialogue management server.

[1020] Step 10: Submit a plan renewal request

[1021] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[1022] Input: User feedback data.

[1023] Output: Update request to the AI ​​life plan simulation engine.

[1024] Specific operation: Based on the feedback received, the dialogue management server issues an API request to send an update instruction.

[1025] Step 11: Update your plan

[1026] The AI ​​life plan simulation engine updates the plan based on the new feedback and sends it back to the server.

[1027] Input: The update request received from the server.

[1028] Output: Updated life plan.

[1029] What it does: The AI ​​engine generates an updated simulation, taking into account new data inputs.

[1030] Step 12: View the updated plan

[1031] The server transmits the updated life plan to the user terminal and displays it again.

[1032] Input: Updated life plan returned from the AI ​​life plan simulation engine.

[1033] Output: The updated life plan sent to the user device.

[1034] Specific operation: The server notifies the user device of the received update plan data and sends it again as display data.

[1035] Step 13: Fill out your advice request

[1036] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[1037] Input: The content of your advice request.

[1038] Output: The input advice request.

[1039] What happens: A user fills out the "Advice Request" form in the app and clicks the "Submit" button.

[1040] Step 14: Submitting the Request

[1041] The terminal receives the request and sends it to the server.

[1042] Input: User advice request data.

[1043] Output: The advice request data sent to the server.

[1044] Specific operation: The device obtains the request data and issues an HTTPS request to the server.

[1045] Step 15: Submitting an Advice Generation Request

[1046] The server sends the request to the expert advice generation engine via the dialogue management server.

[1047] Input: User advice request data.

[1048] Output: A request to the Expert Advice generation engine.

[1049] What happens: The server formats the request data appropriately and makes an API call to the Expert Advice generation engine.

[1050] Step 16: Generating Advice

[1051] The expert advice generation engine generates expert advice based on the user's request and sends it back to the server.

[1052] Input: The request data received from the server.

[1053] Output: The generated advice.

[1054] Specific behavior: The engine references relational databases and knowledge bases to generate specific advice tailored to the user's situation.

[1055] Step 17: Viewing Advice

[1056] The server transmits the generated advice to the user terminal and displays it to the user.

[1057] Input: Advice returned from the Expert Advice generation engine.

[1058] Output: Advice sent to the user's terminal.

[1059] Specific operation: The server transfers the received advice data to the user's device and displays it within the app.

[1060] Step 18: Entering Scenario Requests

[1061] A user inputs a request to simulate a future scenario.

[1062] Input: The contents of the scenario request.

[1063] Output: The input scenario request.

[1064] Specific behavior: The user fills out the app's "Scenario Simulation" form and clicks the "Submit" button.

[1065] Step 19: Submitting the Request

[1066] The terminal receives the request and sends it to the server.

[1067] Input: User's scenario request data.

[1068] Output: The scenario request data sent to the server.

[1069] Specific operation: The device obtains the request data and issues an HTTPS request to the server.

[1070] Step 20: Submitting a Simulation Request

[1071] The server sends the request to the AI ​​life plan simulation engine via the dialogue management server.

[1072] Input: User's scenario request data.

[1073] Output: A request to the AI ​​life plan simulation engine.

[1074] Specific operation: The server formats the request data appropriately and makes an API call to the AI ​​engine.

[1075] Step 21: Generate scenarios

[1076] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable for the user and those that require caution.

[1077] Input: Scenario request data received from the server.

[1078] Output: Generated future scenarios.

[1079] How it works: The AI ​​engine uses statistical models and predictive algorithms to simulate different future scenarios and assess the benefits and risks of each.

[1080] Step 22: Viewing the scenario

[1081] The server transmits the generated scenario to the user terminal and displays it to the user.

[1082] Input: Scenario returned from the AI ​​life plan simulation engine.

[1083] Output: The scenario sent to the user's device.

[1084] Specific operation: The server transfers the received scenario data to the user's device and displays it within the app.

[1085] (Application example 1)

[1086] 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."

[1087] In modern society, it is extremely important for individuals to effectively manage their own life plans and financial plans. However, it is difficult for ordinary users without specialized knowledge to do this on their own, as they are required to understand complex information and analyze vast amounts of data. To solve this problem, there is a need for a system that allows users to easily create and manage their life plans and receive professional financial advice.

[1088] 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.

[1089] In this invention, the server includes means for a user terminal to input initial data regarding a life plan and transmit the data to the server, means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine, means for the AI ​​life plan simulation engine to generate an initial life plan simulation and transmit it back to the server, means for the server to transmit the generated initial life plan to the user terminal, means for the user to input feedback regarding the life plan and transmit the feedback to the server, means for the server to transmit the received feedback to the AI ​​life plan simulation engine to update the plan, and means for the user terminal to input financial data and transmit the data to the AI ​​life plan simulation engine. The system includes a means for transmitting the financial plan to a cloud server, a means for the cloud server to analyze the received data and transmit it to an AI life plan simulation engine, a means for the AI ​​life plan simulation engine to generate a financial plan and return it to the cloud server, a means for the cloud server to transmit the generated financial plan to a user terminal, a means for the user terminal to request advice on a specific field and transmit the request to the server, a means for the server to transmit the received request to an expert advice generation engine, a means for the expert advice generation engine to generate expert advice based on the user request and transmit it back to the server, and a means for the server to transmit the generated advice to the user terminal. This allows users to create their own life plans and easily receive expert advice. It also allows users to understand their own financial situation and effectively manage their future plans.

[1090] A "user terminal" is a device that allows a user to input, send, and receive life plans and financial data.

[1091] A "server" is a central control device that analyzes data received from user terminals and coordinates with other engines and servers.

[1092] The "AI Life Plan Simulation Engine" is an artificial intelligence module that generates and updates life plans and financial plans based on the user's initial data and feedback.

[1093] A "cloud server" is a remote server on the Internet for receiving data from a user terminal and transmitting the analyzed and generated plan to the user terminal.

[1094] An "expert advice generation engine" is an artificial intelligence module that generates expert advice on a specific subject based on a user's request.

[1095] A "life plan" is a plan for a user's life planning, and is an overall strategy that takes into consideration age, income, family structure, desired life events, and the like.

[1096] "Feedback" refers to inputting corrections or additional requests for plans or proposals provided by the user.

[1097] "Specific fields" refer to areas requiring specialized knowledge, such as finance, insurance, real estate, and education expenses.

[1098] "Financial Data" is information related to a user's personal financial situation, such as their income, expenses, and savings goals.

[1099] A "financial plan" is a plan for short-term and long-term income and expenditure management and asset formation that is generated based on the user's financial data.

[1100] A "future financial scenario" is a simulation of future income and expenditures and asset status that is generated based on the user's financial data.

[1101] A "request" is a request submitted by a user for a particular piece of advice or simulation.

[1102] "Analysis" is the process of processing received data and extracting meaningful information.

[1103] A "system" is a structure in which multiple hardware and software components work together to provide a specific function.

[1104] The present invention is a system that allows users to conveniently create and manage their own life plans and financial plans. This system consists of a user terminal, a cloud server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[1105] System Overview

[1106] 1. User Device:

[1107] The user terminal is a device where users input, send, and receive their life plan and financial data. Users input initial data such as age, income, family composition, and desired life events through a smartphone app and send the data to the cloud server.

[1108] 2. Cloud Server:

[1109] The cloud server is a central control unit that analyzes data received from user devices and coordinates with other engines and servers. The cloud server transmits the received data to the dialogue management server and sends requests for analysis and calculation.

[1110] 3. Dialogue Management Server:

[1111] The dialogue management server is responsible for linking the AI ​​life plan simulation engine and the expert advice generation engine based on user input data, and plays a role in appropriately distributing user requests and sending them to each engine.

[1112] 4. AI Life Plan Simulation Engine:

[1113] The AI ​​Life Plan Simulation Engine is an artificial intelligence module that generates and updates initial life plans and financial plans based on the user's initial data and feedback. The engine is implemented using machine learning frameworks such as TensorFlow or PyTorch.

[1114] 5. Expert advice generation engine:

[1115] An expert advice generation engine is an AI module that generates expert advice on a specific subject based on user requests, using natural language processing models such as GPT-3 or BERT.

[1116] Specific examples

[1117] Example 1: Creating a life plan for buying a home

[1118] The user enters information such as their home purchase budget, loan amount, and desired area through a smartphone app. The smartphone app sends the entered information to a cloud server, which then sends the data to the AI ​​life plan simulation engine via a dialogue management server. The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the cloud server. The cloud server then sends the generated plan to the smartphone app and displays it to the user. The user then enters feedback on this plan and submits it again. This allows the plan to be dynamically updated based on the feedback, and the final plan is finalized.

[1119] Prompt Sentence Examples

[1120] "The user is 35 years old, has an annual income of 6 million yen, and consists of a couple and two children. If they plan to purchase a home within the next five years, please provide specific advice on what type of loan and financial management they should take, and which area would be suitable."

[1121] This system allows users to create their own life plans and easily receive professional advice, while also helping users understand their own financial situation and effectively manage their future plans.

[1122] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1123] Step 1:

[1124] The user launches the smartphone app and enters initial data such as age, income, family composition, and desired life events. The entered data is temporarily stored in the smartphone app's local storage. The user then presses the "Send" button, which sends the data to the cloud server.

[1125] Input: Age, income, family structure, desired life events

[1126] Output: Initial data sent to the cloud server

[1127] Step 2:

[1128] The cloud server analyzes the initial data received from the user terminal and sends it to the dialogue management server, which converts the received data into a format required to send it as a request to the AI ​​life plan simulation engine.

[1129] Input: Initial data from the user's terminal

[1130] Output: Data in request format to the dialogue management server

[1131] Step 3:

[1132] The dialogue management server sends the received initial data to the AI ​​life plan simulation engine, which performs calculations to generate an initial life plan based on the data. Specifically, an algorithm is executed to generate an optimal financial plan based on the user's age, income, and family structure.

[1133] Input: Initial data from the dialogue management server

[1134] Output: Generated initial life plan

[1135] Step 4:

[1136] The AI ​​life plan simulation engine returns the generated initial life plan to the cloud server, which then transmits the generated life plan to the user's device.

[1137] Input: Initial life plan

[1138] Output: Data sent to the user terminal

[1139] Step 5:

[1140] The user checks the initial life plan presented on the smartphone app and enters feedback as necessary. Feedback can include requests for revisions or additions to the plan. When the user presses the "Send Feedback" button, the feedback data is sent to the cloud server.

[1141] Input: User feedback

[1142] Output: Feedback data to the cloud server

[1143] Step 6:

[1144] The cloud server analyzes the feedback received from the user and sends it to the AI ​​life plan simulation engine via the dialogue management server. The AI ​​life plan simulation engine generates a new life plan that reflects the feedback.

[1145] Input: Feedback data

[1146] Output: Updated Life Plan

[1147] Step 7:

[1148] The updated life plan is sent to the user's device via the cloud server. The user reviews the life plan again and provides additional feedback if necessary. This process is repeated until a plan that satisfies the user is generated.

[1149] Input: Updated Life Plan

[1150] Output: Data sent to the user terminal

[1151] Step 8:

[1152] When a user requests advice on a specific topic, they input the request through a smartphone app and send it to a cloud server. For example, they can ask for advice on investment strategies or how to choose a loan.

[1153] Input: Request for advice on a specific subject

[1154] Output: Request data to the cloud server

[1155] Step 9:

[1156] The cloud server sends the received request to an expert advice generation engine, which generates expert advice based on the request and sends it back to the cloud server.

[1157] Input: Request for advice

[1158] Output: Generated expert advice

[1159] Step 10:

[1160] The cloud server sends the generated expert advice to the user's device, where the user can check the expert advice on the smartphone app and decide on the next action to take if necessary.

[1161] Enter: Expert Advice

[1162] Output: Data sent to the user terminal

[1163] 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.

[1164] This invention relates to a system that enables users to independently create and manage their life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine.

[1165] System Overview

[1166] 1. User Device:

[1167] Through the interface, users input initial data about their life plan (age, income, family composition, desired life events, etc.).

[1168] The user terminal receives the user's input data and transmits it to the server.

[1169] An input device that allows a user to enter a request for feedback or specific advice.

[1170] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[1171] 2. Server:

[1172] It is a central system that analyzes data received from user terminals and manages collaboration with the dialogue management server and various engines.

[1173] The initial data, feedback, and emotion data are transferred to the dialogue management server, and the response is sent to the user terminal.

[1174] 3. Dialogue Management Server:

[1175] It is an interface server that receives and analyzes data from users and links with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[1176] 4. AI Life Plan Simulation Engine:

[1177] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[1178] It has the ability to verbalize and quantify users' vague anxieties and requests.

[1179] 5. Expert advice generation engine:

[1180] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[1181] It receives requests from users and generates relevant advice.

[1182] 6. Emotion Engine:

[1183] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to the dialogue management server.

[1184] Optimize the results of life plan simulations and expert advice based on emotional data.

