system

Abstract

Provide a system. A method for collecting income and expenditure information; a means for using a generative artificial intelligence to create a life plan based on the income and expenditure information; A means for predicting future economic situations based on the life plan created by the generative artificial intelligence; a means for proposing a specific action plan based on the predicted economic situation; A system including:

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, it is important to efficiently manage income and expenses and create a life plan that predicts future economic conditions. However, many people do not understand how to create a life plan, and because it is time-consuming, many people have never created one. As a result, they end up feeling uncertain about the future and financial anxiety. The purpose of this invention is to solve these problems and support users in easily and accurately creating a life plan, allowing them to live their ideal life with peace of mind. [Means for solving the problem]

[0005] The present invention provides a system including a means for collecting income and expenditure information, a means for using generative artificial intelligence to create a life plan based on the income and expenditure information, a means for predicting a future economic situation based on the life plan created by the generative artificial intelligence, and a means for proposing a specific action plan based on the predicted economic situation. The system may further include a means for collecting transaction data in cooperation with an electronic payment service and bank account information, and a means for collecting user feedback and optimizing the life plan, thereby enabling a user to realize their ideal life plan while receiving actionable suggestions.

[0006] Ok, below I have created definitions for some important words.

[0007] "Income" refers to the monetary benefits gained from the user's work, investments, etc.

[0008] "Expenses" refers to the total amount of money consumed by the user for living expenses and various purchasing activities.

[0009] "Information gathering means" refers to methods and devices for obtaining data relating to a user's income and expenses.

[0010] "Generative AI" is an AI technology that uses big data and machine learning algorithms to analyze user data and generate future predictions and suggestions.

[0011] A "life plan" is a long-term economic plan created based on the user's future goals and plans, taking into account the balance between income and expenditure.

[0012] An "economic forecasting tool" is a method or device that estimates future fluctuations in income and expenditure based on collected data.

[0013] The "means for proposing an action plan" is a method or device that provides a user with specific guidelines for action based on the predicted economic situation.

[0014] "Electronic payment services" are means of non-cash transactions conducted over the internet or mobile devices.

[0015] "Bank account information" refers to information relating to the user's deposits and transaction records at financial institutions.

[0016] A "means for collecting feedback" is a method or device for obtaining responses and opinions from users and incorporating them into the system.

[0017] "Optimization means" are methods or devices for improving life plans and proposals based on collected feedback. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

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

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

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

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and then proposes specific action plans to users.

[0040] System Overview

[0041] This system consists of a "terminal" that collects data on income and expenses, a "server" that analyzes the collected data and creates a life plan, and a "server" that receives feedback from users and performs optimization.

[0042] Program processing

[0043] 1. Data Collection

[0044] Users create an account and link their electronic payment service and bank account information to the system.

[0045] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[0046] 2. Data Analysis

[0047] The server stores the received income and expenditure data in a database and analyzes it using generative artificial intelligence.

[0048] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan.

[0049] 3. Predictions and Recommendations

[0050] The server predicts future economic conditions based on the analysis results of generative artificial intelligence.

[0051] The server generates a specific action plan based on the prediction results and transmits it to the terminal.

[0052] The device will display the suggestions to the user via push notifications or in-app messages.

[0053] 4. Feedback and optimization

[0054] The user reviews the suggestions and enters any necessary changes or feedback into the device.

[0055] The terminal sends feedback information to the server.

[0056] The server optimizes the life plan based on the feedback and generates and sends new proposals.

[0057] Specific examples

[0058] Example: Goal to buy a house in 3 years

[0059] 1. A user downloads the app and creates an account.

[0060] 2. The user connects their electronic payment service and bank account information.

[0061] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0062] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0063] 5. The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[0064] 6. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[0065] 7. The device notifies the user of the proposal and presents a feasible plan.

[0066] 8. The user reviews the proposal and makes adjustments as needed.

[0067] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0068] In this way, users can manage their income and expenses through the system and implement realistic action plans to achieve their future goals. This system reduces users' financial worries and allows them to plan their lives with greater peace of mind.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] A user downloads the app and creates an account.

[0072] The user authenticates and configures the settings to link electronic payment services and bank account information.

[0073] Step 2:

[0074] The terminal periodically acquires transaction data from the linked electronic payment service and bank account.

[0075] The terminal encrypts and stores the acquired transaction data and periodically transmits it to the server.

[0076] Step 3:

[0077] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[0078] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[0079] Step 4:

[0080] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[0081] The server uses past data and big data to predict future economic conditions.

[0082] Step 5:

[0083] The server generates a specific action plan based on the prediction results.

[0084] The server transmits the generated action plan to the terminal.

[0085] Step 6:

[0086] The device will display the suggestions to the user via push notifications or in-app messages.

[0087] The user reviews the proposal and enters any necessary changes or feedback.

[0088] Step 7:

[0089] The terminal transmits feedback information from the user to the server.

[0090] The server reanalyzes and optimizes your life plan based on the collected feedback.

[0091] Step 8:

[0092] The server generates an optimized life plan and new proposals.

[0093] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[0094] In this way, a system is created that continuously collects and analyzes income and expenditure information, and provides users with feedback and suggestions to help them achieve their goals.

[0095] Example 1

[0096] 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."

[0097] In recent years, it has become increasingly important to effectively utilize personal income and expenditure information to specifically plan future life plans. However, current systems do not effectively coordinate data collection, encryption, analysis, and recommendations, and are insufficiently optimized to reflect user feedback. Ensuring safety and efficiency are also issues. To address these issues, a system is needed that efficiently collects and securely transmits income and expenditure data, creates high-quality life plans using generative AI models, and predicts users' future financial situations.

[0098] 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.

[0099] In this invention, the server includes: means for a user to create an account and link with product and service providers; means for periodically acquiring income and expenditure measurement data based on link information via a terminal, encrypting the data, and transmitting the encrypted data to the server; means for the server to analyze the income and expenditure data using a generative AI model and create a life plan; means for predicting future economic conditions based on the created life plan; means for generating a specific action plan based on the prediction results and proposing it to the user via the terminal; and means for collecting user feedback and optimizing the life plan. This makes it possible to analyze the user's income and expenditure in detail, accurately predict future economic conditions, and provide a realistic and specific action plan.

[0100] "User" refers to an individual who uses the system to input income and expense information and receive a financial forecast and suggested action plan.

[0101] "Terminal" refers to a device used by a user that acquires income and expenditure transaction data, encrypts it, and transmits it to a server.

[0102] "Server" refers to the computer system that stores collected income and expenditure data, analyzes the data using generative AI models, and creates and provides life plans.

[0103] "Income and Expense Measure Data" means data that includes transaction information related to a user's income and expenses.

[0104] "Linked information" refers to information related to a user's income and expenditures that is shared with electronic payment services and financial institutions.

[0105] "Generative AI model" refers to an artificial intelligence model that analyzes income and expenditure data to create and optimize life plans.

[0106] "Life Plan" refers to future financial plans and goals created based on a user's income and expenditure data.

[0107] An "action plan" refers to a plan based on the user's life plan that includes proposals for specific income and expenditure management methods, investment plans, etc.

[0108] "Feedback" refers to opinions and requests for corrections made by users regarding the proposed action plan.

[0109] "Encryption" refers to the process used to protect collected income and expense data from being read by third parties.

[0110] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using a generative AI model, predicts future economic conditions, and then proposes specific action plans to users.

[0111] System Overview

[0112] The system consists of three main components:

[0113] 1. Terminal: A device used by a user that collects income and expenditure transaction data, encrypts it, and sends it to a server.

[0114] 2. Server: Analyzes the collected income and expenditure data and creates a life plan using a generative AI model. It also predicts future economic situations and generates specific action plans.

[0115] 3. User: A user of the system who creates an account, enters income and expense information, and implements the proposed action plan.

[0116] Hardware and Software Configuration

[0117] 1. Devices: Use mobile devices such as smartphones and tablets. These devices require API access to collect income and expenditure data. Specifically, use APIs provided by major electronic payment services and financial institutions.

[0118] 2. Server: A high-performance computer system that requires software to run the generative AI model and a database management system (e.g., MySQL (registered trademark) or PostgreSQL). The generative AI model uses a deep learning framework such as TENSORFLOW (registered trademark) or PyTorch.

[0119] Specific examples

[0120] As an example, we will show how the system works when you set a goal of buying a house in three years.

[0121] 1. A user downloads the system app and creates an account.

[0122] 2. The user connects their electronic payment service and bank account information.

[0123] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0124] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0125] 5. The server analyzes the data received and creates an income and expenditure plan to save 30 million yen in three years.

[0126] 6. The server generates a proposal for the amount of savings needed each month and items of expenses that can be reduced (for example, reducing monthly eating out expenses by 20,000 yen).

[0127] 7. The device notifies the user of the proposal and presents a feasible plan.

[0128] 8. The user reviews the proposal and makes adjustments as needed.

[0129] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0130] Through this collaboration, the system will efficiently manage users' income and expenses, accurately predict their future financial situation, and provide realistic action plans to help them achieve their life plans.

[0131] Prompt Sentence Examples

[0132] "Based on your income and expenditure data, generate a concrete action plan to purchase a 30 million yen house in three years."

[0133] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0134] Step 1:

[0135] The user creates an account and links their electronic payment service and bank account information to the system. The user downloads the system's app and creates an account by entering basic information such as name, email address, and password. Next, they link their electronic payment service and bank account information to the system and allow API access. Input: Basic information, linked information. Output: Notification of account creation completion, registration of linked information.

[0136] Step 2:

[0137] Based on the linked information, the device periodically obtains income and expenditure transaction data, encrypts it, and sends it to the server. The device periodically (e.g. daily or weekly) accesses the API of financial institutions and electronic payment services to obtain the latest income and expenditure transaction data. The obtained data is encrypted using an encryption algorithm such as AES256. Input: Linkage information, transaction data. Output: Encrypted transaction data.

[0138] Step 3:

[0139] The server stores the received income and expenditure data in a database and analyzes it using a generative AI model. The server receives encrypted transaction data from the terminal and stores it in a database. The generative AI model is then used to analyze the data and understand the user's income and expenditure patterns. Input: Encrypted transaction data. Output: Analysis results, user's income and expenditure patterns.

[0140] Step 4:

[0141] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan. The server evaluates the user's income and expenditure patterns from the analysis results and uses a generative AI model to create an optimal life plan. For example, a specific plan can be created based on the user's goals for the future (e.g., buying a house, saving for their children's education). Input: Analysis results, user goals. Output: Life plan.

[0142] Step 5:

[0143] The server uses the generated AI model to predict future economic conditions based on the life plan. The server predicts future economic conditions based on the user's income, expenditures, and savings plans described in the life plan. For example, it also takes into account income growth cycles and the risk of unexpected expenditures. Input: Life plan. Output: Future economic situation prediction results.

[0144] Step 6:

[0145] The server generates a specific action plan based on the prediction results and sends it to the device. The server generates specific actions that the user should take (e.g., monthly savings amount, which items to cut spending on) based on the future economic situation prediction results and sends it to the device. Input: Future economic situation prediction results. Output: Action plan.

[0146] Step 7:

[0147] The device notifies the user of the proposed action plan and presents an actionable plan. The device displays the action plan received from the server to the user and informs them of the proposed action plan via push notification or in-app message. The user reviews the displayed plan and considers what can be done. Input: Action plan. Output: Notification to user, presentation of action plan.

[0148] Step 8:

[0149] The user reviews the proposal and inputs any necessary changes or feedback into the device. The user reviews the proposed action plan, makes any necessary changes to suit their own living situation, and inputs feedback into the device. Input: Feedback, changes. Output: Feedback information.

[0150] Step 9:

[0151] The device sends feedback information to the server, which then optimizes the life plan based on this. The device sends feedback information received from the user to the server, which updates the generative AI model to optimize the life plan. This generates new proposals and presents them to the user again. Input: Feedback information. Output: Optimized life plan.

[0152] (Application example 1)

[0153] 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."

[0154] In modern society, understanding one's financial situation and establishing a future life plan are extremely important. However, many people find it difficult to properly manage their income and expenses and predict their future financial situation. In particular, creating a specific action plan and implementing it is not easy. Furthermore, there is a lack of a system that allows users to review proposals and provide feedback to continuously optimize their life plans.

[0155] 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.

[0156] In this invention, the server includes means for collecting income and expenditure information, means for using generative artificial intelligence to create a life plan based on the income and expenditure information, means for predicting future economic conditions based on the life plan created by the generative artificial intelligence, means for proposing a specific action plan based on the predicted economic conditions, and means for notifying the user of the specific action plan. This allows the user to create a specific life plan based on income and expenditure information and predict future economic conditions. Furthermore, by proposing specific action plans to the user and incorporating their feedback, the life plan can be continuously optimized.

[0157] "Income and Expense Information" means all data relating to the sources of income and related expenses of an individual or legal entity.

[0158] "Means of collecting income and expenditure information" refers to mechanisms for collecting transaction data from electronic payment services and financial institutions.

[0159] "Means of using generative artificial intelligence to create a life plan based on the income and expenditure information" refers to a system that uses generative artificial intelligence to analyze collected economic data and automatically create a future life plan.

[0160] "Means for predicting future economic conditions based on a life plan created by the generative artificial intelligence" refers to a mechanism for predicting future income and expenditures based on a life plan created by the generative artificial intelligence.

[0161] "Means for proposing a specific action plan based on the predicted economic situation" refers to a mechanism for presenting a specific, feasible economic action plan to a user based on the results of a prediction of future economic conditions.

[0162] The term "means for notifying the user of the specific action plan" refers to a notification means for effectively communicating the generated action plan to the user.

[0163] "Collecting transaction data in cooperation with electronic payment services and financial institution information" refers to automatically obtaining user transaction data in cooperation with electronic payment systems and bank account information.

[0164] "Collecting user feedback and optimizing the life plan" refers to the process of collecting opinions and impressions from users and refining and improving the life plan based on them.

[0165] A "generative AI model" refers to an artificial intelligence system that learns patterns and relationships from given data and generates predictions and suggestions.

[0166] A "prompt sentence" is a sentence that is input into a generative AI model and is text data that serves as a guideline for the subsequent analysis and generation process.

[0167] To put this invention into practice, it is necessary to build a system that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and proposes specific action plans to users. This system is composed of a terminal that collects data on income and expenditure, a server that analyzes the collected data and creates a life plan, and a server that receives feedback from users and performs optimization.

[0168] First, a user creates an account and connects their electronic payment service and financial institution information to the system. Through this connection, transaction data is periodically collected, encrypted, and sent to a server. The server then analyzes the collected data using generative artificial intelligence, evaluates the user's current financial situation, and creates a life plan.

[0169] Specifically, the server sends the following prompt to the generative AI to analyze the data:

[0170] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[0171] Next, the server predicts future economic conditions based on the analysis results of the generative AI. Based on this prediction, the server generates a specific action plan and sends it to the device. The device then displays the proposal to the user via push notifications or in-app messages.

[0172] The user reviews the proposal and enters any necessary changes or feedback into the device, which then sends the feedback to the server. The server then optimizes the life plan based on the user's feedback and generates and sends a new proposal. Through this series of processes, the user can manage their income and expenses through the system and implement a realistic action plan to achieve their future goals.

[0173] The hardware and software used in realizing this invention include a server for managing collected data, computer resources for executing generative artificial intelligence models, and a smartphone or PC as a user interface. Specific software includes a generative artificial intelligence API (e.g., GPT-3 (registered trademark) from OpenAI (registered trademark)) and a standard protocol for encrypting and transferring data (e.g., SSL / TLS).

[0174] For example, if a user sets a goal of "buying a house in three years," the system will propose a savings plan based on the user's transaction data for the next three years, and provide specific suggestions for reducing monthly dining out expenses, etc. Based on these suggestions, the user can adjust their daily economic activities and implement a plan to achieve their goal.

[0175] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0176] Step 1:

[0177] The terminal creates a user account and configures the connection to electronic payment services and financial institution information. As input, the user's account information and bank account information are required, which are used for API connection to obtain encrypted transaction data. As output, the terminal establishes the source information of the data to be collected and sets the trigger for data collection based on this.

[0178] Step 2:

[0179] The terminal periodically retrieves transaction data from electronic payment services and financial institutions, encrypts it, and sends it to the server. As input, the user's bank account and electronic payment service authentication information are required, and the retrieved transaction data is encrypted and sent to the server. As output, the transaction data is retrieved on the server side and prepared for analysis.

[0180] Step 3:

[0181] The server stores the collected transaction data in a database and analyzes the income and expenditure data using a generative AI model. The inputs are encrypted transaction data and a generative AI model for analysis, which analyzes income and expenditure patterns based on the transaction data stored in the database. The output is an assessment of the user's current financial situation.

[0182] Step 4:

[0183] The server creates a life plan based on the analysis results obtained using the generative AI model and predicts future economic situations. The evaluation results obtained in step 3 and the generative AI model are required as input, and the life plan and economic prediction are made by inputting a prompt statement into the generative AI model. As a specific example, the following text is used as the prompt statement:

[0184] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[0185] As output, a predicted outcome and a life plan are generated.

[0186] Step 5:

[0187] The server generates a specific action plan based on the prediction of future economic conditions and sends the details to the device. The server requires a life plan and economic prediction results as input, and uses a generative AI model to generate an action plan, including specific items to cut and savings plans. The specific action plan is sent to the device as output.

[0188] Step 6:

[0189] The device notifies the user of a specific action plan. As input, it requires the action plan received from the server, and displays the proposal to the user using push notifications or in-app messages. As output, the user reviews the proposal and enters any necessary changes or feedback.

[0190] Step 7:

[0191] The user checks the proposal and enters the necessary feedback into the terminal. The input requires an action plan and the user's opinions and impressions, which are entered into the terminal and sent to the server. The output is the user's feedback, which is reflected in the server.

[0192] Step 8:

[0193] The server optimizes the life plan based on the user's feedback and generates and transmits new proposals. The server requires the user's feedback and existing life plan as input, and reevaluates and optimizes the life plan based on the feedback. The server outputs the optimized new life plan and action plan to the device.

[0194] 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.

[0195] To implement the present invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, proposes specific action plans to users, and further recognizes the user's emotions using an emotion engine to optimize the proposals and life plans.

[0196] System Overview

[0197] The system consists of the following elements:

[0198] 1. Terminal: Provides a means of collecting data on income and expenditures and incorporates an emotion engine that recognizes the user's emotions.

[0199] 2. Server: Analyzes the collected data, creates a life plan using generative AI, predicts future economic situations, and incorporates data from the emotion engine to optimize the recommendations.

[0200] 3. User: Create an account, connect electronic payment services and bank account information, and provide emotional data.

[0201] Program processing

[0202] 1. Data Collection

[0203] A user downloads the app and creates an account.

[0204] The user authenticates and configures the settings for linking electronic payment services and bank account information.

[0205] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[0206] 2. Emotion recognition

[0207] The device collects data on the user's behavior on the digital device (e.g., frequency of use, input patterns) and voice data.

[0208] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[0209] The terminal transmits the recognized emotion data to the server.

[0210] 3. Data Analysis

[0211] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories.

[0212] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[0213] 4. Predictions and Recommendations

[0214] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[0215] The server uses past data and big data to predict future economic conditions.

[0216] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[0217] The server transmits the generated action plan to the terminal.

[0218] 5. Feedback and optimization

[0219] The device will display the suggestions to the user via push notifications or in-app messages.

[0220] The user reviews the proposal and enters any necessary changes or feedback.

[0221] The terminal transmits feedback information from the user to the server.

[0222] The server reanalyzes and optimizes the life plan based on the collected feedback and emotional state.

[0223] Specific examples

[0224] Example: Goal of buying a house in 3 years and emotion recognition

[0225] 1. A user downloads the app and creates an account.

[0226] 2. The user connects their electronic payment service and bank account information.

[0227] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0228] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0229] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[0230] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[0231] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[0232] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[0233] 9. The device notifies the user of the proposal and presents a feasible plan.

[0234] 10. User reviews the proposal and makes adjustments as needed.

[0235] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0236] In this way, a system is realized that continuously manages the user's income and expenses and supports goal achievement through suggestions that take into account the user's emotional state, reducing financial anxiety and enabling users to plan their lives with emotional peace of mind.

[0237] The processing flow will be explained below.

[0238] Step 1:

[0239] A user downloads the app and creates an account.

[0240] The user authenticates and configures the electronic payment service and bank account information.

[0241] Step 2:

[0242] The device periodically retrieves income and expenditure transaction data from linked electronic payment and bank accounts.

[0243] The terminal encrypts the acquired transaction data and transmits it to the server.

[0244] Step 3:

[0245] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[0246] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[0247] Step 4:

[0248] The device collects behavioral and voice data from users' digital devices.

[0249] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[0250] The terminal transmits the recognized emotion data to the server.

[0251] Step 5:

[0252] The server creates a life plan based on the analysis results to help the user achieve their goals.

[0253] The server uses past data and big data to predict future economic conditions.

[0254] Step 6:

[0255] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[0256] The server transmits the generated action plan to the terminal.

[0257] Step 7:

[0258] The device will display the suggestions to the user via push notifications or in-app messages.

[0259] The user reviews the proposal and provides any necessary changes or feedback.

[0260] Step 8:

[0261] The terminal transmits feedback information from the user to the server.

[0262] The server reanalyzes and optimizes the life plan based on the collected feedback and perceived emotional state.

[0263] Step 9:

[0264] The server generates an optimized life plan and new proposals.

[0265] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[0266] In this way, a system is built that continuously collects and analyzes income and expenditure information, and provides feedback and suggestions to users to help them achieve their goals. Furthermore, by providing suggestions that take into account the user's emotional state, it is possible to reduce financial anxiety and enable them to plan their lives with emotional peace of mind.

[0267] Example 2

[0268] 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."

[0269] In recent years, personal financial management has become increasingly demanding, requiring users to predict their future financial situation based on income and expenditure information and provide beneficial action plans. However, existing systems have not taken the user's emotional state into account when making proposals, and the proposed plans are not necessarily easy for users to implement. Furthermore, they lack the functionality to efficiently incorporate user feedback and optimize life plans. This has resulted in reduced user satisfaction and feasibility, preventing effective financial management.

[0270] 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.

[0271] In this invention, the server includes: a means for a user to create an account and link their electronic payment service and bank account information; a means for periodically acquiring and encrypting income and expenditure transaction data based on the linked information and transmitting the encrypted data to the server; a means for collecting behavioral patterns and voice data from the user's digital device and using an emotion engine to recognize emotions; a means for transmitting data recognized by the emotion engine to the server; a means for storing and classifying the transaction data and emotion data received by the server; a means for analyzing the collected data using generative artificial intelligence to evaluate the user's current financial situation; a means for creating a life plan based on the analysis results and predicting future financial circumstances; a means for generating a specific action plan based on the prediction results and the user's emotional state and transmitting the plan to the terminal; a means for notifying the user of the generated action plan and collecting feedback; and a means for reanalyzing and optimizing the life plan based on the feedback and the user's emotional state. This enables the system to effectively manage the user's income and expenditure data and provide a feasible action plan that takes the user's emotional state into account. Furthermore, optimizing the life plan based on the user's feedback improves the satisfaction and feasibility of the user's financial management.

[0272] "User" means any person or entity that utilizes the System to provide income and expense information and manage their own financial affairs.

[0273] "Device" refers to a digital device used by a user, such as a computer, smartphone, or tablet, that collects income and expenditure data and information for emotion recognition.

[0274] "Server" refers to a computer system that analyzes, stores, and categorizes collected data and uses generative artificial intelligence to create life plans and predict future economic situations.

[0275] "Income" means any financial gain earned by a User, including salary, bonuses, investment income, etc.

[0276] "Expenses" refers to financial expenses that a user uses for consumption or investment, including food, rent, entertainment, etc.

[0277] "Transaction Data" refers to detailed information about income and expenditure collected through electronic payment services and bank accounts.

[0278] An "emotion engine" refers to technology that analyzes data collected from a user's digital device (behavioral patterns, voice data, etc.) and recognizes the user's emotional state.

[0279] "Generative AI" refers to artificial intelligence technology that creates and optimizes users' life plans based on collected data, and specifically includes machine learning models and data analysis algorithms.

[0280] "Life Plan" refers to a plan for achieving future financial goals that is created using generative artificial intelligence based on a user's income and expenditure data.

[0281] "Action plan" refers to a specific action plan proposed to a user based on a life plan and emotional data created by generative artificial intelligence.

[0282] "Feedback" refers to evaluations, comments, correction requests, etc. provided by users regarding proposed action plans.

[0283] The present invention provides a series of systems that collect income and expenditure information, use generative artificial intelligence to create a life plan based on that information, predict future economic situations, and propose specific action plans to users. The system of the present invention is characterized by further recognizing the user's emotions using an emotion engine and optimizing the proposals and life plan. This system is implemented using the following hardware and software.

[0284] 1. Hardware Elements

[0285] Device: A digital device used by a user, including a smartphone, tablet, or computer. These devices collect income and expenditure data and recognize the user's emotional state through an emotion engine.

[0286] Server: A computer system that analyzes, stores, and classifies data to generate and optimize life plans. This can be a cloud server or an on-premise server.