[1185] Program processing

[1186] Enter and submit initial data:

[1187] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[1188] The user terminal receives the data entered by the user and transmits it to the server.

[1189] Analysis of initial data and generation of life plan:

[1190] The server transfers the received data to the dialogue management server.

[1191] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[1192] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[1193] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[1194] Leave feedback and update your plan:

[1195] The user enters feedback about the plan (e.g., correction requests, additional requests).

[1196] The user terminal receives the feedback data and causes the emotion engine to analyze the emotion data.

[1197] The device sends the feedback along with the emotion data to the server.

[1198] The server forwards the feedback and emotion data to the dialogue management server.

[1199] The dialogue management server analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[1200] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[1201] The server transmits the updated life plan to the user terminal and displays it again.

[1202] Requesting and Providing Expert Advice:

[1203] A user enters a request for expert advice in a particular area (e.g., mortgage, insurance).

[1204] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1205] The device sends the emotion data along with the request to the server.

[1206] The server sends the request and emotion data to the expert advice generation engine.

[1207] An expert advice generation engine generates advice based on the emotion data and returns it to the server.

[1208] The server transmits the generated advice to the user terminal and displays it to the user.

[1209] Generate future scenarios:

[1210] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[1211] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1212] The device sends the request and emotion data to the server.

[1213] The server sends the request and emotion data to the dialogue management server.

[1214] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[1215] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[1216] The server transmits the generated scenario to the user terminal and displays it to the user.

[1217] Specific examples

[1218] Example 1: Creating a life plan for buying a home

[1219] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[1220] The user terminal transmits the input information to the server.

[1221] The server forwards the received information to the dialogue management server.

[1222] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[1223] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[1224] The server transmits the generated plan to the user terminal.

[1225] The user provides feedback on the plan.

[1226] The user terminal causes the emotion engine to analyze the emotion data along with the feedback, and transmits it to the server.

[1227] From then on, the plan is dynamically updated based on user feedback and emotion data, and the final plan is finalized.

[1228] Example 2: Educational Expenses Scenario Generation

[1229] A user enters a request to simulate a scenario regarding their child's education expenses.

[1230] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1231] The device sends the request and emotion data to the server.

[1232] The server forwards the request to the interaction management server.

[1233] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[1234] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school chosen, and identifies the appropriate scenario for the user.

[1235] The server transmits the generated scenario to the user terminal.

[1236] The user selects the most suitable educational plan based on the provided scenario.

[1237] This allows users to independently create specific and reliable life plans, reducing future anxiety and promoting systematic life planning. Furthermore, the emotion engine takes the user's emotional state into account, enabling more personalized and appropriate planning.

[1238] The processing flow will be explained below.

[1239] Step 1:

[1240] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[1241] Step 2:

[1242] The terminal receives the data entered by the user and transmits the data to the server.

[1243] Step 3:

[1244] The emotion engine collects emotional data from the user's facial expressions, voice, and text input.

[1245] Step 4:

[1246] The terminal receives the emotion data and transmits it to the server together with the initial data.

[1247] Step 5:

[1248] The server transfers the received initial data and emotion data to the dialogue management server.

[1249] Step 6:

[1250] The dialogue management server analyzes the initial data and emotional data and sends a request to the AI ​​life plan simulation engine.

[1251] Step 7:

[1252] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and emotional data and sends it back to the server.

[1253] Step 8:

[1254] The server transmits the generated initial life plan to the user terminal.

[1255] Step 9:

[1256] The user reviews the initial life plan and enters feedback, corrections, and additional requests.

[1257] Step 10:

[1258] The terminal receives the user's feedback and runs the emotion engine again to update the emotion data.

[1259] Step 11:

[1260] The device sends the user's feedback and updated emotion data to the server.

[1261] Step 12:

[1262] The server transfers the received feedback and emotion data to the dialogue management server.

[1263] Step 13:

[1264] The dialogue management server analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[1265] Step 14:

[1266] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[1267] Step 15:

[1268] The server transmits the updated life plan to the user terminal.

[1269] Step 16:

[1270] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[1271] Step 17:

[1272] The terminal receives the request and causes the emotion engine to update the emotion data.

[1273] Step 18:

[1274] The device sends the request and emotion data to the server.

[1275] Step 19:

[1276] The server sends the request and emotion data to the expert advice generation engine.

[1277] Step 20:

[1278] An expert advice generation engine generates expert advice based on the emotion data and sends it back to the server.

[1279] Step 21:

[1280] The server transmits the generated advice to the user terminal.

[1281] Step 22:

[1282] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[1283] Step 23:

[1284] The terminal receives the simulation request and causes the emotion engine to update the emotion data.

[1285] Step 24:

[1286] The device sends the request and emotion data to the server.

[1287] Step 25:

[1288] The server transfers the request and the emotion data to the dialogue management server.

[1289] Step 26:

[1290] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[1291] Step 27:

[1292] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[1293] Step 28:

[1294] The server transmits the generated scenario to the user terminal.

[1295] Step 29:

[1296] The user reviews the provided scenarios, selects the most suitable life plan, and inputs the selection into the terminal.

[1297] Step 30:

[1298] The terminal receives the user's final selection and causes the emotion engine to update the emotion data.

[1299] Step 31:

[1300] The terminal transmits the user's final selection and emotion data to the server.

[1301] Step 32:

[1302] The server sends the final selection and emotion data to the dialogue management server, requesting it to generate a final life plan.

[1303] Step 33:

[1304] The AI ​​life plan simulation engine generates the final life plan and returns the results, taking into account emotional data, to the server.

[1305] Step 34:

[1306] The server transmits the final life plan to the user terminal and displays it to the user.

[1307] Through these steps, users can dynamically and interactively create and update their life plans, and receive expert advice to create the optimal life plan. Furthermore, the introduction of an emotion engine enables personalized planning that takes into account the user's emotional state.

[1308] Example 2

[1309] 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."

[1310] Conventional life plan creation systems make it difficult for users to independently create a balanced life plan, and it is difficult to achieve optimal planning when users lack specialized knowledge. Furthermore, there are insufficient means to consider users' emotions and feedback, making it difficult to provide personalized advice.

[1311] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1312] In this invention, the server includes a means for inputting initial data related to a life plan from a user terminal and transmitting the data to the server, a means for the server to analyze the received initial data and transfer it to a dialogue management computer, and a means for the dialogue management computer to analyze the received data and send a request to the AI ​​life plan simulation engine. This allows users to independently create a well-balanced life plan without specialized knowledge. Furthermore, a system is realized that takes into account the user's emotions and feedback and provides personalized advice.

[1313] A "user terminal" is an interface through which a user inputs data related to a life plan and transmits the data to a server.

[1314] A "server" is a central system that analyzes data received from user terminals and transfers the data to various engines and computers.

[1315] The "dialogue management computer" is a computer system that has the function of analyzing data received from the server and sending requests to the AI ​​life plan simulation engine.

[1316] The "AI Life Plan Simulation Engine" is an artificial intelligence module that generates and updates life plans based on the user's initial data and feedback.

[1317] An "expert advice generation engine" is an artificial intelligence module that generates advice based on user requests and emotional data, using specialized knowledge in a specific field.

[1318] "Emotion data" is data that indicates the emotional state of the user, obtained from facial expressions, voice, text input, and the like.

[1319] "Feedback" is data that indicates opinions and requests for revisions regarding the life plan and advice provided by the user.

[1320] A "future scenario" is a plan for simulating various situations in the future, such as fluctuations in income and changes in economic conditions.

[1321] "Initial data" refers to data such as age, income, family structure, and desired life events that the user inputs as basic information for creating a life plan.

[1322] This invention relates to a system that allows users to independently create and manage their own life plans. This system is composed of the following components: a user terminal, a server, a dialogue management computer, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine.

[1323] System configuration

[1324] 1. User Device:

[1325] Users use the life plan simulation app to input initial data such as age, income, family composition, and desired life events.

[1326] The user terminal receives and transmits input data to the server, and is also an input device for inputting user feedback and specific advice requests.

[1327] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[1328] 2. Server:

[1329] The server is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management computer and various engines.

[1330] The server transfers the initial data, feedback, and emotion data to the dialogue management computer, and sends the response to the user terminal.

[1331] 3. Dialogue Management Computer:

[1332] The dialogue management computer is an interface server that analyzes data from the server and works with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[1333] 4. AI Life Plan Simulation Engine:

[1334] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[1335] It has the ability to verbalize and quantify users' vague anxieties and requests.

[1336] 5. Expert advice generation engine:

[1337] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[1338] It receives requests from users and generates relevant advice.

[1339] 6. Emotion Engine:

[1340] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to a dialogue management computer.

[1341] Optimize the results of life plan simulations and expert advice based on emotional data.

[1342] Specific examples

[1343] Example 1: Creating a life plan for buying a home

[1344] The user enters the following information: "30 years old, annual income 5 million yen, family composition 1 spouse, 2 children, desired life event is to buy a home at age 35."

[1345] The user terminal transmits this data to the server.

[1346] The server transfers the user's input data to the dialogue management computer.

[1347] The dialogue management computer analyzes the data and sends requests to the AI ​​life plan simulation engine.

[1348] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[1349] The server transmits the generated plan to the user terminal.

[1350] The user provides feedback on the plan.

[1351] The user terminal causes the emotion engine to analyze the emotion data along with the feedback, and transmits it to the server.

[1352] From then on, the plan is dynamically updated based on user feedback and emotion data, and the final plan is finalized.

[1353] Example prompt: "User's initial life plan data: age 30, annual income 5 million yen, family composition: 1 spouse, 2 children, desired event: purchase a home at age 35."

[1354] Example 2: Educational Expense Scenario Generation

[1355] A user inputs a request to simulate a scenario regarding a child's education expenses.

[1356] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1357] The device sends the request and emotion data to the server.

[1358] The server forwards the request to the dialogue management computer.

[1359] The dialogue management computer sends requests and emotional data to the AI ​​life plan simulation engine.

[1360] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school chosen, and identifies the appropriate scenario for the user.

[1361] The server transmits the generated scenario to the user terminal.

[1362] The user selects the most suitable educational plan based on the provided scenario.

[1363] Example prompt: "Future income change scenario: Generate a life plan taking into account income changes over the next 10 years."

[1364] This allows users to independently create specific and reliable life plans, reducing future anxiety and promoting systematic life planning. Furthermore, the emotion engine takes the user's emotional state into account, enabling more personalized and appropriate planning.

[1365] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1366] Program processing flow

[1367] Entering and submitting initial data

[1368] Step 1:

[1369] The user launches the life plan simulation app.

[1370] Specific actions: Open the simulation app on your smartphone or PC and access the app's login screen.

[1371] Input: None

[1372] Output: Login screen displayed

[1373] Step 2:

[1374] The user enters initial data such as age, income, family composition, and desired life events.

[1375] Specific actions: Enter the required information into the app's input form (e.g., "30 years old, annual income of 5 million yen, family composition of one spouse and two children, desired life event is to purchase a home at age 35") and press the submit button.

[1376] Input: Initial data (age, income, family structure, desired life events)

[1377] Output: Submit button click event

[1378] Step 3:

[1379] The user terminal receives the data entered by the user and transmits it to the server.

[1380] Specific operation: Save input data locally and send it to the server using an API.

[1381] Input: User initial data

[1382] Output: Initial data sent to the server

[1383] Analysis of initial data and generation of life plans

[1384] Step 4:

[1385] The server receives the data from the user terminal.

[1386] Specific operation: The server receives data sent from the user device via API.

[1387] Input: Initial data from the user's terminal

[1388] Output: Initial data received by the server

[1389] Step 5:

[1390] The server transfers the received data to the dialogue management computer.

[1391] Specific operation: The server analyzes the received data, converts it into an appropriate format, and transfers it to the dialogue management computer.

[1392] Input: Initial data received

[1393] Output: Data transferred to the dialogue management computer

[1394] Step 6:

[1395] The dialogue management computer analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[1396] What it does: Parses the data and sends the request in the appropriate format to the AI ​​life plan simulation engine.

[1397] Input: Received data

[1398] Output: Request data

[1399] Step 7:

[1400] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[1401] What it does: Generates an initial life plan based on input data and known algorithms.

[1402] Input: Request data

[1403] Output: Initial life plan

[1404] Step 8:

[1405] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[1406] Specific operation: The generated life plan is sent to the user's device and the results are displayed on the app screen.

[1407] Input: Initial Life Plan

[1408] Output: Initial life plan sent to user device

[1409] Enter feedback and update your plan

[1410] Step 9:

[1411] The user enters feedback on the plan (requests for corrections, additions, etc.).

[1412] Specific actions: Enter desired changes or additional requests in the feedback field and submit.

[1413] Input: Feedback data

[1414] Output: Submit button click event

[1415] Step 10:

[1416] The user terminal receives the feedback data and causes the emotion engine to analyze the emotion data.

[1417] Specific behavior: Passes feedback data to the emotion engine and analyzes the user's emotions.