[0287] 2. Software Elements

[0288] Generative artificial intelligence (AI): AI techniques used to analyze collected data and generate life plans. Examples include machine learning models and data analysis algorithms implemented in Python or R.

[0289] Emotion engine: A technology that recognizes emotions by analyzing the behavioral patterns and voice data of users' digital devices. It uses natural language processing (NLP) and voice analysis technology.

[0290] 3. Data processing and calculation

[0291] Data collection: The user creates an account and links their electronic payment service and bank account information. Based on this information, the device periodically collects transaction data, encrypts it, and sends it to the server.

[0292] Data Analysis and Classification: The server stores the received transaction data and sentiment data in a database and categorizes them into income and expenditure categories. Generative artificial intelligence is used to analyze the collected data and evaluate the user's current financial situation.

[0293] Prediction and proposal: The server creates a life plan based on the analysis results and predicts the user's future economic situation. Based on the prediction results and the user's emotional state, the server generates a specific action plan and sends it to the device.

[0294] 4. Example of a system

[0295] Example: The system operates based on prompts such as, "I am a 30-year-old office worker with an annual income of 5 million yen. My goal is to purchase a house worth 30 million yen in three years. Please record your current monthly income and expenses in detail and tell me a specific action plan for purchasing a house. Also, since I have a lot of stress at work, please include suggestions to reduce the stress."

[0296] A user downloads the app and creates an account.

[0297] The user connects their electronic payment service and bank account information and sets a goal of "buying a house worth 30 million yen in three years."

[0298] Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0299] The device collects behavioral and voice data from the user's digital devices, and the emotion engine analyzes this to recognize the user's emotional state.

[0300] The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[0301] The server suggests the amount of savings needed each month and items of expenditure that can be reduced, and generates an optimized plan that takes emotional data into account.

[0302] The device will notify the user of the proposal and present a feasible plan.

[0303] The user reviews the proposal and makes adjustments as needed.

[0304] The server will optimize your life plan based on the feedback and continue to make specific suggestions.

[0305] In this way, a system that continuously manages a user's income and expenses and supports goal achievement through suggestions that take emotional state into account is realized. Users can safely and effectively manage their financial situation and plan their lives with peace of mind.

[0306] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0307] Step 1:

[0308] A user downloads an app and creates an account. As input, the user provides an email address and password, and the system sends an authentication code. The user enters the authentication code and an account is created. As output, the user account is created and the user remains logged in. In concrete terms, after installing the app, the user accesses the login screen and enters the required information.

[0309] Step 2:

[0310] The user links their electronic payment service and bank account information. As input, the user provides authentication information for each service (user ID, password, etc.). The system authenticates this information via OAuth 2.0 or API and executes the linking. As output, the system completes the linking process, allowing it to securely obtain the user's transaction data. Specifically, the user selects the linking option on the app's settings screen and enters the required authentication information.

[0311] Step 3:

[0312] The terminal periodically retrieves transaction data, encrypts it, and sends it to the server. The input includes data on the electronic payment service and bank account linked by the user. The data is encrypted using an encryption algorithm (e.g., AES-256) and sent to the server using a secure communication protocol (HTTPS). The output is the encrypted transaction data stored on the server. Specifically, the terminal sends an API request, retrieves and encrypts the transaction data, and sends it to the server.

[0313] Step 4:

[0314] The device collects behavioral patterns and voice data from the user's digital device. Input includes the user's frequency of device use, input patterns, and voice data from the microphone. This data is processed locally and temporarily recorded. As output, the collected data is input into the emotion engine. Specifically, the device collects data using the device's sensors and microphone.

[0315] Step 5:

[0316] The emotion engine built into the device analyzes the collected data and recognizes the user's emotional state. The input includes the behavioral patterns and voice data collected in the previous step. Natural language processing (NLP) and voice analysis techniques are used to analyze the data and evaluate the user's emotional state. The output is the recognized emotion data. Specifically, the emotion engine performs data analysis in real time.

[0317] Step 6:

[0318] The device sends the recognized emotion data to the server. The input includes the emotion data output by the emotion engine. This is also encrypted and sent to the server using a secure communication protocol. The output is the emotion data stored on the server. Specifically, the device encrypts the data and issues a request to send it to the server.

[0319] Step 7:

[0320] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories. The input includes encrypted transaction data and emotion data. A database query is executed for storage and categorization in the database. The output is the classified data stored in the database. Specifically, the server issues a database query to store and categorize the data.

[0321] Step 8:

[0322] The server uses generative artificial intelligence to analyze the collected data and evaluate the user's current financial situation. Input includes transaction data and emotion data stored in a database. The generative artificial intelligence model analyzes the data and generates an evaluation of the user's financial situation. The output is the analysis result. Specifically, the server runs the AI ​​model and analyzes the data.

[0323] Step 9:

[0324] The server creates a life plan for the user's goal setting based on the analysis results. The input includes the analysis results of the financial situation and the user's goal information. The algorithm for creating the life plan is executed, and the plan is generated. The output is the generated life plan. Specifically, the server executes the life plan creation algorithm and outputs the results.

[0325] Step 10:

[0326] The server uses past data and big data to predict future economic conditions. Inputs include life plan data and past big data. A machine learning model (e.g., regression analysis or time series analysis model) is used. Outputs include predicted data for economic conditions. Specifically, the server executes the machine learning model to obtain prediction results.

[0327] Step 11:

[0328] The server generates a specific action plan based on the prediction results and emotional state and sends it to the terminal. The input includes predicted data on the economic situation and data on the emotional state. The generative artificial intelligence model creates an action plan based on this data. The output is an action plan that is generated and sent to the terminal. Specifically, the server runs the action plan generation algorithm and sends the results to the terminal.

[0329] Step 12:

[0330] The device sends a notification to the user and presents the suggestion. The input includes the data of the action plan to be notified. The user is notified using a push notification or an in-app message. The output is the suggestion displayed to the user. Specifically, the device uses the notification API to send a message to the user.

[0331] Step 13:

[0332] The user reviews the suggestions and provides any necessary changes or feedback. The input includes the feedback information provided by the user. The feedback is entered using an in-app form or button. The output is feedback data. The specific behavior is that the user fills out a feedback form within the app.

[0333] Step 14:

[0334] The terminal sends user feedback information to the server. The input includes feedback data from the user. The feedback data is encrypted and sent to the server using a secure communication protocol. The output is stored in the server. As a specific operation, the terminal issues a request to encrypt the data and send it to the server.

[0335] Step 15:

[0336] The server reanalyzes and optimizes the life plan based on the feedback and emotional state. The input includes feedback data and emotional data. The generative artificial intelligence model reanalyzes and optimizes the life plan based on this data. The output is an optimized life plan. Specifically, the server runs the reanalysis algorithm and outputs the results.

[0337] (Application example 2)

[0338] 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."

[0339] Conventional life planning systems are limited to simple predictions and suggestions based on income and expenditure information, and therefore are unable to provide optimal action plans that take into account the user's emotional state. As a result, users may feel stressed by the suggestions, reducing their feasibility. To address this issue, a system is needed that not only collects income and expenditure data but also recognizes the user's emotional state and provides optimized suggestions.

[0340] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0341] In this invention, the server includes means for collecting income and expenditure information, means for creating a life plan using generative artificial intelligence, means for recognizing the user's emotional state using an emotion engine and optimizing the proposals and life plan, means for proposing a specific action plan based on the user's future economic situation, and means for displaying the proposals to the user using push notifications or in-app messages. This makes it possible to provide a less stressful action plan that takes the user's emotional state into consideration and increase the feasibility of the plan.

[0342] "Income information" refers to earnings such as salary earned by a user from work or profits from investments.

[0343] "Expense information" is data related to the money consumed by the user, including living expenses, leisure expenses, etc.

[0344] A "life plan" is a plan that predicts a user's future income and expenses and helps them achieve specific financial goals.

[0345] "Generative artificial intelligence" refers to artificial intelligence technology that generates new information based on collected data and makes predictions and suggestions.

[0346] "Future financial situation" refers to the user's future financial situation as predicted based on the collected data.

[0347] An "action plan" is a plan of specific actions to be taken in order to achieve a set goal.

[0348] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state.

[0349] "Electronic payment service" refers to a service that allows users to conduct transactions over the Internet.

[0350] "Bank Account Information" refers to details about a user's bank account.

[0351] "Transaction Data" refers to records of financial transactions conducted by Users.

[0352] "Push notification" refers to a notification sent from an application to a user's device in real time.

[0353] "Feedback" refers to the reactions and opinions of users regarding proposals and plans.

[0354] "Optimization" refers to improving life plans and proposals based on collected data and feedback.

[0355] The present invention is a system that collects income and expenditure data, creates a life plan that takes into account the user's emotional state, and proposes an optimal action plan. Specific embodiments of the system will be described below.

[0356] System configuration

[0357] The system consists of the following elements:

[0358] 1. Terminal

[0359] 2. Server

[0360] 3. Users

[0361] 1. Terminal

[0362] The device is a digital device such as a smartphone or tablet that provides a means to collect a user's income and expenditure information. The device also incorporates an emotion engine that can recognize the user's emotional state. This engine analyzes user behavior and voice data using OpenCV and Google® Cloud Speech-to-Text.

[0363] 2. Server

[0364] The server analyzes the collected data and generates a life plan using generative artificial intelligence. It also incorporates emotional data recognized by the emotion engine to optimize the recommendations. The server is built on Django and uses Google Cloud Firestore to store data. It also uses a TensorFlow model for generative artificial intelligence and Dialogflow for natural language generation.

[0365] 3. Users

[0366] Users download the app, create an account, and link their electronic payment service and bank account information. This allows transaction data to be collected periodically. Users can review the life plan and specific proposals and enter feedback. This feedback is then sent back to the server and used to optimize the plan.

[0367] Specific examples

[0368] Achieving the goal of buying a house in three years

[0369] 1. A user downloads the app and creates an account.

[0370] 2. The user connects their electronic payment service and bank account information.

[0371] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0372] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0373] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[0374] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[0375] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[0376] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[0377] 9. The device notifies the user of the proposal and presents a feasible plan.

[0378] 10. User reviews the proposal and makes adjustments as needed.

[0379] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0380] Prompt Sentence Examples

[0381] "Create a plan to purchase a house worth 30 million yen in three years. Suggest a specific action plan for managing income and expenses necessary to achieve this, and choose the optimal method taking into account the user's emotional state."

[0382] This invention makes it possible to provide a low-stress life plan that takes into account the user's emotional state through a detailed analysis of the user's financial situation, thereby providing a specific and feasible action plan for achieving goals and improving user satisfaction.

[0383] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0384] Step 1:

[0385] A user downloads the app and creates an account.

[0386] Input: App download and account creation information

[0387] Output: User's account

[0388] Specific operation: A user downloads and installs the app. Then, the user enters the required information on the account creation screen to create an account. During this process, the user enters information such as an email address and password, and is authenticated using GOOGLE FI® rebase Authentication.

[0389] Step 2:

[0390] The user connects their electronic payment service and bank account information.

[0391] Input: User's electronic payment service and bank account information

[0392] Output: User transaction data acquisition settings

[0393] How it works: Users link their electronic payment service and bank account through the app's settings screen. The Plaid API is used to connect to the bank account, and the app is set up to periodically retrieve the user's transaction data.

[0394] Step 3:

[0395] The terminal collects income and expenditure data and transmits it to a server.

[0396] Input: Transaction data from your electronic payment service and bank account

[0397] Output: Collected transaction data

[0398] Specific operation: The device periodically collects transaction data from the connected electronic payment service and bank account. This transaction data is encrypted in JSON format and sent to the server. The server stores the data in Google Cloud Firestore.

[0399] Step 4:

[0400] The device collects user behavioral and voice data, which is then analyzed by the emotion engine.

[0401] Input: User behavior data (frequency of use, input patterns) and voice data

[0402] Output: User's emotional state data

[0403] How it works: The device uses OpenCV and Google Cloud Speech-to-Text to collect user behavior and voice data in real time. The emotion engine analyzes this data and determines the user's emotional state. This data is then sent to the server.

[0404] Step 5:

[0405] The server analyzes the transaction data and emotion data and generates a life plan.

[0406] Input: Collected transactional and sentiment data

[0407] Output: Generated life plan

[0408] How it works: The server uses generative artificial intelligence (AI) with TensorFlow to analyze transaction data and evaluate the user's financial situation. It then generates an optimal life plan based on emotional data. This life plan is then stored in Google Cloud Firestore.

[0409] Step 6:

[0410] The server predicts future economic conditions and proposes specific action plans.

[0411] Input: Generated life plan and past data

[0412] Output: A concrete action plan

[0413] Specific operation: The server predicts future economic conditions based on the analysis results and big data. Generative AI generates a specific action plan to achieve the user's goals and provides it to the user in an actionable form.

[0414] Step 7:

[0415] The server adjusts the suggestions to be less stressful based on the emotional data and notifies the device.

[0416] Input: Specific action plans and emotional data

[0417] Output: Notification of adjusted action plan

[0418] What it does: The server takes into account the emotion data and adjusts the action plan to make it less stressful for the user. The adjusted action plan is then sent to the device as a push notification or in-app message. Notifications are sent using Firebase Cloud Messaging (FCM).

[0419] Step 8:

[0420] The device presents the suggestions to the user and receives feedback.

[0421] Input: Coordinated Action Plan

[0422] Output: User feedback

[0423] What it does: The device displays the recommended action plan to the user. The user reviews the proposal and makes any necessary adjustments or comments. The collected feedback is then sent to the server.

[0424] Step 9:

[0425] The server analyzes the feedback and optimizes the life plan.

[0426] Input: User feedback and existing life plans

[0427] Output: Optimized Life Plan

[0428] How it works: The server analyzes the user's feedback and regenerates and optimizes the life plan based on it. The generative AI works with the feedback information to create and save the latest life plan.

[0429] These steps allow users to better manage their financial situation and implement optimal life plans that take into account their emotional state.

[0430] 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.

[0431] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0432] 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.

[0433] [Second embodiment]

[0434] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0435] 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.

[0436] 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).

[0437] 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.

[0438] 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.

[0439] 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).

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] In the smart glasses 214, 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.

[0445] 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."

[0446] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and then proposes specific action plans to users.

[0447] System Overview

[0448] This system consists of a "terminal" that collects data on income and expenses, a "server" that analyzes the collected data and creates a life plan, and a "server" that receives feedback from users and performs optimization.

[0449] Program processing

[0450] 1. Data Collection

[0451] Users create an account and link their electronic payment service and bank account information to the system.

[0452] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[0453] 2. Data Analysis

[0454] The server stores the received income and expenditure data in a database and analyzes it using generative artificial intelligence.

[0455] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan.

[0456] 3. Predictions and Recommendations

[0457] The server predicts future economic conditions based on the analysis results of generative artificial intelligence.

[0458] The server generates a specific action plan based on the prediction results and transmits it to the terminal.

[0459] The device will display the suggestions to the user via push notifications or in-app messages.

[0460] 4. Feedback and optimization

[0461] The user reviews the suggestions and enters any necessary changes or feedback into the device.

[0462] The terminal sends feedback information to the server.

[0463] The server optimizes the life plan based on the feedback and generates and sends new proposals.

[0464] Specific examples

[0465] Example: Goal to buy a house in 3 years

[0466] 1. A user downloads the app and creates an account.

[0467] 2. The user connects their electronic payment service and bank account information.

[0468] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0469] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0470] 5. The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[0471] 6. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[0472] 7. The device notifies the user of the proposal and presents a feasible plan.

[0473] 8. The user reviews the proposal and makes adjustments as needed.

[0474] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0475] In this way, users can manage their income and expenses through the system and implement realistic action plans to achieve their future goals. This system reduces users' financial worries and allows them to plan their lives with greater peace of mind.

[0476] The processing flow will be explained below.

[0477] Step 1:

[0478] A user downloads the app and creates an account.

[0479] The user authenticates and configures the settings to link electronic payment services and bank account information.

[0480] Step 2:

[0481] The terminal periodically acquires transaction data from the linked electronic payment service and bank account.

[0482] The terminal encrypts and stores the acquired transaction data and periodically transmits it to the server.

[0483] Step 3:

[0484] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[0485] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[0486] Step 4:

[0487] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[0488] The server uses past data and big data to predict future economic conditions.

[0489] Step 5:

[0490] The server generates a specific action plan based on the prediction results.

[0491] The server transmits the generated action plan to the terminal.

[0492] Step 6:

[0493] The device will display the suggestions to the user via push notifications or in-app messages.

[0494] The user reviews the proposal and enters any necessary changes or feedback.

[0495] Step 7:

[0496] The terminal transmits feedback information from the user to the server.

[0497] The server reanalyzes and optimizes your life plan based on the collected feedback.

[0498] Step 8:

[0499] The server generates an optimized life plan and new proposals.

[0500] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[0501] In this way, a system is created that continuously collects and analyzes income and expenditure information, and provides users with feedback and suggestions to help them achieve their goals.

[0502] Example 1

[0503] 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."

[0504] In recent years, it has become increasingly important to effectively utilize personal income and expenditure information to specifically plan future life plans. However, current systems do not effectively coordinate data collection, encryption, analysis, and recommendations, and are insufficiently optimized to reflect user feedback. Ensuring safety and efficiency are also issues. To address these issues, a system is needed that efficiently collects and securely transmits income and expenditure data, creates high-quality life plans using generative AI models, and predicts users' future financial situations.

[0505] 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.

[0506] In this invention, the server includes: means for a user to create an account and link with product and service providers; means for periodically acquiring income and expenditure measurement data based on link information via a terminal, encrypting the data, and transmitting the encrypted data to the server; means for the server to analyze the income and expenditure data using a generative AI model and create a life plan; means for predicting future economic conditions based on the created life plan; means for generating a specific action plan based on the prediction results and proposing it to the user via the terminal; and means for collecting user feedback and optimizing the life plan. This makes it possible to analyze the user's income and expenditure in detail, accurately predict future economic conditions, and provide a realistic and specific action plan.

[0507] "User" refers to an individual who uses the system to input income and expense information and receive a financial forecast and suggested action plan.

[0508] "Terminal" refers to a device used by a user that acquires income and expenditure transaction data, encrypts it, and transmits it to a server.

[0509] "Server" refers to the computer system that stores collected income and expenditure data, analyzes the data using generative AI models, and creates and provides life plans.

[0510] "Income and Expense Measure Data" means data that includes transaction information related to a user's income and expenses.

[0511] "Linked information" refers to information related to a user's income and expenditures that is shared with electronic payment services and financial institutions.

[0512] "Generative AI model" refers to an artificial intelligence model that analyzes income and expenditure data to create and optimize life plans.

[0513] "Life Plan" refers to future financial plans and goals created based on a user's income and expenditure data.

[0514] An "action plan" refers to a plan based on the user's life plan that includes proposals for specific income and expenditure management methods, investment plans, etc.

[0515] "Feedback" refers to opinions and requests for corrections made by users regarding the proposed action plan.

[0516] "Encryption" refers to the process used to protect collected income and expense data from being read by third parties.

[0517] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using a generative AI model, predicts future economic conditions, and then proposes specific action plans to users.

[0518] System Overview

[0519] The system consists of three main components:

[0520] 1. Terminal: A device used by a user that collects income and expenditure transaction data, encrypts it, and sends it to a server.

[0521] 2. Server: Analyzes the collected income and expenditure data and creates a life plan using a generative AI model. It also predicts future economic situations and generates specific action plans.

[0522] 3. User: A user of the system who creates an account, enters income and expense information, and implements the proposed action plan.

[0523] Hardware and Software Configuration

[0524] 1. Devices: Use mobile devices such as smartphones and tablets. These devices require API access to collect income and expenditure data. Specifically, use APIs provided by major electronic payment services and financial institutions.

[0525] 2. Server: A high-performance computer system that requires software to run the generative AI model and a database management system (e.g., MySQL or PostgreSQL), using a deep learning framework such as TensorFlow or PyTorch.

[0526] Specific examples

[0527] As an example, we will show how the system works when you set a goal of buying a house in three years.

[0528] 1. A user downloads the system app and creates an account.

[0529] 2. The user connects their electronic payment service and bank account information.

[0530] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0531] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0532] 5. The server analyzes the data received and creates an income and expenditure plan to save 30 million yen in three years.

[0533] 6. The server generates a proposal for the amount of savings needed each month and items of expenses that can be reduced (for example, reducing monthly eating out expenses by 20,000 yen).

[0534] 7. The device notifies the user of the proposal and presents a feasible plan.

[0535] 8. The user reviews the proposal and makes adjustments as needed.

[0536] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0537] Through this collaboration, the system will efficiently manage users' income and expenses, accurately predict their future financial situation, and provide realistic action plans to help them achieve their life plans.

[0538] Prompt Sentence Examples

[0539] "Based on your income and expenditure data, generate a concrete action plan to purchase a 30 million yen house in three years."

[0540] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0541] Step 1:

[0542] The user creates an account and links their electronic payment service and bank account information to the system. The user downloads the system's app and creates an account by entering basic information such as name, email address, and password. Next, they link their electronic payment service and bank account information to the system and allow API access. Input: Basic information, linked information. Output: Notification of account creation completion, registration of linked information.

[0543] Step 2:

[0544] Based on the linked information, the device periodically obtains income and expenditure transaction data, encrypts it, and sends it to the server. The device periodically (e.g. daily or weekly) accesses the API of financial institutions and electronic payment services to obtain the latest income and expenditure transaction data. The obtained data is encrypted using an encryption algorithm such as AES256. Input: Linkage information, transaction data. Output: Encrypted transaction data.

[0545] Step 3:

[0546] The server stores the received income and expenditure data in a database and analyzes it using a generative AI model. The server receives encrypted transaction data from the terminal and stores it in a database. The generative AI model is then used to analyze the data and understand the user's income and expenditure patterns. Input: Encrypted transaction data. Output: Analysis results, user's income and expenditure patterns.

[0547] Step 4:

[0548] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan. The server evaluates the user's income and expenditure patterns from the analysis results and uses a generative AI model to create an optimal life plan. For example, a specific plan can be created based on the user's goals for the future (e.g., buying a house, saving for their children's education). Input: Analysis results, user goals. Output: Life plan.

[0549] Step 5:

[0550] The server uses the generated AI model to predict future economic conditions based on the life plan. The server predicts future economic conditions based on the user's income, expenditures, and savings plans described in the life plan. For example, it also takes into account income growth cycles and the risk of unexpected expenditures. Input: Life plan. Output: Future economic situation prediction results.

[0551] Step 6:

[0552] The server generates a specific action plan based on the prediction results and sends it to the device. The server generates specific actions that the user should take (e.g., monthly savings amount, which items to cut spending on) based on the future economic situation prediction results and sends it to the device. Input: Future economic situation prediction results. Output: Action plan.

[0553] Step 7:

[0554] The device notifies the user of the proposed action plan and presents an actionable plan. The device displays the action plan received from the server to the user and informs them of the proposed action plan via push notification or in-app message. The user reviews the displayed plan and considers what can be done. Input: Action plan. Output: Notification to user, presentation of action plan.

[0555] Step 8:

[0556] The user reviews the proposal and inputs any necessary changes or feedback into the device. The user reviews the proposed action plan, makes any necessary changes to suit their own living situation, and inputs feedback into the device. Input: Feedback, changes. Output: Feedback information.

[0557] Step 9:

[0558] The device sends feedback information to the server, which then optimizes the life plan based on this. The device sends feedback information received from the user to the server, which updates the generative AI model to optimize the life plan. This generates new proposals and presents them to the user again. Input: Feedback information. Output: Optimized life plan.

[0559] (Application example 1)

[0560] 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."

[0561] In modern society, understanding one's financial situation and establishing a future life plan are extremely important. However, many people find it difficult to properly manage their income and expenses and predict their future financial situation. In particular, creating a specific action plan and implementing it is not easy. Furthermore, there is a lack of a system that allows users to review proposals and provide feedback to continuously optimize their life plans.

[0562] 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.

[0563] In this invention, the server includes means for collecting income and expenditure information, means for using generative artificial intelligence to create a life plan based on the income and expenditure information, means for predicting future economic conditions based on the life plan created by the generative artificial intelligence, means for proposing a specific action plan based on the predicted economic conditions, and means for notifying the user of the specific action plan. This allows the user to create a specific life plan based on income and expenditure information and predict future economic conditions. Furthermore, by proposing specific action plans to the user and incorporating their feedback, the life plan can be continuously optimized.

[0564] "Income and Expense Information" means all data relating to the sources of income and related expenses of an individual or legal entity.

[0565] "Means of collecting income and expenditure information" refers to mechanisms for collecting transaction data from electronic payment services and financial institutions.

[0566] "Means of using generative artificial intelligence to create a life plan based on the income and expenditure information" refers to a system that uses generative artificial intelligence to analyze collected economic data and automatically create a future life plan.

[0567] "Means for predicting future economic conditions based on a life plan created by the generative artificial intelligence" refers to a mechanism for predicting future income and expenditures based on a life plan created by the generative artificial intelligence.

[0568] "Means for proposing a specific action plan based on the predicted economic situation" refers to a mechanism for presenting a specific, feasible economic action plan to a user based on the results of a prediction of future economic conditions.