[1418] Input: Feedback data

[1419] Output: Emotion data

[1420] Step 11:

[1421] The terminal transmits the feedback together with the emotion data to the server.

[1422] Specific operation: Sends the analyzed data to the server.

[1423] Input: Feedback data, emotion data

[1424] Output: Feedback and emotion data sent to the server

[1425] Step 12:

[1426] The server transfers the feedback and emotion data to the dialogue management computer.

[1427] Specific operation: The server sends feedback and emotion data to the dialogue management computer.

[1428] Input: Feedback data, emotion data

[1429] Output: Feedback and emotion data transmitted to the dialogue management computer

[1430] Step 13:

[1431] The dialogue management computer analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[1432] Specific operation: Analyzes the feedback content and emotional data, and sends an update request to the AI ​​life plan simulation engine.

[1433] Input: Feedback data, emotion data

[1434] Output: Update request

[1435] Step 14:

[1436] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[1437] What it does: Update your life plan with new data.

[1438] Input: Update request

[1439] Output: Updated Life Plan

[1440] Step 15:

[1441] The server transmits the updated life plan to the user terminal and displays it again.

[1442] Specific operation: The updated plan is sent to the user's device and displayed again on the app screen.

[1443] Enter: Updated Life Plan

[1444] Output: Updated life plan sent to user device

[1445] Requesting and Providing Expert Advice

[1446] Step 16:

[1447] A user enters a request for expert advice in a particular area (e.g., mortgage, insurance, etc.).

[1448] What you do: Select the area of ​​advice you need, enter details, and submit your request.

[1449] Input: Advice request

[1450] Output: Submit button click event

[1451] Step 17:

[1452] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1453] Specific operation: Receives request data and requests the emotion engine to analyze it.

[1454] Input: Advice request

[1455] Output: Emotion data

[1456] Step 18:

[1457] The terminal transmits the emotion data together with the request to the server.

[1458] Specific behavior: Sends request and emotion data to the server.

[1459] Input: Advice request, emotion data

[1460] Output: Advice request and emotion data sent to the server

[1461] Step 19:

[1462] The server sends the request and the emotion data to the expert advice generation engine.

[1463] Specific operation: The server sends the request content and emotion data to the expert advice generation engine.

[1464] Input: Advice request, emotion data

[1465] Output: Expert Advice Request

[1466] Step 20:

[1467] An expert advice generation engine generates advice based on the emotion data and sends it back to the server.

[1468] Specific behavior: Generate optimal advice taking into account emotional data.

[1469] Input: Advice request, emotion data

[1470] Output: Expert advice

[1471] Step 21:

[1472] The server transmits the generated advice to the user terminal and displays it to the user.

[1473] Specific operation: The generated advice is sent to the user's device and displayed on the app screen.

[1474] Enter: Expert Advice

[1475] Output: Expert advice sent to the user's device

[1476] Generating future scenarios

[1477] Step 22:

[1478] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[1479] Specific Action: Enter details of the future scenario and submit a simulation request.

[1480] Input: Simulation request

[1481] Output: Submit button click event

[1482] Step 23:

[1483] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1484] Specific operation: Receives request data and requests the emotion engine to analyze it.

[1485] Input: Simulation request

[1486] Output: Emotion data

[1487] Step 24:

[1488] The terminal transmits the emotion data together with the request to the server.

[1489] Specific behavior: Sends request and emotion data to the server.

[1490] Input: Simulation request, emotion data

[1491] Output: Simulation request and emotion data sent to the server

[1492] Step 25:

[1493] The server sends the request and emotion data to the dialogue management computer.

[1494] Specific operation: The server sends the request content and emotion data to the dialogue management computer.

[1495] Input: Simulation request, emotion data

[1496] Output: Request and emotion data transmitted to the dialogue management computer

[1497] Step 26:

[1498] The dialogue management computer sends requests and emotional data to the AI ​​life plan simulation engine.

[1499] Specific operation: Sends a request and emotion data and requests scenario generation.

[1500] Input: Request, emotion data

[1501] Output: Simulation request

[1502] Step 27:

[1503] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[1504] Specific operation: Generate multiple future scenarios based on various data and identify scenarios that are advantageous or require caution.

[1505] Input: Simulation request

[1506] Output: Future scenario

[1507] Step 28:

[1508] The server transmits the generated scenario to the user terminal and displays it to the user.

[1509] Specific operation: The generated scenario is sent to the user's device and displayed on the app screen.

[1510] Input: Future scenario

[1511] Output: Future scenario sent to the user device

[1512] (Application example 2)

[1513] 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."

[1514] Currently, many users struggle with managing income and expenses and simulating future scenarios when creating their future life plans. In particular, the lack of professional advice and the ability to adjust plans to accommodate fluctuations in income and expenses makes it difficult to create accurate and effective life plans. Furthermore, the lack of consideration for user emotions in planning makes it difficult to provide plans that are satisfactory. A system that solves these problems is needed.

[1515] 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 a user terminal to input initial data related to a life plan and transmit the data to the server; means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine; means for the AI ​​life plan simulation engine to generate an initial life plan simulation and return it to the server; means for the server to transmit the generated initial life plan to the user terminal; means for the user to input feedback on the life plan and transmit the feedback to the server; means for the server to transmit the received feedback to the AI ​​life plan simulation engine to update the plan; means for the user terminal to input data for managing daily income and expenses and transmit the data to the server; means for the server to analyze the received income and expense data and provide the user with saving tips and investment suggestions; and means for the emotion engine to analyze the user's emotion data and transmit the data to the server to reflect the results. This allows the user to update their life plan as needed to reflect fluctuations in income and expenses and receive expert advice. Furthermore, users can receive personalized feedback that takes emotional data into account, which is expected to help create a more satisfying life plan.

[1516] A "user terminal" is a device that allows a user to input data related to life plans and income / expense management and transmit it to the server.

[1517] The "server" is a central management system that analyzes data received from users and executes processing in cooperation with other engines, such as the AI ​​life plan simulation engine.

[1518] The "AI Life Plan Simulation Engine" is an artificial intelligence module that analyzes the initial data and feedback provided by users to generate and update life plans.

[1519] "Feedback" is information such as desired modifications or additions that the user inputs to the generated life plan.

[1520] The "emotion engine" is a software module that recognizes emotions from the user's facial expressions, voice, and text input, analyzes the emotional data, and reflects it in simulation results and feedback.

[1521] An "expert advice generation engine" is an artificial intelligence module that generates appropriate advice for users based on specialized knowledge in a particular field.

[1522] "Income" refers to financial resources such as monetary income or salary that a user receives within a certain period of time.

[1523] "Expenses" refers to all payments made by a user within a certain period of time, including living expenses and money spent on hobbies.

[1524] "Savings Tips" are suggestions and advice to help users reduce wasteful spending and manage their money efficiently.

[1525] An "investment proposal" is a proposal for specific investment destinations and methods that will enable users to effectively manage their funds and earn profits.

[1526] A "prompt" is text data input to a generative AI model, and is an instruction that enables the model to generate appropriate answers or advice.

[1527] The present invention relates to a system that allows users to independently create and manage their own life plans. This system is composed of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine. Specific embodiments for implementing the present invention are described below.

[1528] System Overview

[1529] 1. User Device:

[1530] Through the interface, users input initial data about their life plan (age, income, family composition, desired life events, etc.).

[1531] You can also enter data to manage your daily income and expenses.

[1532] The user terminal transmits this data to the server.

[1533] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[1534] 2. Server:

[1535] The server is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management server and various engines.

[1536] Initial data, feedback, and emotional data are transferred to the dialogue management server, and the analysis results are sent to the user's terminal.

[1537] It analyzes income and expenditure data and provides users with savings tips and investment suggestions.

[1538] 3. Dialogue Management Server:

[1539] It is an interface server that receives and analyzes data from users and links with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[1540] 4. AI Life Plan Simulation Engine:

[1541] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[1542] Generate an initial life plan and update the plan based on daily income and expenditure.

[1543] It is built using TensorFlow.

[1544] 5. Expert advice generation engine:

[1545] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[1546] Using OpenAI GPT-3, it generates relevant expert advice based on user requests.

[1547] 6. Emotion Engine:

[1548] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to the dialogue management server.

[1549] It is built using the Microsoft Azure Emotion Recognition API.

[1550] Optimize the results of life plan simulations and expert advice based on emotional data.

[1551] Specific example explanation

[1552] Example 1: Creating a life plan for buying a home

[1553] When a user is planning to purchase a home, they use the system in the following steps: The user launches the life plan simulation app and enters information such as age, income, family composition, budget, loan amount, and desired area. The user's device sends the entered information to the server, which then forwards it to the dialogue management server. The dialogue management server sends the received data to the AI ​​life plan simulation engine, which generates an initial life plan. The user then enters feedback on the plan and sends emotional data along with the feedback to the server. The server analyzes this data and dynamically updates the plan.

[1554] Example 2: Educational Expenses Scenario Generation

[1555] This is the procedure when a user wants to simulate a scenario regarding their child's education expenses. The user inputs a request and the request is sent to the server on the user's device. The server forwards the request to the dialogue management server, which then sends it to the AI ​​life plan simulation engine. The engine generates scenarios based on changes in education expenses and the school to which the user will advance, and the user can then select the optimal education plan based on these scenarios.

[1556] Prompt Sentence Examples

[1557] For example, if you are 35 years old, have a family of four, earn 7 million yen a year, and your desired life events are buying a house and educating your children, the user would use the following prompt:

[1558] User data: {"age": 35, "income": 7000000, "family": {"members": 4}, "events": ["buy_house", "child_education"]}. Provide financial advice.

[1559] By inputting this prompt into a generative AI model, expert advice can be generated, providing the user with an appropriate life plan.

[1560] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1561] Step 1:

[1562] The user's terminal inputs initial data related to their life plan and sends that data to the server. Specifically, the user enters data about their age, income, family structure, and desired life events (e.g., buying a home, children's education, etc.) into an input form. Once this initial data is sent, it is received by the server.

[1563] Step 2:

[1564] The server analyzes the received initial data and transfers it to the dialogue management server. The server converts the initial data into JSON format and sends it to the dialogue management server. This data specifically includes the user's age, income, desired events, etc.

[1565] Step 3:

[1566] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine. The dialogue management server formats the data appropriately and constructs and sends a request to the AI ​​life plan simulation engine.

[1567] Step 4:

[1568] The AI ​​life plan simulation engine generates an initial life plan and sends it back to the server. The AI ​​life plan simulation engine uses TensorFlow to analyze and generate an initial life plan based on the user's data. The results are sent back to the server.

[1569] Step 5:

[1570] The server transmits the generated initial life plan to the user terminal. The server receives the initial life plan returned from the dialogue management server and transmits it to the user terminal. The user terminal displays the received life plan on its screen.

[1571] Step 6:

[1572] The user inputs feedback about the life plan and sends the feedback to the server. The user checks the life plan and inputs any necessary corrections or additions as feedback. This feedback is sent from the user terminal to the server.

[1573] Step 7:

[1574] The server sends the received feedback to the AI ​​life plan simulation engine to update the plan. The server analyzes the feedback data and sends it to the AI ​​life plan simulation engine. The engine updates the plan based on it and sends the result back to the server.

[1575] Step 8:

[1576] The user's terminal inputs data for managing daily income and expenses and transmits the data to the server. The user inputs details of daily income and expenses into the application, and the data is transmitted to the server.

[1577] Step 9:

[1578] The server analyzes the received income and expenditure data and provides the user with savings tips and investment suggestions. Based on this data, the server uses a generative AI model such as OpenAI GPT-3 to generate prompts and provide appropriate savings and investment advice. This advice is then sent to the user's device.

[1579] Step 10:

[1580] The emotion engine analyzes the user's emotional data and sends that data to the server, which reflects the results. The emotion engine recognizes emotions from the user's facial expressions, voice, text input, etc. and sends that emotional data to the server. The server adjusts the life plan and proposal content based on this data.

[1581] This process allows users to create and manage their life plans in real time and with a personalized interface. For example, if a 35-year-old user with an annual income of 7 million yen plans to buy a home, specific advice and updates to the plan will be automatically provided based on that plan. The generative AI model also provides advice using prompts such as:

[1582] User data: {"age": 35, "income": 7000000, "family": {"members": 4}, "events": ["buy_house", "child_education"]}. Provide financial advice.

[1583] 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.

[1584] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), 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.

[1585] 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.

[1586] [Third embodiment]

[1587] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1588] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1589] 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).

[1590] 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.

[1591] 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.

[1592] 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).

[1593] 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. 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.

[1594] 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.

[1595] 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.

[1596] 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.

[1597] 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.

[1598] 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."

[1599] This invention relates to a system that enables users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[1600] System Overview

[1601] 1. User terminal: The user inputs initial data about their life plan (age, income, family structure, desired life events, etc.) through an interface. It is also an input device for providing feedback on the generated life plan and requesting specific advice.