[0569] The term "means for notifying the user of the specific action plan" refers to a notification means for effectively communicating the generated action plan to the user.

[0570] "Collecting transaction data in cooperation with electronic payment services and financial institution information" refers to automatically obtaining user transaction data in cooperation with electronic payment systems and bank account information.

[0571] "Collecting user feedback and optimizing the life plan" refers to the process of collecting opinions and impressions from users and refining and improving the life plan based on them.

[0572] A "generative AI model" refers to an artificial intelligence system that learns patterns and relationships from given data and generates predictions and suggestions.

[0573] A "prompt sentence" is a sentence that is input into a generative AI model and is text data that serves as a guideline for the subsequent analysis and generation process.

[0574] To put this invention into practice, it is necessary to build a system that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and proposes specific action plans to users. This system is composed of a terminal that collects data on income and expenditure, a server that analyzes the collected data and creates a life plan, and a server that receives feedback from users and performs optimization.

[0575] First, a user creates an account and connects their electronic payment service and financial institution information to the system. Through this connection, transaction data is periodically collected, encrypted, and sent to a server. The server then analyzes the collected data using generative artificial intelligence, evaluates the user's current financial situation, and creates a life plan.

[0576] Specifically, the server sends the following prompt to the generative AI to analyze the data:

[0577] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[0578] Next, the server predicts future economic conditions based on the analysis results of the generative AI. Based on this prediction, the server generates a specific action plan and sends it to the device. The device then displays the proposal to the user via push notifications or in-app messages.

[0579] The user reviews the proposal and enters any necessary changes or feedback into the device, which then sends the feedback to the server. The server then optimizes the life plan based on the user's feedback and generates and sends a new proposal. Through this series of processes, the user can manage their income and expenses through the system and implement a realistic action plan to achieve their future goals.

[0580] The hardware and software used in realizing this invention include a server for managing collected data, computer resources for executing generative artificial intelligence models, and a smartphone or PC as a user interface. Specific software includes a generative artificial intelligence API (e.g., OpenAI's GPT-3) and a standard protocol for encrypting and transferring data (e.g., SSL / TLS).

[0581] For example, if a user sets a goal of "buying a house in three years," the system will propose a savings plan based on the user's transaction data for the next three years, and provide specific suggestions for reducing monthly dining out expenses, etc. Based on these suggestions, the user can adjust their daily economic activities and implement a plan to achieve their goal.

[0582] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0583] Step 1:

[0584] The terminal creates a user account and configures the connection to electronic payment services and financial institution information. As input, the user's account information and bank account information are required, which are used for API connection to obtain encrypted transaction data. As output, the terminal establishes the source information of the data to be collected and sets the trigger for data collection based on this.

[0585] Step 2:

[0586] The terminal periodically retrieves transaction data from electronic payment services and financial institutions, encrypts it, and sends it to the server. As input, the user's bank account and electronic payment service authentication information are required, and the retrieved transaction data is encrypted and sent to the server. As output, the transaction data is retrieved on the server side and prepared for analysis.

[0587] Step 3:

[0588] The server stores the collected transaction data in a database and analyzes the income and expenditure data using a generative AI model. The inputs are encrypted transaction data and a generative AI model for analysis, which analyzes income and expenditure patterns based on the transaction data stored in the database. The output is an assessment of the user's current financial situation.

[0589] Step 4:

[0590] The server creates a life plan based on the analysis results obtained using the generative AI model and predicts future economic situations. The evaluation results obtained in step 3 and the generative AI model are required as input, and the life plan and economic prediction are made by inputting a prompt statement into the generative AI model. As a specific example, the following text is used as the prompt statement:

[0591] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[0592] As output, a predicted outcome and a life plan are generated.

[0593] Step 5:

[0594] The server generates a specific action plan based on the prediction of future economic conditions and sends the details to the device. The server requires a life plan and economic prediction results as input, and uses a generative AI model to generate an action plan, including specific items to cut and savings plans. The specific action plan is sent to the device as output.

[0595] Step 6:

[0596] The device notifies the user of a specific action plan. As input, it requires the action plan received from the server, and displays the proposal to the user using push notifications or in-app messages. As output, the user reviews the proposal and enters any necessary changes or feedback.

[0597] Step 7:

[0598] The user checks the proposal and enters the necessary feedback into the terminal. The input requires an action plan and the user's opinions and impressions, which are entered into the terminal and sent to the server. The output is the user's feedback, which is reflected in the server.

[0599] Step 8:

[0600] The server optimizes the life plan based on the user's feedback and generates and transmits new proposals. The server requires the user's feedback and existing life plan as input, and reevaluates and optimizes the life plan based on the feedback. The server outputs the optimized new life plan and action plan to the device.

[0601] 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.

[0602] To implement the present invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, proposes specific action plans to users, and further recognizes the user's emotions using an emotion engine to optimize the proposals and life plans.

[0603] System Overview

[0604] The system consists of the following elements:

[0605] 1. Terminal: Provides a means of collecting data on income and expenditures and incorporates an emotion engine that recognizes the user's emotions.

[0606] 2. Server: Analyzes the collected data, creates a life plan using generative AI, predicts future economic situations, and incorporates data from the emotion engine to optimize the recommendations.

[0607] 3. User: Create an account, connect electronic payment services and bank account information, and provide emotional data.

[0608] Program processing

[0609] 1. Data Collection

[0610] A user downloads the app and creates an account.

[0611] The user authenticates and configures the settings for linking electronic payment services and bank account information.

[0612] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[0613] 2. Emotion recognition

[0614] The device collects data on the user's behavior on the digital device (e.g., frequency of use, input patterns) and voice data.

[0615] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[0616] The terminal transmits the recognized emotion data to the server.

[0617] 3. Data Analysis

[0618] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories.

[0619] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[0620] 4. Predictions and Recommendations

[0621] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[0622] The server uses past data and big data to predict future economic conditions.

[0623] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[0624] The server transmits the generated action plan to the terminal.

[0625] 5. Feedback and optimization

[0626] The device will display the suggestions to the user via push notifications or in-app messages.

[0627] The user reviews the proposal and enters any necessary changes or feedback.

[0628] The terminal transmits feedback information from the user to the server.

[0629] The server reanalyzes and optimizes the life plan based on the collected feedback and emotional state.

[0630] Specific examples

[0631] Example: Goal of buying a house in 3 years and emotion recognition

[0632] 1. A user downloads the app and creates an account.

[0633] 2. The user connects their electronic payment service and bank account information.

[0634] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0635] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0636] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[0637] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[0638] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[0639] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[0640] 9. The device notifies the user of the proposal and presents a feasible plan.

[0641] 10. User reviews the proposal and makes adjustments as needed.

[0642] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0643] In this way, a system is realized that continuously manages the user's income and expenses and supports goal achievement through suggestions that take into account the user's emotional state, reducing financial anxiety and enabling users to plan their lives with emotional peace of mind.

[0644] The processing flow will be explained below.

[0645] Step 1:

[0646] A user downloads the app and creates an account.

[0647] The user authenticates and configures the electronic payment service and bank account information.

[0648] Step 2:

[0649] The device periodically retrieves income and expenditure transaction data from linked electronic payment and bank accounts.

[0650] The terminal encrypts the acquired transaction data and transmits it to the server.

[0651] Step 3:

[0652] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[0653] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[0654] Step 4:

[0655] The device collects behavioral and voice data from users' digital devices.

[0656] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[0657] The terminal transmits the recognized emotion data to the server.

[0658] Step 5:

[0659] The server creates a life plan based on the analysis results to help the user achieve their goals.

[0660] The server uses past data and big data to predict future economic conditions.

[0661] Step 6:

[0662] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[0663] The server transmits the generated action plan to the terminal.

[0664] Step 7:

[0665] The device will display the suggestions to the user via push notifications or in-app messages.

[0666] The user reviews the proposal and provides any necessary changes or feedback.

[0667] Step 8:

[0668] The terminal transmits feedback information from the user to the server.

[0669] The server reanalyzes and optimizes the life plan based on the collected feedback and perceived emotional state.

[0670] Step 9:

[0671] The server generates an optimized life plan and new proposals.

[0672] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[0673] In this way, a system is built that continuously collects and analyzes income and expenditure information, and provides feedback and suggestions to users to help them achieve their goals. Furthermore, by providing suggestions that take into account the user's emotional state, it is possible to reduce financial anxiety and enable them to plan their lives with emotional peace of mind.

[0674] Example 2

[0675] 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."

[0676] In recent years, personal financial management has become increasingly demanding, requiring users to predict their future financial situation based on income and expenditure information and provide beneficial action plans. However, existing systems have not taken the user's emotional state into account when making proposals, and the proposed plans are not necessarily easy for users to implement. Furthermore, they lack the functionality to efficiently incorporate user feedback and optimize life plans. This has resulted in reduced user satisfaction and feasibility, preventing effective financial management.

[0677] 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.

[0678] In this invention, the server includes: a means for a user to create an account and link their electronic payment service and bank account information; a means for periodically acquiring and encrypting income and expenditure transaction data based on the linked information and transmitting the encrypted data to the server; a means for collecting behavioral patterns and voice data from the user's digital device and using an emotion engine to recognize emotions; a means for transmitting data recognized by the emotion engine to the server; a means for storing and classifying the transaction data and emotion data received by the server; a means for analyzing the collected data using generative artificial intelligence to evaluate the user's current financial situation; a means for creating a life plan based on the analysis results and predicting future financial circumstances; a means for generating a specific action plan based on the prediction results and the user's emotional state and transmitting the plan to the terminal; a means for notifying the user of the generated action plan and collecting feedback; and a means for reanalyzing and optimizing the life plan based on the feedback and the user's emotional state. This enables the system to effectively manage the user's income and expenditure data and provide a feasible action plan that takes the user's emotional state into account. Furthermore, optimizing the life plan based on the user's feedback improves the satisfaction and feasibility of the user's financial management.

[0679] "User" means any person or entity that utilizes the System to provide income and expense information and manage their own financial affairs.

[0680] "Device" refers to a digital device used by a user, such as a computer, smartphone, or tablet, that collects income and expenditure data and information for emotion recognition.

[0681] "Server" refers to a computer system that analyzes, stores, and categorizes collected data and uses generative artificial intelligence to create life plans and predict future economic situations.

[0682] "Income" means any financial gain earned by a User, including salary, bonuses, investment income, etc.

[0683] "Expenses" refers to financial expenses that a user uses for consumption or investment, including food, rent, entertainment, etc.

[0684] "Transaction Data" refers to detailed information about income and expenditure collected through electronic payment services and bank accounts.

[0685] An "emotion engine" refers to technology that analyzes data collected from a user's digital device (behavioral patterns, voice data, etc.) and recognizes the user's emotional state.

[0686] "Generative AI" refers to artificial intelligence technology that creates and optimizes users' life plans based on collected data, and specifically includes machine learning models and data analysis algorithms.

[0687] "Life Plan" refers to a plan for achieving future financial goals that is created using generative artificial intelligence based on a user's income and expenditure data.

[0688] "Action plan" refers to a specific action plan proposed to a user based on a life plan and emotional data created by generative artificial intelligence.

[0689] "Feedback" refers to evaluations, comments, correction requests, etc. provided by users regarding proposed action plans.

[0690] The present invention provides a series of systems that collect income and expenditure information, use generative artificial intelligence to create a life plan based on that information, predict future economic situations, and propose specific action plans to users. The system of the present invention is characterized by further recognizing the user's emotions using an emotion engine and optimizing the proposals and life plan. This system is implemented using the following hardware and software.

[0691] 1. Hardware Elements

[0692] Device: A digital device used by a user, including a smartphone, tablet, or computer. These devices collect income and expenditure data and recognize the user's emotional state through an emotion engine.

[0693] Server: A computer system that analyzes, stores, and classifies data to generate and optimize life plans. This can be a cloud server or an on-premise server.

[0694] 2. Software Elements

[0695] Generative artificial intelligence (AI): AI techniques used to analyze collected data and generate life plans. Examples include machine learning models and data analysis algorithms implemented in Python or R.

[0696] Emotion engine: A technology that recognizes emotions by analyzing the behavioral patterns and voice data of users' digital devices. It uses natural language processing (NLP) and voice analysis technology.

[0697] 3. Data processing and calculation

[0698] Data collection: The user creates an account and links their electronic payment service and bank account information. Based on this information, the device periodically collects transaction data, encrypts it, and sends it to the server.

[0699] Data Analysis and Classification: The server stores the received transaction data and sentiment data in a database and categorizes them into income and expenditure categories. Generative artificial intelligence is used to analyze the collected data and evaluate the user's current financial situation.

[0700] Prediction and proposal: The server creates a life plan based on the analysis results and predicts the user's future economic situation. Based on the prediction results and the user's emotional state, the server generates a specific action plan and sends it to the device.

[0701] 4. Example of a system

[0702] Example: The system operates based on prompts such as, "I am a 30-year-old office worker with an annual income of 5 million yen. My goal is to purchase a house worth 30 million yen in three years. Please record your current monthly income and expenses in detail and tell me a specific action plan for purchasing a house. Also, since I have a lot of stress at work, please include suggestions to reduce the stress."

[0703] A user downloads the app and creates an account.

[0704] The user connects their electronic payment service and bank account information and sets a goal of "buying a house worth 30 million yen in three years."

[0705] Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0706] The device collects behavioral and voice data from the user's digital devices, and the emotion engine analyzes this to recognize the user's emotional state.

[0707] The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[0708] The server suggests the amount of savings needed each month and items of expenditure that can be reduced, and generates an optimized plan that takes emotional data into account.

[0709] The device will notify the user of the proposal and present a feasible plan.

[0710] The user reviews the proposal and makes adjustments as needed.

[0711] The server will optimize your life plan based on the feedback and continue to make specific suggestions.

[0712] In this way, a system that continuously manages a user's income and expenses and supports goal achievement through suggestions that take emotional state into account is realized. Users can safely and effectively manage their financial situation and plan their lives with peace of mind.

[0713] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0714] Step 1:

[0715] A user downloads an app and creates an account. As input, the user provides an email address and password, and the system sends an authentication code. The user enters the authentication code and an account is created. As output, the user account is created and the user remains logged in. In concrete terms, after installing the app, the user accesses the login screen and enters the required information.

[0716] Step 2:

[0717] The user links their electronic payment service and bank account information. As input, the user provides authentication information for each service (user ID, password, etc.). The system authenticates this information via OAuth 2.0 or API and executes the linking. As output, the system completes the linking process, allowing it to securely obtain the user's transaction data. Specifically, the user selects the linking option on the app's settings screen and enters the required authentication information.

[0718] Step 3:

[0719] The terminal periodically retrieves transaction data, encrypts it, and sends it to the server. The input includes data on the electronic payment service and bank account linked by the user. The data is encrypted using an encryption algorithm (e.g., AES-256) and sent to the server using a secure communication protocol (HTTPS). The output is the encrypted transaction data stored on the server. Specifically, the terminal sends an API request, retrieves and encrypts the transaction data, and sends it to the server.

[0720] Step 4:

[0721] The device collects behavioral patterns and voice data from the user's digital device. Input includes the user's frequency of device use, input patterns, and voice data from the microphone. This data is processed locally and temporarily recorded. As output, the collected data is input into the emotion engine. Specifically, the device collects data using the device's sensors and microphone.

[0722] Step 5:

[0723] The emotion engine built into the device analyzes the collected data and recognizes the user's emotional state. The input includes the behavioral patterns and voice data collected in the previous step. Natural language processing (NLP) and voice analysis techniques are used to analyze the data and evaluate the user's emotional state. The output is the recognized emotion data. Specifically, the emotion engine performs data analysis in real time.

[0724] Step 6:

[0725] The device sends the recognized emotion data to the server. The input includes the emotion data output by the emotion engine. This is also encrypted and sent to the server using a secure communication protocol. The output is the emotion data stored on the server. Specifically, the device encrypts the data and issues a request to send it to the server.

[0726] Step 7:

[0727] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories. The input includes encrypted transaction data and emotion data. A database query is executed for storage and categorization in the database. The output is the classified data stored in the database. Specifically, the server issues a database query to store and categorize the data.

[0728] Step 8:

[0729] The server uses generative artificial intelligence to analyze the collected data and evaluate the user's current financial situation. Input includes transaction data and emotion data stored in a database. The generative artificial intelligence model analyzes the data and generates an evaluation of the user's financial situation. The output is the analysis result. Specifically, the server runs the AI ​​model and analyzes the data.

[0730] Step 9:

[0731] The server creates a life plan for the user's goal setting based on the analysis results. The input includes the analysis results of the financial situation and the user's goal information. The algorithm for creating the life plan is executed, and the plan is generated. The output is the generated life plan. Specifically, the server executes the life plan creation algorithm and outputs the results.

[0732] Step 10:

[0733] The server uses past data and big data to predict future economic conditions. Inputs include life plan data and past big data. A machine learning model (e.g., regression analysis or time series analysis model) is used. Outputs include predicted data for economic conditions. Specifically, the server executes the machine learning model to obtain prediction results.

[0734] Step 11:

[0735] The server generates a specific action plan based on the prediction results and emotional state and sends it to the terminal. The input includes predicted data on the economic situation and data on the emotional state. The generative artificial intelligence model creates an action plan based on this data. The output is an action plan that is generated and sent to the terminal. Specifically, the server runs the action plan generation algorithm and sends the results to the terminal.

[0736] Step 12:

[0737] The device sends a notification to the user and presents the suggestion. The input includes the data of the action plan to be notified. The user is notified using a push notification or an in-app message. The output is the suggestion displayed to the user. Specifically, the device uses the notification API to send a message to the user.

[0738] Step 13:

[0739] The user reviews the suggestions and provides any necessary changes or feedback. The input includes the feedback information provided by the user. The feedback is entered using an in-app form or button. The output is feedback data. The specific behavior is that the user fills out a feedback form within the app.

[0740] Step 14:

[0741] The terminal sends user feedback information to the server. The input includes feedback data from the user. The feedback data is encrypted and sent to the server using a secure communication protocol. The output is stored in the server. As a specific operation, the terminal issues a request to encrypt the data and send it to the server.

[0742] Step 15:

[0743] The server reanalyzes and optimizes the life plan based on the feedback and emotional state. The input includes feedback data and emotional data. The generative artificial intelligence model reanalyzes and optimizes the life plan based on this data. The output is an optimized life plan. Specifically, the server runs the reanalysis algorithm and outputs the results.

[0744] (Application example 2)

[0745] 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."

[0746] Conventional life planning systems are limited to simple predictions and suggestions based on income and expenditure information, and therefore are unable to provide optimal action plans that take into account the user's emotional state. As a result, users may feel stressed by the suggestions, reducing their feasibility. To address this issue, a system is needed that not only collects income and expenditure data but also recognizes the user's emotional state and provides optimized suggestions.

[0747] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0748] In this invention, the server includes means for collecting income and expenditure information, means for creating a life plan using generative artificial intelligence, means for recognizing the user's emotional state using an emotion engine and optimizing the proposals and life plan, means for proposing a specific action plan based on the user's future economic situation, and means for displaying the proposals to the user using push notifications or in-app messages. This makes it possible to provide a less stressful action plan that takes the user's emotional state into consideration and increase the feasibility of the plan.

[0749] "Income information" refers to earnings such as salary earned by a user from work or profits from investments.

[0750] "Expense information" is data related to the money consumed by the user, including living expenses, leisure expenses, etc.

[0751] A "life plan" is a plan that predicts a user's future income and expenses and helps them achieve specific financial goals.

[0752] "Generative artificial intelligence" refers to artificial intelligence technology that generates new information based on collected data and makes predictions and suggestions.

[0753] "Future financial situation" refers to the user's future financial situation as predicted based on the collected data.

[0754] An "action plan" is a plan of specific actions to be taken in order to achieve a set goal.

[0755] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state.

[0756] "Electronic payment service" refers to a service that allows users to conduct transactions over the Internet.

[0757] "Bank Account Information" refers to details about a user's bank account.

[0758] "Transaction Data" refers to records of financial transactions conducted by Users.

[0759] "Push notification" refers to a notification sent from an application to a user's device in real time.

[0760] "Feedback" refers to the reactions and opinions of users regarding proposals and plans.

[0761] "Optimization" refers to improving life plans and proposals based on collected data and feedback.

[0762] The present invention is a system that collects income and expenditure data, creates a life plan that takes into account the user's emotional state, and proposes an optimal action plan. Specific embodiments of the system will be described below.

[0763] System configuration

[0764] The system consists of the following elements:

[0765] 1. Terminal

[0766] 2. Server

[0767] 3. Users

[0768] 1. Terminal

[0769] The terminal is a digital device such as a smartphone or tablet that provides a means to collect a user's income and expenditure information. The terminal also incorporates an emotion engine that can recognize the user's emotional state. The engine analyzes user behavior and voice data using OpenCV and Google Cloud Speech-to-Text.

[0770] 2. Server

[0771] The server analyzes the collected data and generates a life plan using generative artificial intelligence. It also incorporates emotional data recognized by the emotion engine to optimize the recommendations. The server is built on Django and uses Google Cloud Firestore to store data. It also uses a TensorFlow model for generative artificial intelligence and Dialogflow for natural language generation.

[0772] 3. Users

[0773] Users download the app, create an account, and link their electronic payment service and bank account information. This allows transaction data to be collected periodically. Users can review the life plan and specific proposals and enter feedback. This feedback is then sent back to the server and used to optimize the plan.

[0774] Specific examples

[0775] Achieving the goal of buying a house in three years

[0776] 1. A user downloads the app and creates an account.

[0777] 2. The user connects their electronic payment service and bank account information.

[0778] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0779] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0780] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[0781] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[0782] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[0783] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[0784] 9. The device notifies the user of the proposal and presents a feasible plan.

[0785] 10. User reviews the proposal and makes adjustments as needed.

[0786] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0787] Prompt Sentence Examples

[0788] "Create a plan to purchase a house worth 30 million yen in three years. Suggest a specific action plan for managing income and expenses necessary to achieve this, and choose the optimal method taking into account the user's emotional state."

[0789] This invention makes it possible to provide a low-stress life plan that takes into account the user's emotional state through a detailed analysis of the user's financial situation, thereby providing a specific and feasible action plan for achieving goals and improving user satisfaction.

[0790] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0791] Step 1:

[0792] A user downloads the app and creates an account.

[0793] Input: App download and account creation information

[0794] Output: User's account

[0795] Specific operation: A user downloads and installs the app. Then, the user enters the required information on the account creation screen and creates an account. During this process, the user enters information such as an email address and password, and is authenticated using Google Firebase Authentication.

[0796] Step 2:

[0797] The user connects their electronic payment service and bank account information.

[0798] Input: User's electronic payment service and bank account information

[0799] Output: User transaction data acquisition settings

[0800] How it works: Users link their electronic payment service and bank account through the app's settings screen. The Plaid API is used to connect to the bank account, and the app is set up to periodically retrieve the user's transaction data.

[0801] Step 3:

[0802] The terminal collects income and expenditure data and transmits it to a server.

[0803] Input: Transaction data from your electronic payment service and bank account

[0804] Output: Collected transaction data

[0805] Specific operation: The device periodically collects transaction data from the connected electronic payment service and bank account. This transaction data is encrypted in JSON format and sent to the server. The server stores the data in Google Cloud Firestore.

[0806] Step 4:

[0807] The device collects user behavioral and voice data, which is then analyzed by the emotion engine.

[0808] Input: User behavior data (frequency of use, input patterns) and voice data

[0809] Output: User's emotional state data

[0810] How it works: The device uses OpenCV and Google Cloud Speech-to-Text to collect user behavior and voice data in real time. The emotion engine analyzes this data and determines the user's emotional state. This data is then sent to the server.

[0811] Step 5:

[0812] The server analyzes the transaction data and emotion data and generates a life plan.

[0813] Input: Collected transactional and sentiment data

[0814] Output: Generated life plan

[0815] How it works: The server uses generative artificial intelligence (AI) with TensorFlow to analyze transaction data and evaluate the user's financial situation. It then generates an optimal life plan based on emotional data. This life plan is then stored in Google Cloud Firestore.

[0816] Step 6:

[0817] The server predicts future economic conditions and proposes specific action plans.

[0818] Input: Generated life plan and past data

[0819] Output: A concrete action plan

[0820] Specific operation: The server predicts future economic conditions based on the analysis results and big data. Generative AI generates a specific action plan to achieve the user's goals and provides it to the user in an actionable form.

[0821] Step 7:

[0822] The server adjusts the suggestions to be less stressful based on the emotional data and notifies the device.

[0823] Input: Specific action plans and emotional data

[0824] Output: Notification of adjusted action plan

[0825] What it does: The server takes into account the emotion data and adjusts the action plan to make it less stressful for the user. The adjusted action plan is then sent to the device as a push notification or in-app message. Notifications are sent using Firebase Cloud Messaging (FCM).

[0826] Step 8:

[0827] The device presents the suggestions to the user and receives feedback.

[0828] Input: Coordinated Action Plan

[0829] Output: User feedback

[0830] What it does: The device displays the recommended action plan to the user. The user reviews the proposal and makes any necessary adjustments or comments. The collected feedback is then sent to the server.

[0831] Step 9:

[0832] The server analyzes the feedback and optimizes the life plan.