[1602] 2. Server: A central system that analyzes data received from user devices and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user devices.

[1603] 3. Dialogue Management Server: This is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue.

[1604] 4. AI Life Plan Simulation Engine: This is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[1605] 5. Expert Advice Generation Engine: An AI module with expertise in specific fields such as finance, insurance, real estate, etc. It receives requests from users and generates relevant advice.

[1606] Program processing

[1607] Entering and submitting initial data

[1608] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[1609] The terminal receives the data entered by the user and transmits it to the server.

[1610] Analysis of initial data and generation of initial life plan

[1611] The server analyzes the received user initial data and transfers it to the dialogue management server.

[1612] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[1613] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[1614] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[1615] Enter feedback and update your plan

[1616] The user inputs feedback (e.g., requests for corrections or additions) on the presented life plan.

[1617] The terminal receives the user's feedback and transmits it to the server.

[1618] The server forwards the feedback to the interaction management server.

[1619] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[1620] The AI ​​life plan simulation engine updates the plan based on the new feedback and sends it back to the server.

[1621] The server transmits the updated life plan to the user terminal and displays it again.

[1622] Providing expert advice

[1623] A user enters a request for advice in a particular area (eg, mortgage, insurance).

[1624] The terminal receives the request and sends it to the server.

[1625] The server sends the request to the expert advice generation engine.

[1626] The expert advice generation engine generates expert advice based on the user's request and sends it back to the server.

[1627] The server transmits the generated advice to the user terminal and displays it to the user.

[1628] Generating future scenarios

[1629] A user inputs a request to simulate a future scenario.

[1630] The terminal receives the request and sends it to the server.

[1631] The server sends the request to the AI ​​life plan simulation engine.

[1632] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable for the user and those that require caution.

[1633] The server transmits the generated scenario to the user terminal and displays it to the user.

[1634] Specific examples

[1635] Example 1: Creating a life plan for buying a home

[1636] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[1637] The terminal transmits the input information to the server.

[1638] The server forwards the received information to the dialogue management server.

[1639] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[1640] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[1641] The server transmits the generated plan to the user terminal.

[1642] The user enters feedback on the plan and submits it again.

[1643] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[1644] Example 2: Educational Expenses Scenario Generation

[1645] A user enters a request to simulate a scenario regarding their child's education expenses.

[1646] The terminal sends a request to the server.

[1647] The server sends the request to the AI ​​life plan simulation engine.

[1648] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[1649] The server transmits the generated scenario to the user terminal.

[1650] The user selects the most suitable training plan based on multiple scenarios.

[1651] This allows users to independently create specific and reliable life plans, reduce anxiety about the future, and advance systematic life planning.

[1652] The processing flow will be explained below.

[1653] Step 1:

[1654] The user launches the life plan simulation app and enters personal information (age, income, family composition, desired life events, etc.).

[1655] Step 2:

[1656] The terminal receives the data entered by the user and transmits the data to the server.

[1657] Step 3:

[1658] The server transfers the received data to the dialogue management server.

[1659] Step 4:

[1660] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[1661] Step 5:

[1662] The AI ​​life plan simulation engine generates an initial life plan simulation based on the user's initial data.

[1663] Step 6:

[1664] The server receives the generated initial life plan and transmits it to the user terminal.

[1665] Step 7:

[1666] The user checks the life plan they received and enters feedback, corrections, and additional requests.

[1667] Step 8:

[1668] The terminal receives the user's feedback and transmits the feedback to the server.

[1669] Step 9:

[1670] The server forwards the received feedback to the interaction management server.

[1671] Step 10:

[1672] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[1673] Step 11:

[1674] The AI ​​life plan simulation engine updates the plan to reflect the new feedback and sends it back to the server.

[1675] Step 12:

[1676] The server transmits the updated life plan to the user terminal.

[1677] Step 13:

[1678] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[1679] Step 14:

[1680] The terminal receives the request and sends it to the server.

[1681] Step 15:

[1682] The server forwards the received request to the expert advice generation engine.

[1683] Step 16:

[1684] The expert advice generation engine generates expert advice based on the user's request and returns the results to the server.

[1685] Step 17:

[1686] The server transmits the generated advice to the user terminal.

[1687] Step 18:

[1688] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[1689] Step 19:

[1690] The terminal receives the simulation request and sends it to the server.

[1691] Step 20:

[1692] The server sends the request to the AI ​​life plan simulation engine.

[1693] Step 21:

[1694] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[1695] Step 22:

[1696] The server transmits the generated scenario to the user terminal.

[1697] Step 23:

[1698] The user reviews the provided scenarios, selects the most suitable life plan, and enters that selection into the system.

[1699] Step 24:

[1700] The terminal receives the user's final selection and transmits it to the server.

[1701] Step 25:

[1702] The server sends the final selection to the dialogue management server, requesting the generation of a final life plan.

[1703] Step 26:

[1704] The AI ​​life plan simulation engine generates the final life plan and sends it back to the server.

[1705] Step 27:

[1706] The server transmits the final life plan to the user terminal and displays it to the user.

[1707] Through these steps, we have created a system that allows users to dynamically and interactively create and update their life plans and receive expert advice to form the optimal life plan.

[1708] Example 1

[1709] 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."

[1710] Conventional life plan creation systems have the problem that it is difficult for users to obtain appropriate advice when they do not have specialized knowledge or when they have limited access to advice, and they are unable to fully meet the needs of users. Another problem is that simulating and updating a life plan is time-consuming and tedious. The purpose of this invention is to solve these problems and enable users to effectively create and manage their life plans on their own.

[1711] 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.

[1712] In this invention, the server includes: means for a user terminal to input initial data regarding a life plan and transmit the data to the server; means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine via the dialogue management server; means for the AI ​​life plan simulation engine to generate an initial life plan simulation and transmit it back to the server; means for the server to transmit the generated initial life plan to the user terminal; means for the user to input feedback regarding the life plan and transmit the feedback to the server; and means for transmitting the feedback received by the server to the AI ​​life plan simulation engine via the dialogue management server to update the plan. This enables the AI ​​to dynamically generate and update a life plan and obtain expert advice based on the initial data and feedback input by the user.

[1713] A "user terminal" is a device through which a user inputs data related to their life plan and communicates with the server.

[1714] The "server" is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management server and various engines.

[1715] The "dialogue management server" is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine.

[1716] The "AI Life Plan Simulation Engine" is an AI module that generates and updates life plan simulations based on the user's initial data and feedback.

[1717] An "expert advice generation engine" is an AI module that has expertise in a specific field and generates expert advice based on requests from users.

[1718] "Initial data" refers to basic information that a user inputs to create a life plan, and includes age, income, family structure, desired life events, and the like.

[1719] "Feedback" refers to opinions and requests, such as corrections and additions, provided by the user regarding the generated life plan.

[1720] A "request" is input data that a user inputs to the server, requesting specific advice or a simulation of a future scenario.

[1721] "Simulation" refers to the process of predicting and generating future life plans and multiple future scenarios carried out by an AI life plan simulation engine.

[1722] This invention relates to a system that allows users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[1723] System Overview

[1724] User terminal

[1725] The user terminal is a device where a user inputs initial data about their life plan and transmits that data to a server. The user terminal has an interface through which the user inputs initial data such as age, income, family composition, and desired life events through an application. The user terminal is also an input device for providing feedback on the generated life plan and requesting specific advice.

[1726] server

[1727] The server is a central system that analyzes data received from user terminals and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user terminal. The server also collaborates with the expert advice generation engine to provide expert advice.

[1728] Dialogue Management Server

[1729] The dialogue management server is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue and sends the initial data and feedback received from users to each engine.

[1730] AI life plan simulation engine

[1731] The AI ​​life plan simulation engine is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[1732] Expert Advice Generation Engine

[1733] An expert advice generation engine is an AI module with specialized knowledge in a specific field, such as finance, insurance, or real estate, that receives requests from users and generates relevant advice.

[1734] Specific examples

[1735] Example 1: Creating a life plan for buying a home

[1736] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[1737] The terminal transmits the input information to the server.

[1738] The server forwards the received information to the dialogue management server.

[1739] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[1740] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[1741] The server transmits the generated plan to the user terminal.

[1742] The user enters feedback on the plan and submits it again.

[1743] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[1744] Example 2: Educational Expenses Scenario Generation

[1745] A user enters a request to simulate a scenario regarding their child's education expenses.

[1746] The terminal sends a request to the server.

[1747] The server sends the request to the AI ​​life plan simulation engine.

[1748] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[1749] The server transmits the generated scenario to the user terminal.

[1750] The user selects the most suitable training plan based on multiple scenarios.

[1751] Prompt Sentence Examples

[1752] 1. "Generate a life plan based on your home buying budget and desired area."

[1753] 2. "Simulate several scenarios for your child's education expenses."

[1754] This system allows users to independently create specific and reliable life plans, reducing anxiety about the future and enabling them to plan their lives in a planned manner.

[1755] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1756] Step 1: Enter initial data

[1757] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[1758] Input: Any initial data that a user enters into an app form.

[1759] Output: The input data is compiled as JSON format data.

[1760] What happens: Data is collected when a user fills out a form on the app and clicks the "Submit" button.

[1761] Step 2: Sending initial data

[1762] The terminal receives the initial data entered by the user and transmits it to the server.

[1763] Input: Initial data in JSON format.

[1764] Output: The initial data sent to the server.

[1765] Specific operation: The terminal's data transmission module sends the initial data to the server using an HTTPS request.

[1766] Step 3: Analyze the initial data

[1767] The server analyzes the received initial data and forwards it to the dialogue management server.

[1768] Input: The initial data received by the server in JSON format.

[1769] Output: The parsed data is transferred to the dialogue management server.

[1770] Specific operation: The server analyzes the initial data using a data analysis algorithm, and then reformats and transmits the analysis results to the dialogue management server.

[1771] Step 4: Submitting a simulation request

[1772] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[1773] Input: Analysis results based on initial data.

[1774] Output: The request sent to the AI ​​life plan simulation engine.

[1775] Specific operation: The dialogue management server formats the analysis results into a format that the AI ​​engine can understand and submits a request via API.

[1776] Step 5: Generate an initial life plan

[1777] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[1778] Input: The request data received from the server.

[1779] Output: Generated initial life plan.

[1780] How it works: The AI ​​engine uses past data and statistical models to generate a life plan that best suits the user's initial data.

[1781] Step 6: Displaying your initial life plan

[1782] The server transmits the generated initial life plan to the user terminal.

[1783] Input: Initial life plan returned from the AI ​​life plan simulation engine.

[1784] Output: The initial life plan sent to the user's device.

[1785] Specific operation: The server re-encodes the life plan data into JSON format and sends it to the user's device as an HTTPS response.

[1786] Step 7: Provide feedback

[1787] The user inputs feedback (e.g., requests for corrections or additions) on the presented life plan.

[1788] Input: Feedback based on the life plan provided.

[1789] Output: The input feedback data.

[1790] Specific behavior: A user fills in the required information in the app's feedback form and clicks the "Submit Feedback" button.

[1791] Step 8: Submit your feedback

[1792] The terminal receives the user's feedback and transmits it to the server.

[1793] Input: User feedback data.

[1794] Output: Feedback data sent to the server.

[1795] Specific operation: The device obtains the feedback data and issues an HTTPS request to the server.

[1796] Step 9: Analyze feedback

[1797] The server forwards the feedback to the interaction management server.

[1798] Input: The feedback data received by the server.

[1799] Output: Feedback data transmitted to the dialogue management server.

[1800] Specific operation: The server checks the received feedback data and notifies the dialogue management server.

[1801] Step 10: Submit a plan renewal request

[1802] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[1803] Input: User feedback data.

[1804] Output: Update request to the AI ​​life plan simulation engine.

[1805] Specific operation: Based on the feedback received, the dialogue management server issues an API request to send an update instruction.

[1806] Step 11: Update your plan

[1807] The AI ​​life plan simulation engine updates the plan based on the new feedback and sends it back to the server.

[1808] Input: The update request received from the server.

[1809] Output: Updated life plan.

[1810] What it does: The AI ​​engine generates an updated simulation, taking into account new data inputs.

[1811] Step 12: View the updated plan

[1812] The server transmits the updated life plan to the user terminal and displays it again.

[1813] Input: Updated life plan returned from the AI ​​life plan simulation engine.

[1814] Output: The updated life plan sent to the user device.

[1815] Specific operation: The server notifies the user device of the received update plan data and sends it again as display data.

[1816] Step 13: Fill out your advice request

[1817] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[1818] Input: The content of your advice request.

[1819] Output: The input advice request.

[1820] What happens: A user fills out the "Advice Request" form in the app and clicks the "Submit" button.

[1821] Step 14: Submitting the Request

[1822] The terminal receives the request and sends it to the server.

[1823] Input: User advice request data.

[1824] Output: The advice request data sent to the server.

[1825] Specific operation: The device obtains the request data and issues an HTTPS request to the server.