[0833] Input: User feedback and existing life plans

[0834] Output: Optimized Life Plan

[0835] How it works: The server analyzes the user's feedback and regenerates and optimizes the life plan based on it. The generative AI works with the feedback information to create and save the latest life plan.

[0836] These steps allow users to better manage their financial situation and implement optimal life plans that take into account their emotional state.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] [Third embodiment]

[0841] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0842] 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.

[0843] 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).

[0844] 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.

[0845] 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.

[0846] 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).

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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."

[0853] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and then proposes specific action plans to users.

[0854] System Overview

[0855] This system consists of a "terminal" that collects data on income and expenses, a "server" that analyzes the collected data and creates a life plan, and a "server" that receives feedback from users and performs optimization.

[0856] Program processing

[0857] 1. Data Collection

[0858] Users create an account and link their electronic payment service and bank account information to the system.

[0859] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[0860] 2. Data Analysis

[0861] The server stores the received income and expenditure data in a database and analyzes it using generative artificial intelligence.

[0862] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan.

[0863] 3. Predictions and Recommendations

[0864] The server predicts future economic conditions based on the analysis results of generative artificial intelligence.

[0865] The server generates a specific action plan based on the prediction results and transmits it to the terminal.

[0866] The device will display the suggestions to the user via push notifications or in-app messages.

[0867] 4. Feedback and optimization

[0868] The user reviews the suggestions and enters any necessary changes or feedback into the device.

[0869] The terminal sends feedback information to the server.

[0870] The server optimizes the life plan based on the feedback and generates and sends new proposals.

[0871] Specific examples

[0872] Example: Goal to buy a house in 3 years

[0873] 1. A user downloads the app and creates an account.

[0874] 2. The user connects their electronic payment service and bank account information.

[0875] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0876] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0877] 5. The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[0878] 6. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[0879] 7. The device notifies the user of the proposal and presents a feasible plan.

[0880] 8. The user reviews the proposal and makes adjustments as needed.

[0881] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0882] In this way, users can manage their income and expenses through the system and implement realistic action plans to achieve their future goals. This system reduces users' financial worries and allows them to plan their lives with greater peace of mind.

[0883] The processing flow will be explained below.

[0884] Step 1:

[0885] A user downloads the app and creates an account.

[0886] The user authenticates and configures the settings to link electronic payment services and bank account information.

[0887] Step 2:

[0888] The terminal periodically acquires transaction data from the linked electronic payment service and bank account.

[0889] The terminal encrypts and stores the acquired transaction data and periodically transmits it to the server.

[0890] Step 3:

[0891] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[0892] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[0893] Step 4:

[0894] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[0895] The server uses past data and big data to predict future economic conditions.

[0896] Step 5:

[0897] The server generates a specific action plan based on the prediction results.

[0898] The server transmits the generated action plan to the terminal.

[0899] Step 6:

[0900] The device will display the suggestions to the user via push notifications or in-app messages.

[0901] The user reviews the proposal and enters any necessary changes or feedback.

[0902] Step 7:

[0903] The terminal transmits feedback information from the user to the server.

[0904] The server reanalyzes and optimizes your life plan based on the collected feedback.

[0905] Step 8:

[0906] The server generates an optimized life plan and new proposals.

[0907] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[0908] In this way, a system is created that continuously collects and analyzes income and expenditure information, and provides users with feedback and suggestions to help them achieve their goals.

[0909] Example 1

[0910] 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."

[0911] In recent years, it has become increasingly important to effectively utilize personal income and expenditure information to specifically plan future life plans. However, current systems do not effectively coordinate data collection, encryption, analysis, and recommendations, and are insufficiently optimized to reflect user feedback. Ensuring safety and efficiency are also issues. To address these issues, a system is needed that efficiently collects and securely transmits income and expenditure data, creates high-quality life plans using generative AI models, and predicts users' future financial situations.

[0912] 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.

[0913] In this invention, the server includes: means for a user to create an account and link with product and service providers; means for periodically acquiring income and expenditure measurement data based on link information via a terminal, encrypting the data, and transmitting the encrypted data to the server; means for the server to analyze the income and expenditure data using a generative AI model and create a life plan; means for predicting future economic conditions based on the created life plan; means for generating a specific action plan based on the prediction results and proposing it to the user via the terminal; and means for collecting user feedback and optimizing the life plan. This makes it possible to analyze the user's income and expenditure in detail, accurately predict future economic conditions, and provide a realistic and specific action plan.

[0914] "User" refers to an individual who uses the system to input income and expense information and receive a financial forecast and suggested action plan.

[0915] "Terminal" refers to a device used by a user that acquires income and expenditure transaction data, encrypts it, and transmits it to a server.

[0916] "Server" refers to the computer system that stores collected income and expenditure data, analyzes the data using generative AI models, and creates and provides life plans.

[0917] "Income and Expense Measure Data" means data that includes transaction information related to a user's income and expenses.

[0918] "Linked information" refers to information related to a user's income and expenditures that is shared with electronic payment services and financial institutions.

[0919] "Generative AI model" refers to an artificial intelligence model that analyzes income and expenditure data to create and optimize life plans.

[0920] "Life Plan" refers to future financial plans and goals created based on a user's income and expenditure data.

[0921] An "action plan" refers to a plan based on the user's life plan that includes proposals for specific income and expenditure management methods, investment plans, etc.

[0922] "Feedback" refers to opinions and requests for corrections made by users regarding the proposed action plan.

[0923] "Encryption" refers to the process used to protect collected income and expense data from being read by third parties.

[0924] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using a generative AI model, predicts future economic conditions, and then proposes specific action plans to users.

[0925] System Overview

[0926] The system consists of three main components:

[0927] 1. Terminal: A device used by a user that collects income and expenditure transaction data, encrypts it, and sends it to a server.

[0928] 2. Server: Analyzes the collected income and expenditure data and creates a life plan using a generative AI model. It also predicts future economic situations and generates specific action plans.

[0929] 3. User: A user of the system who creates an account, enters income and expense information, and implements the proposed action plan.

[0930] Hardware and Software Configuration

[0931] 1. Devices: Use mobile devices such as smartphones and tablets. These devices require API access to collect income and expenditure data. Specifically, use APIs provided by major electronic payment services and financial institutions.

[0932] 2. Server: A high-performance computer system that requires software to run the generative AI model and a database management system (e.g., MySQL or PostgreSQL), using a deep learning framework such as TensorFlow or PyTorch.

[0933] Specific examples

[0934] As an example, we will show how the system works when you set a goal of buying a house in three years.

[0935] 1. A user downloads the system app and creates an account.

[0936] 2. The user connects their electronic payment service and bank account information.

[0937] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[0938] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[0939] 5. The server analyzes the data received and creates an income and expenditure plan to save 30 million yen in three years.

[0940] 6. The server generates a proposal for the amount of savings needed each month and items of expenses that can be reduced (for example, reducing monthly eating out expenses by 20,000 yen).

[0941] 7. The device notifies the user of the proposal and presents a feasible plan.

[0942] 8. The user reviews the proposal and makes adjustments as needed.

[0943] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[0944] Through this collaboration, the system will efficiently manage users' income and expenses, accurately predict their future financial situation, and provide realistic action plans to help them achieve their life plans.

[0945] Prompt Sentence Examples

[0946] "Based on your income and expenditure data, generate a concrete action plan to purchase a 30 million yen house in three years."

[0947] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0948] Step 1:

[0949] The user creates an account and links their electronic payment service and bank account information to the system. The user downloads the system's app and creates an account by entering basic information such as name, email address, and password. Next, they link their electronic payment service and bank account information to the system and allow API access. Input: Basic information, linked information. Output: Notification of account creation completion, registration of linked information.

[0950] Step 2:

[0951] Based on the linked information, the device periodically obtains income and expenditure transaction data, encrypts it, and sends it to the server. The device periodically (e.g. daily or weekly) accesses the API of financial institutions and electronic payment services to obtain the latest income and expenditure transaction data. The obtained data is encrypted using an encryption algorithm such as AES256. Input: Linkage information, transaction data. Output: Encrypted transaction data.

[0952] Step 3:

[0953] The server stores the received income and expenditure data in a database and analyzes it using a generative AI model. The server receives encrypted transaction data from the terminal and stores it in a database. The generative AI model is then used to analyze the data and understand the user's income and expenditure patterns. Input: Encrypted transaction data. Output: Analysis results, user's income and expenditure patterns.

[0954] Step 4:

[0955] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan. The server evaluates the user's income and expenditure patterns from the analysis results and uses a generative AI model to create an optimal life plan. For example, a specific plan can be created based on the user's goals for the future (e.g., buying a house, saving for their children's education). Input: Analysis results, user goals. Output: Life plan.

[0956] Step 5:

[0957] The server uses the generated AI model to predict future economic conditions based on the life plan. The server predicts future economic conditions based on the user's income, expenditures, and savings plans described in the life plan. For example, it also takes into account income growth cycles and the risk of unexpected expenditures. Input: Life plan. Output: Future economic situation prediction results.

[0958] Step 6:

[0959] The server generates a specific action plan based on the prediction results and sends it to the device. The server generates specific actions that the user should take (e.g., monthly savings amount, which items to cut spending on) based on the future economic situation prediction results and sends it to the device. Input: Future economic situation prediction results. Output: Action plan.

[0960] Step 7:

[0961] The device notifies the user of the proposed action plan and presents an actionable plan. The device displays the action plan received from the server to the user and informs them of the proposed action plan via push notification or in-app message. The user reviews the displayed plan and considers what can be done. Input: Action plan. Output: Notification to user, presentation of action plan.

[0962] Step 8:

[0963] The user reviews the proposal and inputs any necessary changes or feedback into the device. The user reviews the proposed action plan, makes any necessary changes to suit their own living situation, and inputs feedback into the device. Input: Feedback, changes. Output: Feedback information.

[0964] Step 9:

[0965] The device sends feedback information to the server, which then optimizes the life plan based on this. The device sends feedback information received from the user to the server, which updates the generative AI model to optimize the life plan. This generates new proposals and presents them to the user again. Input: Feedback information. Output: Optimized life plan.

[0966] (Application example 1)

[0967] 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."

[0968] In modern society, understanding one's financial situation and establishing a future life plan are extremely important. However, many people find it difficult to properly manage their income and expenses and predict their future financial situation. In particular, creating a specific action plan and implementing it is not easy. Furthermore, there is a lack of a system that allows users to review proposals and provide feedback to continuously optimize their life plans.

[0969] 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.

[0970] In this invention, the server includes means for collecting income and expenditure information, means for using generative artificial intelligence to create a life plan based on the income and expenditure information, means for predicting future economic conditions based on the life plan created by the generative artificial intelligence, means for proposing a specific action plan based on the predicted economic conditions, and means for notifying the user of the specific action plan. This allows the user to create a specific life plan based on income and expenditure information and predict future economic conditions. Furthermore, by proposing specific action plans to the user and incorporating their feedback, the life plan can be continuously optimized.

[0971] "Income and Expense Information" means all data relating to the sources of income and related expenses of an individual or legal entity.

[0972] "Means of collecting income and expenditure information" refers to mechanisms for collecting transaction data from electronic payment services and financial institutions.

[0973] "Means of using generative artificial intelligence to create a life plan based on the income and expenditure information" refers to a system that uses generative artificial intelligence to analyze collected economic data and automatically create a future life plan.

[0974] "Means for predicting future economic conditions based on a life plan created by the generative artificial intelligence" refers to a mechanism for predicting future income and expenditures based on a life plan created by the generative artificial intelligence.

[0975] "Means for proposing a specific action plan based on the predicted economic situation" refers to a mechanism for presenting a specific, feasible economic action plan to a user based on the results of a prediction of future economic conditions.

[0976] The term "means for notifying the user of the specific action plan" refers to a notification means for effectively communicating the generated action plan to the user.

[0977] "Collecting transaction data in cooperation with electronic payment services and financial institution information" refers to automatically obtaining user transaction data in cooperation with electronic payment systems and bank account information.

[0978] "Collecting user feedback and optimizing the life plan" refers to the process of collecting opinions and impressions from users and refining and improving the life plan based on them.

[0979] A "generative AI model" refers to an artificial intelligence system that learns patterns and relationships from given data and generates predictions and suggestions.

[0980] A "prompt sentence" is a sentence that is input into a generative AI model and is text data that serves as a guideline for the subsequent analysis and generation process.

[0981] To put this invention into practice, it is necessary to build a system that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and proposes specific action plans to users. This system is composed of a terminal that collects data on income and expenditure, a server that analyzes the collected data and creates a life plan, and a server that receives feedback from users and performs optimization.