[1826] Step 15: Submitting an Advice Generation Request

[1827] The server sends the request to the expert advice generation engine via the dialogue management server.

[1828] Input: User advice request data.

[1829] Output: A request to the Expert Advice generation engine.

[1830] What happens: The server formats the request data appropriately and makes an API call to the Expert Advice generation engine.

[1831] Step 16: Generating Advice

[1832] The expert advice generation engine generates expert advice based on the user's request and sends it back to the server.

[1833] Input: The request data received from the server.

[1834] Output: The generated advice.

[1835] Specific behavior: The engine references relational databases and knowledge bases to generate specific advice tailored to the user's situation.

[1836] Step 17: Viewing Advice

[1837] The server transmits the generated advice to the user terminal and displays it to the user.

[1838] Input: Advice returned from the Expert Advice generation engine.

[1839] Output: Advice sent to the user's terminal.

[1840] Specific operation: The server transfers the received advice data to the user's device and displays it within the app.

[1841] Step 18: Entering Scenario Requests

[1842] A user inputs a request to simulate a future scenario.

[1843] Input: The contents of the scenario request.

[1844] Output: The input scenario request.

[1845] Specific behavior: The user fills out the app's "Scenario Simulation" form and clicks the "Submit" button.

[1846] Step 19: Submitting the Request

[1847] The terminal receives the request and sends it to the server.

[1848] Input: User's scenario request data.

[1849] Output: The scenario request data sent to the server.

[1850] Specific operation: The device obtains the request data and issues an HTTPS request to the server.

[1851] Step 20: Submitting a Simulation Request

[1852] The server sends the request to the AI ​​life plan simulation engine via the dialogue management server.

[1853] Input: User's scenario request data.

[1854] Output: A request to the AI ​​life plan simulation engine.

[1855] Specific operation: The server formats the request data appropriately and makes an API call to the AI ​​engine.

[1856] Step 21: Generate scenarios

[1857] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable for the user and those that require caution.

[1858] Input: Scenario request data received from the server.

[1859] Output: Generated future scenarios.

[1860] How it works: The AI ​​engine uses statistical models and predictive algorithms to simulate different future scenarios and assess the benefits and risks of each.

[1861] Step 22: Viewing the scenario

[1862] The server transmits the generated scenario to the user terminal and displays it to the user.

[1863] Input: Scenario returned from the AI ​​life plan simulation engine.

[1864] Output: The scenario sent to the user's device.

[1865] Specific operation: The server transfers the received scenario data to the user's device and displays it within the app.

[1866] (Application example 1)

[1867] 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."

[1868] In modern society, it is extremely important for individuals to effectively manage their own life plans and financial plans. However, it is difficult for ordinary users without specialized knowledge to do this on their own, as they are required to understand complex information and analyze vast amounts of data. To solve this problem, there is a need for a system that allows users to easily create and manage their life plans and receive professional financial advice.

[1869] 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.

[1870] In this invention, the server includes means for a user terminal to input initial data regarding a life plan and transmit the data to the server, means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine, means for the AI ​​life plan simulation engine to generate an initial life plan simulation and transmit it back to the server, means for the server to transmit the generated initial life plan to the user terminal, means for the user to input feedback regarding the life plan and transmit the feedback to the server, means for the server to transmit the received feedback to the AI ​​life plan simulation engine to update the plan, and means for the user terminal to input financial data and transmit the data to the AI ​​life plan simulation engine. The system includes a means for transmitting the financial plan to a cloud server, a means for the cloud server to analyze the received data and transmit it to an AI life plan simulation engine, a means for the AI ​​life plan simulation engine to generate a financial plan and return it to the cloud server, a means for the cloud server to transmit the generated financial plan to a user terminal, a means for the user terminal to request advice on a specific field and transmit the request to the server, a means for the server to transmit the received request to an expert advice generation engine, a means for the expert advice generation engine to generate expert advice based on the user request and transmit it back to the server, and a means for the server to transmit the generated advice to the user terminal. This allows users to create their own life plans and easily receive expert advice. It also allows users to understand their own financial situation and effectively manage their future plans.

[1871] A "user terminal" is a device that allows a user to input, send, and receive life plans and financial data.

[1872] A "server" is a central control device that analyzes data received from user terminals and coordinates with other engines and servers.

[1873] The "AI Life Plan Simulation Engine" is an artificial intelligence module that generates and updates life plans and financial plans based on the user's initial data and feedback.

[1874] A "cloud server" is a remote server on the Internet for receiving data from a user terminal and transmitting the analyzed and generated plan to the user terminal.

[1875] An "expert advice generation engine" is an artificial intelligence module that generates expert advice on a specific subject based on a user's request.

[1876] A "life plan" is a plan for a user's life planning, and is an overall strategy that takes into consideration age, income, family structure, desired life events, and the like.

[1877] "Feedback" refers to inputting corrections or additional requests for plans or proposals provided by the user.

[1878] "Specific fields" refer to areas requiring specialized knowledge, such as finance, insurance, real estate, and education expenses.

[1879] "Financial Data" is information related to a user's personal financial situation, such as their income, expenses, and savings goals.

[1880] A "financial plan" is a plan for short-term and long-term income and expenditure management and asset formation that is generated based on the user's financial data.

[1881] A "future financial scenario" is a simulation of future income and expenditures and asset status that is generated based on the user's financial data.

[1882] A "request" is a request submitted by a user for a particular piece of advice or simulation.

[1883] "Analysis" is the process of processing received data and extracting meaningful information.

[1884] A "system" is a structure in which multiple hardware and software components work together to provide a specific function.

[1885] The present invention is a system that allows users to conveniently create and manage their own life plans and financial plans. This system consists of a user terminal, a cloud server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[1886] System Overview

[1887] 1. User Device:

[1888] The user terminal is a device where users input, send, and receive their life plan and financial data. Users input initial data such as age, income, family composition, and desired life events through a smartphone app and send the data to the cloud server.

[1889] 2. Cloud Server:

[1890] The cloud server is a central control unit that analyzes data received from user devices and coordinates with other engines and servers. The cloud server transmits the received data to the dialogue management server and sends requests for analysis and calculation.

[1891] 3. Dialogue Management Server:

[1892] The dialogue management server is responsible for linking the AI ​​life plan simulation engine and the expert advice generation engine based on user input data, and plays a role in appropriately distributing user requests and sending them to each engine.

[1893] 4. AI Life Plan Simulation Engine:

[1894] The AI ​​Life Plan Simulation Engine is an artificial intelligence module that generates and updates initial life plans and financial plans based on the user's initial data and feedback. The engine is implemented using machine learning frameworks such as TensorFlow or PyTorch.

[1895] 5. Expert advice generation engine:

[1896] An expert advice generation engine is an AI module that generates expert advice on a specific subject based on user requests, using natural language processing models such as GPT-3 or BERT.

[1897] Specific examples

[1898] Example 1: Creating a life plan for buying a home

[1899] The user enters information such as their home purchase budget, loan amount, and desired area through a smartphone app. The smartphone app sends the entered information to a cloud server, which then sends the data to the AI ​​life plan simulation engine via a dialogue management server. The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the cloud server. The cloud server then sends the generated plan to the smartphone app and displays it to the user. The user then enters feedback on this plan and submits it again. This allows the plan to be dynamically updated based on the feedback, and the final plan is finalized.

[1900] Prompt Sentence Examples

[1901] "The user is 35 years old, has an annual income of 6 million yen, and consists of a couple and two children. If they plan to purchase a home within the next five years, please provide specific advice on what type of loan and financial management they should take, and which area would be suitable."

[1902] This system allows users to create their own life plans and easily receive professional advice, while also helping users understand their own financial situation and effectively manage their future plans.

[1903] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1904] Step 1:

[1905] The user launches the smartphone app and enters initial data such as age, income, family composition, and desired life events. The entered data is temporarily stored in the smartphone app's local storage. The user then presses the "Send" button, which sends the data to the cloud server.

[1906] Input: Age, income, family structure, desired life events

[1907] Output: Initial data sent to the cloud server

[1908] Step 2:

[1909] The cloud server analyzes the initial data received from the user terminal and sends it to the dialogue management server, which converts the received data into a format required to send it as a request to the AI ​​life plan simulation engine.

[1910] Input: Initial data from the user's terminal

[1911] Output: Data in request format to the dialogue management server

[1912] Step 3:

[1913] The dialogue management server sends the received initial data to the AI ​​life plan simulation engine, which performs calculations to generate an initial life plan based on the data. Specifically, an algorithm is executed to generate an optimal financial plan based on the user's age, income, and family structure.

[1914] Input: Initial data from the dialogue management server

[1915] Output: Generated initial life plan

[1916] Step 4:

[1917] The AI ​​life plan simulation engine returns the generated initial life plan to the cloud server, which then transmits the generated life plan to the user's device.

[1918] Input: Initial life plan

[1919] Output: Data sent to the user terminal

[1920] Step 5:

[1921] The user checks the initial life plan presented on the smartphone app and enters feedback as necessary. Feedback can include requests for revisions or additions to the plan. When the user presses the "Send Feedback" button, the feedback data is sent to the cloud server.

[1922] Input: User feedback

[1923] Output: Feedback data to the cloud server

[1924] Step 6:

[1925] The cloud server analyzes the feedback received from the user and sends it to the AI ​​life plan simulation engine via the dialogue management server. The AI ​​life plan simulation engine generates a new life plan that reflects the feedback.

[1926] Input: Feedback data

[1927] Output: Updated Life Plan

[1928] Step 7:

[1929] The updated life plan is sent to the user's device via the cloud server. The user reviews the life plan again and provides additional feedback if necessary. This process is repeated until a plan that satisfies the user is generated.

[1930] Input: Updated Life Plan

[1931] Output: Data sent to the user terminal

[1932] Step 8:

[1933] When a user requests advice on a specific topic, they input the request through a smartphone app and send it to a cloud server. For example, they can ask for advice on investment strategies or how to choose a loan.

[1934] Input: Request for advice on a specific subject

[1935] Output: Request data to the cloud server

[1936] Step 9:

[1937] The cloud server sends the received request to an expert advice generation engine, which generates expert advice based on the request and sends it back to the cloud server.

[1938] Input: Request for advice

[1939] Output: Generated expert advice

[1940] Step 10:

[1941] The cloud server sends the generated expert advice to the user's device, where the user can check the expert advice on the smartphone app and decide on the next action to take if necessary.

[1942] Enter: Expert Advice

[1943] Output: Data sent to the user terminal

[1944] 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.

[1945] This invention relates to a system that enables users to independently create and manage their life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine.

[1946] System Overview

[1947] 1. User Device:

[1948] Through the interface, users input initial data about their life plan (age, income, family composition, desired life events, etc.).

[1949] The user terminal receives the user's input data and transmits it to the server.

[1950] An input device that allows a user to enter a request for feedback or specific advice.

[1951] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[1952] 2. Server:

[1953] It is a central system that analyzes data received from user terminals and manages collaboration with the dialogue management server and various engines.

[1954] The initial data, feedback, and emotion data are transferred to the dialogue management server, and the response is sent to the user terminal.

[1955] 3. Dialogue Management Server:

[1956] It is an interface server that receives and analyzes data from users and links with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[1957] 4. AI Life Plan Simulation Engine:

[1958] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[1959] It has the ability to verbalize and quantify users' vague anxieties and requests.

[1960] 5. Expert advice generation engine:

[1961] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[1962] It receives requests from users and generates relevant advice.

[1963] 6. Emotion Engine:

[1964] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to the dialogue management server.

[1965] Optimize the results of life plan simulations and expert advice based on emotional data.

[1966] Program processing

[1967] Enter and submit initial data:

[1968] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[1969] The user terminal receives the data entered by the user and transmits it to the server.

[1970] Analysis of initial data and generation of life plan:

[1971] The server transfers the received data to the dialogue management server.

[1972] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[1973] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[1974] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[1975] Leave feedback and update your plan:

[1976] The user enters feedback about the plan (e.g., correction requests, additional requests).

[1977] The user terminal receives the feedback data and causes the emotion engine to analyze the emotion data.

[1978] The device sends the feedback along with the emotion data to the server.

[1979] The server forwards the feedback and emotion data to the dialogue management server.

[1980] The dialogue management server analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[1981] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[1982] The server transmits the updated life plan to the user terminal and displays it again.

[1983] Requesting and Providing Expert Advice:

[1984] A user enters a request for expert advice in a particular area (e.g., mortgage, insurance).

[1985] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1986] The device sends the emotion data along with the request to the server.

[1987] The server sends the request and emotion data to the expert advice generation engine.

[1988] An expert advice generation engine generates advice based on the emotion data and returns it to the server.

[1989] The server transmits the generated advice to the user terminal and displays it to the user.

[1990] Generate future scenarios:

[1991] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[1992] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[1993] The device sends the request and emotion data to the server.

[1994] The server sends the request and emotion data to the dialogue management server.

[1995] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[1996] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[1997] The server transmits the generated scenario to the user terminal and displays it to the user.

[1998] Specific examples

[1999] Example 1: Creating a life plan for buying a home

[2000] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[2001] The user terminal transmits the input information to the server.

[2002] The server forwards the received information to the dialogue management server.

[2003] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[2004] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[2005] The server transmits the generated plan to the user terminal.

[2006] The user provides feedback on the plan.

[2007] The user terminal causes the emotion engine to analyze the emotion data along with the feedback, and transmits it to the server.

[2008] From then on, the plan is dynamically updated based on user feedback and emotion data, and the final plan is finalized.

[2009] Example 2: Educational Expenses Scenario Generation

[2010] A user enters a request to simulate a scenario regarding their child's education expenses.

[2011] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[2012] The device sends the request and emotion data to the server.

[2013] The server forwards the request to the interaction management server.

[2014] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[2015] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school chosen, and identifies the appropriate scenario for the user.

[2016] The server transmits the generated scenario to the user terminal.

[2017] The user selects the most suitable educational plan based on the provided scenario.

[2018] This allows users to independently create specific and reliable life plans, reducing future anxiety and promoting systematic life planning. Furthermore, the emotion engine takes the user's emotional state into account, enabling more personalized and appropriate planning.

[2019] The processing flow will be explained below.

[2020] Step 1:

[2021] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[2022] Step 2:

[2023] The terminal receives the data entered by the user and transmits the data to the server.

[2024] Step 3:

[2025] The emotion engine collects emotional data from the user's facial expressions, voice, and text input.

[2026] Step 4:

[2027] The terminal receives the emotion data and transmits it to the server together with the initial data.

[2028] Step 5:

[2029] The server transfers the received initial data and emotion data to the dialogue management server.

[2030] Step 6:

[2031] The dialogue management server analyzes the initial data and emotional data and sends a request to the AI ​​life plan simulation engine.

[2032] Step 7:

[2033] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and emotional data and sends it back to the server.

[2034] Step 8:

[2035] The server transmits the generated initial life plan to the user terminal.

[2036] Step 9:

[2037] The user reviews the initial life plan and enters feedback, corrections, and additional requests.

[2038] Step 10:

[2039] The terminal receives the user's feedback and runs the emotion engine again to update the emotion data.

[2040] Step 11:

[2041] The device sends the user's feedback and updated emotion data to the server.

[2042] Step 12:

[2043] The server transfers the received feedback and emotion data to the dialogue management server.

[2044] Step 13:

[2045] The dialogue management server analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[2046] Step 14:

[2047] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[2048] Step 15:

[2049] The server transmits the updated life plan to the user terminal.

[2050] Step 16:

[2051] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[2052] Step 17:

[2053] The terminal receives the request and causes the emotion engine to update the emotion data.

[2054] Step 18:

[2055] The device sends the request and emotion data to the server.

[2056] Step 19:

[2057] The server sends the request and emotion data to the expert advice generation engine.

[2058] Step 20:

[2059] An expert advice generation engine generates expert advice based on the emotion data and sends it back to the server.

[2060] Step 21:

[2061] The server transmits the generated advice to the user terminal.

[2062] Step 22:

[2063] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[2064] Step 23:

[2065] The terminal receives the simulation request and causes the emotion engine to update the emotion data.

[2066] Step 24:

[2067] The device sends the request and emotion data to the server.

[2068] Step 25:

[2069] The server transfers the request and the emotion data to the dialogue management server.

[2070] Step 26:

[2071] The dialogue management server sends the request and emotional data to the AI ​​life plan simulation engine.

[2072] Step 27:

[2073] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[2074] Step 28:

[2075] The server transmits the generated scenario to the user terminal.

[2076] Step 29:

[2077] The user reviews the provided scenarios, selects the most suitable life plan, and inputs the selection into the terminal.

[2078] Step 30:

[2079] The terminal receives the user's final selection and causes the emotion engine to update the emotion data.

[2080] Step 31:

[2081] The terminal transmits the user's final selection and emotion data to the server.

[2082] Step 32:

[2083] The server sends the final selection and emotion data to the dialogue management server, requesting it to generate a final life plan.

[2084] Step 33:

[2085] The AI ​​life plan simulation engine generates the final life plan and returns the results, taking into account emotional data, to the server.

[2086] Step 34:

[2087] The server transmits the final life plan to the user terminal and displays it to the user.

[2088] Through these steps, users can dynamically and interactively create and update their life plans, and receive expert advice to create the optimal life plan. Furthermore, the introduction of an emotion engine enables personalized planning that takes into account the user's emotional state.

[2089] Example 2

[2090] 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."

[2091] Conventional life plan creation systems make it difficult for users to independently create a balanced life plan, and it is difficult to achieve optimal planning when users lack specialized knowledge. Furthermore, there are insufficient means to consider users' emotions and feedback, making it difficult to provide personalized advice.

[2092] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2093] In this invention, the server includes a means for inputting initial data related to a life plan from a user terminal and transmitting the data to the server, a means for the server to analyze the received initial data and transfer it to a dialogue management computer, and a means for the dialogue management computer to analyze the received data and send a request to the AI ​​life plan simulation engine. This allows users to independently create a well-balanced life plan without specialized knowledge. Furthermore, a system is realized that takes into account the user's emotions and feedback and provides personalized advice.

[2094] A "user terminal" is an interface through which a user inputs data related to a life plan and transmits the data to a server.

[2095] A "server" is a central system that analyzes data received from user terminals and transfers the data to various engines and computers.

[2096] The "dialogue management computer" is a computer system that has the function of analyzing data received from the server and sending requests to the AI ​​life plan simulation engine.

[2097] The "AI Life Plan Simulation Engine" is an artificial intelligence module that generates and updates life plans based on the user's initial data and feedback.

[2098] An "expert advice generation engine" is an artificial intelligence module that generates advice based on user requests and emotional data, using specialized knowledge in a specific field.

[2099] "Emotion data" is data that indicates the emotional state of the user, obtained from facial expressions, voice, text input, and the like.

[2100] "Feedback" is data that indicates opinions and requests for revisions regarding the life plan and advice provided by the user.

[2101] A "future scenario" is a plan for simulating various situations in the future, such as fluctuations in income and changes in economic conditions.

[2102] "Initial data" refers to data such as age, income, family structure, and desired life events that the user inputs as basic information for creating a life plan.

[2103] This invention relates to a system that allows users to independently create and manage their own life plans. This system is composed of the following components: a user terminal, a server, a dialogue management computer, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine.

[2104] System configuration

[2105] 1. User Device:

[2106] Users use the life plan simulation app to input initial data such as age, income, family composition, and desired life events.

[2107] The user terminal receives and transmits input data to the server, and is also an input device for inputting user feedback and specific advice requests.

[2108] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[2109] 2. Server:

[2110] The server is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management computer and various engines.

[2111] The server transfers the initial data, feedback, and emotion data to the dialogue management computer, and sends the response to the user terminal.

[2112] 3. Dialogue Management Computer:

[2113] The dialogue management computer is an interface server that analyzes data from the server and works with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[2114] 4. AI Life Plan Simulation Engine:

[2115] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[2116] It has the ability to verbalize and quantify users' vague anxieties and requests.

[2117] 5. Expert advice generation engine:

[2118] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[2119] It receives requests from users and generates relevant advice.

[2120] 6. Emotion Engine:

[2121] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to a dialogue management computer.

[2122] Optimize the results of life plan simulations and expert advice based on emotional data.

[2123] Specific examples

[2124] Example 1: Creating a life plan for buying a home

[2125] The user enters the following information: "30 years old, annual income 5 million yen, family composition 1 spouse, 2 children, desired life event is to buy a home at age 35."

[2126] The user terminal transmits this data to the server.

[2127] The server transfers the user's input data to the dialogue management computer.

[2128] The dialogue management computer analyzes the data and sends requests to the AI ​​life plan simulation engine.

[2129] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[2130] The server transmits the generated plan to the user terminal.

[2131] The user provides feedback on the plan.

[2132] The user terminal causes the emotion engine to analyze the emotion data along with the feedback, and transmits it to the server.

[2133] From then on, the plan is dynamically updated based on user feedback and emotion data, and the final plan is finalized.

[2134] Example prompt: "User's initial life plan data: age 30, annual income 5 million yen, family composition: 1 spouse, 2 children, desired event: purchase a home at age 35."

[2135] Example 2: Educational Expense Scenario Generation

[2136] A user inputs a request to simulate a scenario regarding a child's education expenses.

[2137] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[2138] The device sends the request and emotion data to the server.

[2139] The server forwards the request to the dialogue management computer.

[2140] The dialogue management computer sends requests and emotional data to the AI ​​life plan simulation engine.

[2141] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school chosen, and identifies the appropriate scenario for the user.

[2142] The server transmits the generated scenario to the user terminal.

[2143] The user selects the most suitable educational plan based on the provided scenario.

[2144] Example prompt: "Future income change scenario: Generate a life plan taking into account income changes over the next 10 years."

[2145] This allows users to independently create specific and reliable life plans, reducing future anxiety and promoting systematic life planning. Furthermore, the emotion engine takes the user's emotional state into account, enabling more personalized and appropriate planning.

[2146] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2147] Program processing flow

[2148] Entering and submitting initial data

[2149] Step 1:

[2150] The user launches the life plan simulation app.

[2151] Specific actions: Open the simulation app on your smartphone or PC and access the app's login screen.

[2152] Input: None

[2153] Output: Login screen displayed

[2154] Step 2:

[2155] The user enters initial data such as age, income, family composition, and desired life events.

[2156] Specific actions: Enter the required information into the app's input form (e.g., "30 years old, annual income of 5 million yen, family composition of one spouse and two children, desired life event is to purchase a home at age 35") and press the submit button.

[2157] Input: Initial data (age, income, family structure, desired life events)

[2158] Output: Submit button click event

[2159] Step 3:

[2160] The user terminal receives the data entered by the user and transmits it to the server.

[2161] Specific operation: Save input data locally and send it to the server using an API.

[2162] Input: User initial data

[2163] Output: Initial data sent to the server

[2164] Analysis of initial data and generation of life plans

[2165] Step 4:

[2166] The server receives the data from the user terminal.

[2167] Specific operation: The server receives data sent from the user device via API.

[2168] Input: Initial data from the user's terminal

[2169] Output: Initial data received by the server

[2170] Step 5:

[2171] The server transfers the received data to the dialogue management computer.

[2172] Specific operation: The server analyzes the received data, converts it into an appropriate format, and transfers it to the dialogue management computer.

[2173] Input: Initial data received

[2174] Output: Data transferred to the dialogue management computer

[2175] Step 6:

[2176] The dialogue management computer analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[2177] What it does: Parses the data and sends the request in the appropriate format to the AI ​​life plan simulation engine.

[2178] Input: Received data

[2179] Output: Request data

[2180] Step 7:

[2181] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[2182] What it does: Generates an initial life plan based on input data and known algorithms.

[2183] Input: Request data

[2184] Output: Initial life plan

[2185] Step 8:

[2186] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[2187] Specific operation: The generated life plan is sent to the user's device and the results are displayed on the app screen.

[2188] Input: Initial Life Plan

[2189] Output: Initial life plan sent to user device

[2190] Enter feedback and update your plan

[2191] Step 9:

[2192] The user enters feedback on the plan (requests for corrections, additions, etc.).

[2193] Specific actions: Enter desired changes or additional requests in the feedback field and submit.

[2194] Input: Feedback data

[2195] Output: Submit button click event

[2196] Step 10:

[2197] The user terminal receives the feedback data and causes the emotion engine to analyze the emotion data.

[2198] Specific behavior: Passes feedback data to the emotion engine and analyzes the user's emotions.

[2199] Input: Feedback data

[2200] Output: Emotion data

[2201] Step 11:

[2202] The terminal transmits the feedback together with the emotion data to the server.

[2203] Specific operation: Sends the analyzed data to the server.

[2204] Input: Feedback data, emotion data

[2205] Output: Feedback and emotion data sent to the server

[2206] Step 12:

[2207] The server transfers the feedback and emotion data to the dialogue management computer.

[2208] Specific operation: The server sends feedback and emotion data to the dialogue management computer.

[2209] Input: Feedback data, emotion data

[2210] Output: Feedback and emotion data transmitted to the dialogue management computer

[2211] Step 13:

[2212] The dialogue management computer analyzes the feedback and emotional data and sends update requests to the AI ​​life plan simulation engine.

[2213] Specific operation: Analyzes the feedback content and emotional data, and sends an update request to the AI ​​life plan simulation engine.

[2214] Input: Feedback data, emotion data

[2215] Output: Update request

[2216] Step 14:

[2217] The AI ​​life plan simulation engine updates the plan to reflect the new information and sends it back to the server.

[2218] What it does: Update your life plan with new data.

[2219] Input: Update request

[2220] Output: Updated Life Plan

[2221] Step 15:

[2222] The server transmits the updated life plan to the user terminal and displays it again.

[2223] Specific operation: The updated plan is sent to the user's device and displayed again on the app screen.

[2224] Enter: Updated Life Plan

[2225] Output: Updated life plan sent to user device

[2226] Requesting and Providing Expert Advice

[2227] Step 16:

[2228] A user enters a request for expert advice in a particular area (e.g., mortgage, insurance, etc.).

[2229] What you do: Select the area of ​​advice you need, enter details, and submit your request.

[2230] Input: Advice request

[2231] Output: Submit button click event

[2232] Step 17:

[2233] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[2234] Specific operation: Receives request data and requests the emotion engine to analyze it.

[2235] Input: Advice request

[2236] Output: Emotion data

[2237] Step 18:

[2238] The terminal transmits the emotion data together with the request to the server.

[2239] Specific behavior: Sends request and emotion data to the server.

[2240] Input: Advice request, emotion data

[2241] Output: Advice request and emotion data sent to the server

[2242] Step 19:

[2243] The server sends the request and the emotion data to the expert advice generation engine.

[2244] Specific operation: The server sends the request content and emotion data to the expert advice generation engine.

[2245] Input: Advice request, emotion data

[2246] Output: Expert Advice Request

[2247] Step 20:

[2248] An expert advice generation engine generates advice based on the emotion data and sends it back to the server.

[2249] Specific behavior: Generate optimal advice taking into account emotional data.

[2250] Input: Advice request, emotion data

[2251] Output: Expert advice

[2252] Step 21:

[2253] The server transmits the generated advice to the user terminal and displays it to the user.

[2254] Specific operation: The generated advice is sent to the user's device and displayed on the app screen.

[2255] Enter: Expert Advice

[2256] Output: Expert advice sent to the user's device

[2257] Generating future scenarios

[2258] Step 22:

[2259] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[2260] Specific Action: Enter details of the future scenario and submit a simulation request.

[2261] Input: Simulation request

[2262] Output: Submit button click event

[2263] Step 23:

[2264] The user terminal receives the request and causes the emotion engine to analyze the emotion data.

[2265] Specific operation: Receives request data and requests the emotion engine to analyze it.

[2266] Input: Simulation request

[2267] Output: Emotion data

[2268] Step 24:

[2269] The terminal transmits the emotion data together with the request to the server.

[2270] Specific behavior: Sends request and emotion data to the server.

[2271] Input: Simulation request, emotion data

[2272] Output: Simulation request and emotion data sent to the server

[2273] Step 25:

[2274] The server sends the request and emotion data to the dialogue management computer.

[2275] Specific operation: The server sends the request content and emotion data to the dialogue management computer.

[2276] Input: Simulation request, emotion data

[2277] Output: Request and emotion data transmitted to the dialogue management computer

[2278] Step 26:

[2279] The dialogue management computer sends requests and emotional data to the AI ​​life plan simulation engine.

[2280] Specific operation: Sends a request and emotion data and requests scenario generation.

[2281] Input: Request, emotion data

[2282] Output: Simulation request

[2283] Step 27:

[2284] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[2285] Specific operation: Generate multiple future scenarios based on various data and identify scenarios that are advantageous or require caution.

[2286] Input: Simulation request

[2287] Output: Future scenario

[2288] Step 28:

[2289] The server transmits the generated scenario to the user terminal and displays it to the user.

[2290] Specific operation: The generated scenario is sent to the user's device and displayed on the app screen.

[2291] Input: Future scenario

[2292] Output: Future scenario sent to the user device

[2293] (Application example 2)

[2294] 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."

[2295] Currently, many users struggle with managing income and expenses and simulating future scenarios when creating their future life plans. In particular, the lack of professional advice and the ability to adjust plans to accommodate fluctuations in income and expenses makes it difficult to create accurate and effective life plans. Furthermore, the lack of consideration for user emotions in planning makes it difficult to provide plans that are satisfactory. A system that solves these problems is needed.

[2296] 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 a user terminal to input initial data related to a life plan and transmit the data to the server; means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine; means for the AI ​​life plan simulation engine to generate an initial life plan simulation and return it to the server; means for the server to transmit the generated initial life plan to the user terminal; means for the user to input feedback on the life plan and transmit the feedback to the server; means for the server to transmit the received feedback to the AI ​​life plan simulation engine to update the plan; means for the user terminal to input data for managing daily income and expenses and transmit the data to the server; means for the server to analyze the received income and expense data and provide the user with saving tips and investment suggestions; and means for the emotion engine to analyze the user's emotion data and transmit the data to the server to reflect the results. This allows the user to update their life plan as needed to reflect fluctuations in income and expenses and receive expert advice. Furthermore, users can receive personalized feedback that takes emotional data into account, which is expected to help create a more satisfying life plan.

[2297] A "user terminal" is a device that allows a user to input data related to life plans and income / expense management and transmit it to the server.

[2298] The "server" is a central management system that analyzes data received from users and executes processing in cooperation with other engines, such as the AI ​​life plan simulation engine.

[2299] The "AI Life Plan Simulation Engine" is an artificial intelligence module that analyzes the initial data and feedback provided by users to generate and update life plans.

[2300] "Feedback" is information such as desired modifications or additions that the user inputs to the generated life plan.

[2301] The "emotion engine" is a software module that recognizes emotions from the user's facial expressions, voice, and text input, analyzes the emotional data, and reflects it in simulation results and feedback.

[2302] An "expert advice generation engine" is an artificial intelligence module that generates appropriate advice for users based on specialized knowledge in a particular field.

[2303] "Income" refers to financial resources such as monetary income or salary that a user receives within a certain period of time.

[2304] "Expenses" refers to all payments made by a user within a certain period of time, including living expenses and money spent on hobbies.

[2305] "Savings Tips" are suggestions and advice to help users reduce wasteful spending and manage their money efficiently.

[2306] An "investment proposal" is a proposal for specific investment destinations and methods that will enable users to effectively manage their funds and earn profits.

[2307] A "prompt" is text data input to a generative AI model, and is an instruction that enables the model to generate appropriate answers or advice.

[2308] The present invention relates to a system that allows users to independently create and manage their own life plans. This system is composed of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, an expert advice generation engine, and an emotion engine. Specific embodiments for implementing the present invention are described below.

[2309] System Overview

[2310] 1. User Device:

[2311] Through the interface, users input initial data about their life plan (age, income, family composition, desired life events, etc.).

[2312] You can also enter data to manage your daily income and expenses.

[2313] The user terminal transmits this data to the server.

[2314] It has a built-in emotion engine that recognizes emotions from the user's facial expressions, voice, text input, etc.

[2315] 2. Server:

[2316] The server is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management server and various engines.

[2317] Initial data, feedback, and emotional data are transferred to the dialogue management server, and the analysis results are sent to the user's terminal.

[2318] It analyzes income and expenditure data and provides users with savings tips and investment suggestions.

[2319] 3. Dialogue Management Server:

[2320] It is an interface server that receives and analyzes data from users and links with the AI ​​life plan simulation engine, expert advice generation engine, and emotion engine.

[2321] 4. AI Life Plan Simulation Engine:

[2322] This is an AI module that generates and updates life plan simulations based on the user's initial data, feedback, and emotional data.

[2323] Generate an initial life plan and update the plan based on daily income and expenditure.

[2324] It is built using TensorFlow.

[2325] 5. Expert advice generation engine:

[2326] It is an AI module with expertise in specific fields such as finance, insurance, and real estate.

[2327] Using OpenAI GPT-3, it generates relevant expert advice based on user requests.

[2328] 6. Emotion Engine:

[2329] The system recognizes emotions from the user's facial expressions, voice, text input, etc., and provides the emotion data to the dialogue management server.

[2330] It is built using the Microsoft Azure Emotion Recognition API.

[2331] Optimize the results of life plan simulations and expert advice based on emotional data.

[2332] Specific example explanation

[2333] Example 1: Creating a life plan for buying a home

[2334] When a user is planning to purchase a home, they use the system in the following steps: The user launches the life plan simulation app and enters information such as age, income, family composition, budget, loan amount, and desired area. The user's device sends the entered information to the server, which then forwards it to the dialogue management server. The dialogue management server sends the received data to the AI ​​life plan simulation engine, which generates an initial life plan. The user then enters feedback on the plan and sends emotional data along with the feedback to the server. The server analyzes this data and dynamically updates the plan.

[2335] Example 2: Educational Expenses Scenario Generation

[2336] This is the procedure when a user wants to simulate a scenario regarding their child's education expenses. The user inputs a request and the request is sent to the server on the user's device. The server forwards the request to the dialogue management server, which then sends it to the AI ​​life plan simulation engine. The engine generates scenarios based on changes in education expenses and the school to which the user will advance, and the user can then select the optimal education plan based on these scenarios.

[2337] Prompt Sentence Examples

[2338] For example, if you are 35 years old, have a family of four, earn 7 million yen a year, and your desired life events are buying a house and educating your children, the user would use the following prompt:

[2339] User data: {"age": 35, "income": 7000000, "family": {"members": 4}, "events": ["buy_house", "child_education"]}. Provide financial advice.

[2340] By inputting this prompt into a generative AI model, expert advice can be generated, providing the user with an appropriate life plan.

[2341] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2342] Step 1:

[2343] The user's terminal inputs initial data related to their life plan and sends that data to the server. Specifically, the user enters data about their age, income, family structure, and desired life events (e.g., buying a home, children's education, etc.) into an input form. Once this initial data is sent, it is received by the server.

[2344] Step 2:

[2345] The server analyzes the received initial data and transfers it to the dialogue management server. The server converts the initial data into JSON format and sends it to the dialogue management server. This data specifically includes the user's age, income, desired events, etc.

[2346] Step 3:

[2347] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine. The dialogue management server formats the data appropriately and constructs and sends a request to the AI ​​life plan simulation engine.

[2348] Step 4:

[2349] The AI ​​life plan simulation engine generates an initial life plan and sends it back to the server. The AI ​​life plan simulation engine uses TensorFlow to analyze and generate an initial life plan based on the user's data. The results are sent back to the server.

[2350] Step 5:

[2351] The server transmits the generated initial life plan to the user terminal. The server receives the initial life plan returned from the dialogue management server and transmits it to the user terminal. The user terminal displays the received life plan on its screen.

[2352] Step 6:

[2353] The user inputs feedback about the life plan and sends the feedback to the server. The user checks the life plan and inputs any necessary corrections or additions as feedback. This feedback is sent from the user terminal to the server.

[2354] Step 7:

[2355] The server sends the received feedback to the AI ​​life plan simulation engine to update the plan. The server analyzes the feedback data and sends it to the AI ​​life plan simulation engine. The engine updates the plan based on it and sends the result back to the server.

[2356] Step 8:

[2357] The user's terminal inputs data for managing daily income and expenses and transmits the data to the server. The user inputs details of daily income and expenses into the application, and the data is transmitted to the server.

[2358] Step 9:

[2359] The server analyzes the received income and expenditure data and provides the user with savings tips and investment suggestions. Based on this data, the server uses a generative AI model such as OpenAI GPT-3 to generate prompts and provide appropriate savings and investment advice. This advice is then sent to the user's device.

[2360] Step 10:

[2361] The emotion engine analyzes the user's emotional data and sends that data to the server, which reflects the results. The emotion engine recognizes emotions from the user's facial expressions, voice, text input, etc. and sends that emotional data to the server. The server adjusts the life plan and proposal content based on this data.

[2362] This process allows users to create and manage their life plans in real time and with a personalized interface. For example, if a 35-year-old user with an annual income of 7 million yen plans to buy a home, specific advice and updates to the plan will be automatically provided based on that plan. The generative AI model also provides advice using prompts such as:

[2363] User data: {"age": 35, "income": 7000000, "family": {"members": 4}, "events": ["buy_house", "child_education"]}. Provide financial advice.

[2364] 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.

[2365] 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.

[2366] 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.

[2367] [Fourth embodiment]

[2368] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2369] 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.

[2370] 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).

[2371] 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.

[2372] 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.

[2373] 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).

[2374] 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. 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.

[2375] 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.

[2376] 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.

[2377] 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.

[2378] 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.

[2379] 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.

[2380] 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."

[2381] This invention relates to a system that enables users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[2382] System Overview

[2383] 1. User terminal: The user inputs initial data about their life plan (age, income, family structure, desired life events, etc.) through an interface. It is also an input device for providing feedback on the generated life plan and requesting specific advice.

[2384] 2. Server: A central system that analyzes data received from user devices and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user devices.

[2385] 3. Dialogue Management Server: This is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue.

[2386] 4. AI Life Plan Simulation Engine: This is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[2387] 5. Expert Advice Generation Engine: An AI module with expertise in specific fields such as finance, insurance, real estate, etc. It receives requests from users and generates relevant advice.

[2388] Program processing

[2389] Entering and submitting initial data

[2390] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[2391] The terminal receives the data entered by the user and transmits it to the server.

[2392] Analysis of initial data and generation of initial life plan

[2393] The server analyzes the received user initial data and transfers it to the dialogue management server.

[2394] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[2395] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[2396] The server transmits the generated initial life plan to the user terminal and displays it to the user.

[2397] Enter feedback and update your plan

[2398] The user inputs feedback (e.g., requests for corrections or additions) on the presented life plan.

[2399] The terminal receives the user's feedback and transmits it to the server.

[2400] The server forwards the feedback to the interaction management server.

[2401] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[2402] The AI ​​life plan simulation engine updates the plan based on the new feedback and sends it back to the server.

[2403] The server transmits the updated life plan to the user terminal and displays it again.

[2404] Providing expert advice

[2405] A user enters a request for advice in a particular area (eg, mortgage, insurance).

[2406] The terminal receives the request and sends it to the server.

[2407] The server sends the request to the expert advice generation engine.

[2408] The expert advice generation engine generates expert advice based on the user's request and sends it back to the server.

[2409] The server transmits the generated advice to the user terminal and displays it to the user.

[2410] Generating future scenarios

[2411] A user inputs a request to simulate a future scenario.

[2412] The terminal receives the request and sends it to the server.

[2413] The server sends the request to the AI ​​life plan simulation engine.

[2414] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable for the user and those that require caution.

[2415] The server transmits the generated scenario to the user terminal and displays it to the user.

[2416] Specific examples

[2417] Example 1: Creating a life plan for buying a home

[2418] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[2419] The terminal transmits the input information to the server.

[2420] The server forwards the received information to the dialogue management server.

[2421] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[2422] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[2423] The server transmits the generated plan to the user terminal.

[2424] The user enters feedback on the plan and submits it again.

[2425] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[2426] Example 2: Educational Expenses Scenario Generation

[2427] A user enters a request to simulate a scenario regarding their child's education expenses.

[2428] The terminal sends a request to the server.

[2429] The server sends the request to the AI ​​life plan simulation engine.

[2430] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[2431] The server transmits the generated scenario to the user terminal.

[2432] The user selects the most suitable training plan based on multiple scenarios.

[2433] This allows users to independently create specific and reliable life plans, reduce anxiety about the future, and advance systematic life planning.

[2434] The processing flow will be explained below.

[2435] Step 1:

[2436] The user launches the life plan simulation app and enters personal information (age, income, family composition, desired life events, etc.).

[2437] Step 2:

[2438] The terminal receives the data entered by the user and transmits the data to the server.

[2439] Step 3:

[2440] The server transfers the received data to the dialogue management server.

[2441] Step 4:

[2442] The dialogue management server analyzes the received data and sends a request to the AI ​​life plan simulation engine.

[2443] Step 5:

[2444] The AI ​​life plan simulation engine generates an initial life plan simulation based on the user's initial data.

[2445] Step 6:

[2446] The server receives the generated initial life plan and transmits it to the user terminal.

[2447] Step 7:

[2448] The user checks the life plan they received and enters feedback, corrections, and additional requests.

[2449] Step 8:

[2450] The terminal receives the user's feedback and transmits the feedback to the server.

[2451] Step 9:

[2452] The server forwards the received feedback to the interaction management server.

[2453] Step 10:

[2454] The dialogue management server analyzes the feedback and sends update requests to the AI ​​life plan simulation engine.

[2455] Step 11:

[2456] The AI ​​life plan simulation engine updates the plan to reflect the new feedback and sends it back to the server.

[2457] Step 12:

[2458] The server transmits the updated life plan to the user terminal.

[2459] Step 13:

[2460] A user enters a request for advice in a particular area (e.g., mortgage, insurance).

[2461] Step 14:

[2462] The terminal receives the request and sends it to the server.

[2463] Step 15:

[2464] The server forwards the received request to the expert advice generation engine.

[2465] Step 16:

[2466] The expert advice generation engine generates expert advice based on the user's request and returns the results to the server.

[2467] Step 17:

[2468] The server transmits the generated advice to the user terminal.

[2469] Step 18:

[2470] A user inputs a request to simulate a future scenario (e.g., income fluctuations, changes in economic conditions).

[2471] Step 19:

[2472] The terminal receives the simulation request and sends it to the server.

[2473] Step 20:

[2474] The server sends the request to the AI ​​life plan simulation engine.

[2475] Step 21:

[2476] The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are advantageous to the user and those that require caution.

[2477] Step 22:

[2478] The server transmits the generated scenario to the user terminal.

[2479] Step 23:

[2480] The user reviews the provided scenarios, selects the most suitable life plan, and enters that selection into the system.

[2481] Step 24:

[2482] The terminal receives the user's final selection and transmits it to the server.

[2483] Step 25:

[2484] The server sends the final selection to the dialogue management server, requesting the generation of a final life plan.

[2485] Step 26:

[2486] The AI ​​life plan simulation engine generates the final life plan and sends it back to the server.

[2487] Step 27:

[2488] The server transmits the final life plan to the user terminal and displays it to the user.

[2489] Through these steps, we have created a system that allows users to dynamically and interactively create and update their life plans and receive expert advice to form the optimal life plan.

[2490] Example 1

[2491] 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."

[2492] Conventional life plan creation systems have the problem that it is difficult for users to obtain appropriate advice when they do not have specialized knowledge or when they have limited access to advice, and they are unable to fully meet the needs of users. Another problem is that simulating and updating a life plan is time-consuming and tedious. The purpose of this invention is to solve these problems and enable users to effectively create and manage their life plans on their own.

[2493] 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.

[2494] In this invention, the server includes: means for a user terminal to input initial data regarding a life plan and transmit the data to the server; means for the server to analyze the received initial data and transmit a request to the AI ​​life plan simulation engine via the dialogue management server; means for the AI ​​life plan simulation engine to generate an initial life plan simulation and transmit it back to the server; means for the server to transmit the generated initial life plan to the user terminal; means for the user to input feedback regarding the life plan and transmit the feedback to the server; and means for transmitting the feedback received by the server to the AI ​​life plan simulation engine via the dialogue management server to update the plan. This enables the AI ​​to dynamically generate and update a life plan and obtain expert advice based on the initial data and feedback input by the user.

[2495] A "user terminal" is a device through which a user inputs data related to their life plan and communicates with the server.

[2496] The "server" is a central system that analyzes data received from user terminals and manages cooperation with the dialogue management server and various engines.

[2497] The "dialogue management server" is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine.

[2498] The "AI Life Plan Simulation Engine" is an AI module that generates and updates life plan simulations based on the user's initial data and feedback.

[2499] An "expert advice generation engine" is an AI module that has expertise in a specific field and generates expert advice based on requests from users.

[2500] "Initial data" refers to basic information that a user inputs to create a life plan, and includes age, income, family structure, desired life events, and the like.

[2501] "Feedback" refers to opinions and requests, such as corrections and additions, provided by the user regarding the generated life plan.

[2502] A "request" is input data that a user inputs to the server, requesting specific advice or a simulation of a future scenario.

[2503] "Simulation" refers to the process of predicting and generating future life plans and multiple future scenarios carried out by an AI life plan simulation engine.

[2504] This invention relates to a system that allows users to independently create and manage their own life plans. This system consists of the following components: a user terminal, a server, a dialogue management server, an AI life plan simulation engine, and an expert advice generation engine.

[2505] System Overview

[2506] User terminal

[2507] The user terminal is a device where a user inputs initial data about their life plan and transmits that data to a server. The user terminal has an interface through which the user inputs initial data such as age, income, family composition, and desired life events through an application. The user terminal is also an input device for providing feedback on the generated life plan and requesting specific advice.

[2508] server

[2509] The server is a central system that analyzes data received from user terminals and manages collaboration with the dialogue management server and various engines. The server appropriately transfers initial data and feedback to the dialogue management server and sends responses to the user terminal. The server also collaborates with the expert advice generation engine to provide expert advice.

[2510] Dialogue Management Server

[2511] The dialogue management server is an interface server that receives and analyzes data from users and connects with the AI ​​life plan simulation engine and expert advice generation engine. It is responsible for managing the overall flow of the dialogue and sends the initial data and feedback received from users to each engine.

[2512] AI life plan simulation engine

[2513] The AI ​​life plan simulation engine is an AI module that generates and updates life plan simulations based on the user's initial data and feedback. This engine has the ability to verbalize and quantify the user's vague anxieties and desires.

[2514] Expert Advice Generation Engine

[2515] An expert advice generation engine is an AI module with specialized knowledge in a specific field, such as finance, insurance, or real estate, that receives requests from users and generates relevant advice.

[2516] Specific examples

[2517] Example 1: Creating a life plan for buying a home

[2518] A user plans to purchase a home and enters information such as budget, loan amount, and desired area into a life plan simulation app.

[2519] The terminal transmits the input information to the server.

[2520] The server forwards the received information to the dialogue management server.

[2521] The dialogue management server transmits the received data to the AI ​​life plan simulation engine.

[2522] The AI ​​life plan simulation engine generates an initial life plan based on the provided information and sends it back to the server.

[2523] The server transmits the generated plan to the user terminal.

[2524] The user enters feedback on the plan and submits it again.

[2525] Thereafter, the plan is dynamically updated based on user feedback, and the final plan is finalized.

[2526] Example 2: Educational Expenses Scenario Generation

[2527] A user enters a request to simulate a scenario regarding their child's education expenses.

[2528] The terminal sends a request to the server.

[2529] The server sends the request to the AI ​​life plan simulation engine.

[2530] The AI ​​life plan simulation engine generates scenarios based on changes in educational expenses and the type of school one chooses to attend, and sends them back to the server.

[2531] The server transmits the generated scenario to the user terminal.

[2532] The user selects the most suitable training plan based on multiple scenarios.

[2533] Prompt Sentence Examples

[2534] 1. "Generate a life plan based on your home buying budget and desired area."

[2535] 2. "Simulate several scenarios for your child's education expenses."

[2536] This system allows users to independently create specific and reliable life plans, reducing anxiety about the future and enabling them to plan their lives in a planned manner.

[2537] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2538] Step 1: Enter initial data

[2539] The user launches the life plan simulation app and enters initial data such as age, income, family composition, and desired life events.

[2540] Input: Any initial data that a user enters into an app form.

[2541] Output: The input data is compiled as JSON format data.

[2542] What happens: Data is collected when a user fills out a form on the app and clicks the "Submit" button.

[2543] Step 2: Sending initial data

[2544] The terminal receives the initial data entered by the user and transmits it to the server.

[2545] Input: Initial data in JSON format.

[2546] Output: The initial data sent to the server.

[2547] Specific operation: The terminal's data transmission module sends the initial data to the server using an HTTPS request.

[2548] Step 3: Analyze the initial data

[2549] The server analyzes the received initial data and forwards it to the dialogue management server.

[2550] Input: The initial data received by the server in JSON format.

[2551] Output: The parsed data is transferred to the dialogue management server.

[2552] Specific operation: The server analyzes the initial data using a data analysis algorithm, and then reformats and transmits the analysis results to the dialogue management server.

[2553] Step 4: Submitting a simulation request

[2554] The dialogue management server analyzes the initial data and sends a request to the AI ​​life plan simulation engine.

[2555] Input: Analysis results based on initial data.

[2556] Output: The request sent to the AI ​​life plan simulation engine.

[2557] Specific operation: The dialogue management server formats the analysis results into a format that the AI ​​engine can understand and submits a request via API.

[2558] Step 5: Generate an initial life plan

[2559] The AI ​​life plan simulation engine generates an initial life plan based on the initial data and sends it back to the server.

[2560] Input: The request data received from the server.

[2561] Output: Generated initial life plan.

[2562] How it works: The AI ​​engine uses past data and statistical models to generate a life plan that best suits the user's initial data.

[2563] Step 6: Displaying your initial life plan

[2564] The server transmits the generated initial life plan to the user terminal.

[2565] Input: Initial life plan return...

Claims

1. A means for a user terminal to input initial data regarding a life plan and transmit the data to a server; A means for the server to analyze the received initial data and send a request to the AI ​​life plan simulation engine; a means for the AI ​​life plan simulation engine to generate an initial life plan simulation and return it to the server; A means for the server to transmit the generated initial life plan to a user terminal; a means for a user to input feedback on the life plan and transmit the feedback to a server; a means for transmitting the received feedback from the server to the AI ​​life plan simulation engine to update the plan; A system including:

2. a means for inputting a request for advice on a specific field at a user terminal and transmitting the request to a server; means for transmitting the received request by the server to an expert advice generation engine; means for the expert advice generation engine to generate expert advice based on the user's request and return it to the server; A means for the server to transmit the generated advice to a user terminal; The system of claim 1 , comprising:

3. a means for a user terminal to input a request for simulating a future scenario and transmit the request to a server; A means for transmitting the received request by the server to the AI ​​life plan simulation engine; The AI ​​life plan simulation engine generates multiple future scenarios and identifies scenarios that are favorable to the user and those that require caution; a means for transmitting the generated scenario to a user terminal by the server; A means for users to make decisions based on AI suggestions and input the results into the app. The system of claim 1 , comprising:

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