[0982] First, a user creates an account and connects their electronic payment service and financial institution information to the system. Through this connection, transaction data is periodically collected, encrypted, and sent to a server. The server then analyzes the collected data using generative artificial intelligence, evaluates the user's current financial situation, and creates a life plan.

[0983] Specifically, the server sends the following prompt to the generative AI to analyze the data:

[0984] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[0985] Next, the server predicts future economic conditions based on the analysis results of the generative AI. Based on this prediction, the server generates a specific action plan and sends it to the device. The device then displays the proposal to the user via push notifications or in-app messages.

[0986] The user reviews the proposal and enters any necessary changes or feedback into the device, which then sends the feedback to the server. The server then optimizes the life plan based on the user's feedback and generates and sends a new proposal. Through this series of processes, the user can manage their income and expenses through the system and implement a realistic action plan to achieve their future goals.

[0987] The hardware and software used in realizing this invention include a server for managing collected data, computer resources for executing generative artificial intelligence models, and a smartphone or PC as a user interface. Specific software includes a generative artificial intelligence API (e.g., OpenAI's GPT-3) and a standard protocol for encrypting and transferring data (e.g., SSL / TLS).

[0988] For example, if a user sets a goal of "buying a house in three years," the system will propose a savings plan based on the user's transaction data for the next three years, and provide specific suggestions for reducing monthly dining out expenses, etc. Based on these suggestions, the user can adjust their daily economic activities and implement a plan to achieve their goal.

[0989] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0990] Step 1:

[0991] The terminal creates a user account and configures the connection to electronic payment services and financial institution information. As input, the user's account information and bank account information are required, which are used for API connection to obtain encrypted transaction data. As output, the terminal establishes the source information of the data to be collected and sets the trigger for data collection based on this.

[0992] Step 2:

[0993] The terminal periodically retrieves transaction data from electronic payment services and financial institutions, encrypts it, and sends it to the server. As input, the user's bank account and electronic payment service authentication information are required, and the retrieved transaction data is encrypted and sent to the server. As output, the transaction data is retrieved on the server side and prepared for analysis.

[0994] Step 3:

[0995] The server stores the collected transaction data in a database and analyzes the income and expenditure data using a generative AI model. The inputs are encrypted transaction data and a generative AI model for analysis, which analyzes income and expenditure patterns based on the transaction data stored in the database. The output is an assessment of the user's current financial situation.

[0996] Step 4:

[0997] The server creates a life plan based on the analysis results obtained using the generative AI model and predicts future economic situations. The evaluation results obtained in step 3 and the generative AI model are required as input, and the life plan and economic prediction are made by inputting a prompt statement into the generative AI model. As a specific example, the following text is used as the prompt statement:

[0998] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[0999] As output, a predicted outcome and a life plan are generated.

[1000] Step 5:

[1001] The server generates a specific action plan based on the prediction of future economic conditions and sends the details to the device. The server requires a life plan and economic prediction results as input, and uses a generative AI model to generate an action plan, including specific items to cut and savings plans. The specific action plan is sent to the device as output.

[1002] Step 6:

[1003] The device notifies the user of a specific action plan. As input, it requires the action plan received from the server, and displays the proposal to the user using push notifications or in-app messages. As output, the user reviews the proposal and enters any necessary changes or feedback.

[1004] Step 7:

[1005] The user checks the proposal and enters the necessary feedback into the terminal. The input requires an action plan and the user's opinions and impressions, which are entered into the terminal and sent to the server. The output is the user's feedback, which is reflected in the server.

[1006] Step 8:

[1007] The server optimizes the life plan based on the user's feedback and generates and transmits new proposals. The server requires the user's feedback and existing life plan as input, and reevaluates and optimizes the life plan based on the feedback. The server outputs the optimized new life plan and action plan to the device.

[1008] 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.

[1009] To implement the present invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, proposes specific action plans to users, and further recognizes the user's emotions using an emotion engine to optimize the proposals and life plans.

[1010] System Overview

[1011] The system consists of the following elements:

[1012] 1. Terminal: Provides a means of collecting data on income and expenditures and incorporates an emotion engine that recognizes the user's emotions.

[1013] 2. Server: Analyzes the collected data, creates a life plan using generative AI, predicts future economic situations, and incorporates data from the emotion engine to optimize the recommendations.

[1014] 3. User: Create an account, connect electronic payment services and bank account information, and provide emotional data.

[1015] Program processing

[1016] 1. Data Collection

[1017] A user downloads the app and creates an account.

[1018] The user authenticates and configures the settings for linking electronic payment services and bank account information.

[1019] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[1020] 2. Emotion recognition

[1021] The device collects data on the user's behavior on the digital device (e.g., frequency of use, input patterns) and voice data.

[1022] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[1023] The terminal transmits the recognized emotion data to the server.

[1024] 3. Data Analysis

[1025] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories.

[1026] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[1027] 4. Predictions and Recommendations

[1028] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[1029] The server uses past data and big data to predict future economic conditions.

[1030] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[1031] The server transmits the generated action plan to the terminal.

[1032] 5. Feedback and optimization

[1033] The device will display the suggestions to the user via push notifications or in-app messages.

[1034] The user reviews the proposal and enters any necessary changes or feedback.

[1035] The terminal transmits feedback information from the user to the server.

[1036] The server reanalyzes and optimizes the life plan based on the collected feedback and emotional state.

[1037] Specific examples

[1038] Example: Goal of buying a house in 3 years and emotion recognition

[1039] 1. A user downloads the app and creates an account.

[1040] 2. The user connects their electronic payment service and bank account information.

[1041] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[1042] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1043] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[1044] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[1045] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[1046] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[1047] 9. The device notifies the user of the proposal and presents a feasible plan.

[1048] 10. User reviews the proposal and makes adjustments as needed.

[1049] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[1050] In this way, a system is realized that continuously manages the user's income and expenses and supports goal achievement through suggestions that take into account the user's emotional state, reducing financial anxiety and enabling users to plan their lives with emotional peace of mind.

[1051] The processing flow will be explained below.

[1052] Step 1:

[1053] A user downloads the app and creates an account.

[1054] The user authenticates and configures the electronic payment service and bank account information.

[1055] Step 2:

[1056] The device periodically retrieves income and expenditure transaction data from linked electronic payment and bank accounts.

[1057] The terminal encrypts the acquired transaction data and transmits it to the server.

[1058] Step 3:

[1059] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[1060] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[1061] Step 4:

[1062] The device collects behavioral and voice data from users' digital devices.

[1063] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[1064] The terminal transmits the recognized emotion data to the server.

[1065] Step 5:

[1066] The server creates a life plan based on the analysis results to help the user achieve their goals.

[1067] The server uses past data and big data to predict future economic conditions.

[1068] Step 6:

[1069] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[1070] The server transmits the generated action plan to the terminal.

[1071] Step 7:

[1072] The device will display the suggestions to the user via push notifications or in-app messages.

[1073] The user reviews the proposal and provides any necessary changes or feedback.

[1074] Step 8:

[1075] The terminal transmits feedback information from the user to the server.

[1076] The server reanalyzes and optimizes the life plan based on the collected feedback and perceived emotional state.

[1077] Step 9:

[1078] The server generates an optimized life plan and new proposals.

[1079] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[1080] In this way, a system is built that continuously collects and analyzes income and expenditure information, and provides feedback and suggestions to users to help them achieve their goals. Furthermore, by providing suggestions that take into account the user's emotional state, it is possible to reduce financial anxiety and enable them to plan their lives with emotional peace of mind.

[1081] Example 2

[1082] 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."

[1083] In recent years, personal financial management has become increasingly demanding, requiring users to predict their future financial situation based on income and expenditure information and provide beneficial action plans. However, existing systems have not taken the user's emotional state into account when making proposals, and the proposed plans are not necessarily easy for users to implement. Furthermore, they lack the functionality to efficiently incorporate user feedback and optimize life plans. This has resulted in reduced user satisfaction and feasibility, preventing effective financial management.

[1084] 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.

[1085] In this invention, the server includes: a means for a user to create an account and link their electronic payment service and bank account information; a means for periodically acquiring and encrypting income and expenditure transaction data based on the linked information and transmitting the encrypted data to the server; a means for collecting behavioral patterns and voice data from the user's digital device and using an emotion engine to recognize emotions; a means for transmitting data recognized by the emotion engine to the server; a means for storing and classifying the transaction data and emotion data received by the server; a means for analyzing the collected data using generative artificial intelligence to evaluate the user's current financial situation; a means for creating a life plan based on the analysis results and predicting future financial circumstances; a means for generating a specific action plan based on the prediction results and the user's emotional state and transmitting the plan to the terminal; a means for notifying the user of the generated action plan and collecting feedback; and a means for reanalyzing and optimizing the life plan based on the feedback and the user's emotional state. This enables the system to effectively manage the user's income and expenditure data and provide a feasible action plan that takes the user's emotional state into account. Furthermore, optimizing the life plan based on the user's feedback improves the satisfaction and feasibility of the user's financial management.

[1086] "User" means any person or entity that utilizes the System to provide income and expense information and manage their own financial affairs.

[1087] "Device" refers to a digital device used by a user, such as a computer, smartphone, or tablet, that collects income and expenditure data and information for emotion recognition.

[1088] "Server" refers to a computer system that analyzes, stores, and categorizes collected data and uses generative artificial intelligence to create life plans and predict future economic situations.

[1089] "Income" means any financial gain earned by a User, including salary, bonuses, investment income, etc.

[1090] "Expenses" refers to financial expenses that a user uses for consumption or investment, including food, rent, entertainment, etc.

[1091] "Transaction Data" refers to detailed information about income and expenditure collected through electronic payment services and bank accounts.

[1092] An "emotion engine" refers to technology that analyzes data collected from a user's digital device (behavioral patterns, voice data, etc.) and recognizes the user's emotional state.

[1093] "Generative AI" refers to artificial intelligence technology that creates and optimizes users' life plans based on collected data, and specifically includes machine learning models and data analysis algorithms.

[1094] "Life Plan" refers to a plan for achieving future financial goals that is created using generative artificial intelligence based on a user's income and expenditure data.

[1095] "Action plan" refers to a specific action plan proposed to a user based on a life plan and emotional data created by generative artificial intelligence.

[1096] "Feedback" refers to evaluations, comments, correction requests, etc. provided by users regarding proposed action plans.

[1097] The present invention provides a series of systems that collect income and expenditure information, use generative artificial intelligence to create a life plan based on that information, predict future economic situations, and propose specific action plans to users. The system of the present invention is characterized by further recognizing the user's emotions using an emotion engine and optimizing the proposals and life plan. This system is implemented using the following hardware and software.

[1098] 1. Hardware Elements

[1099] Device: A digital device used by a user, including a smartphone, tablet, or computer. These devices collect income and expenditure data and recognize the user's emotional state through an emotion engine.

[1100] Server: A computer system that analyzes, stores, and classifies data to generate and optimize life plans. This can be a cloud server or an on-premise server.

[1101] 2. Software Elements

[1102] Generative artificial intelligence (AI): AI techniques used to analyze collected data and generate life plans. Examples include machine learning models and data analysis algorithms implemented in Python or R.

[1103] Emotion engine: A technology that recognizes emotions by analyzing the behavioral patterns and voice data of users' digital devices. It uses natural language processing (NLP) and voice analysis technology.

[1104] 3. Data processing and calculation

[1105] Data collection: The user creates an account and links their electronic payment service and bank account information. Based on this information, the device periodically collects transaction data, encrypts it, and sends it to the server.

[1106] Data Analysis and Classification: The server stores the received transaction data and sentiment data in a database and categorizes them into income and expenditure categories. Generative artificial intelligence is used to analyze the collected data and evaluate the user's current financial situation.

[1107] Prediction and proposal: The server creates a life plan based on the analysis results and predicts the user's future economic situation. Based on the prediction results and the user's emotional state, the server generates a specific action plan and sends it to the device.

[1108] 4. Example of a system

[1109] Example: The system operates based on prompts such as, "I am a 30-year-old office worker with an annual income of 5 million yen. My goal is to purchase a house worth 30 million yen in three years. Please record your current monthly income and expenses in detail and tell me a specific action plan for purchasing a house. Also, since I have a lot of stress at work, please include suggestions to reduce the stress."

[1110] A user downloads the app and creates an account.

[1111] The user connects their electronic payment service and bank account information and sets a goal of "buying a house worth 30 million yen in three years."

[1112] Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1113] The device collects behavioral and voice data from the user's digital devices, and the emotion engine analyzes this to recognize the user's emotional state.

[1114] The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[1115] The server suggests the amount of savings needed each month and items of expenditure that can be reduced, and generates an optimized plan that takes emotional data into account.

[1116] The device will notify the user of the proposal and present a feasible plan.

[1117] The user reviews the proposal and makes adjustments as needed.

[1118] The server will optimize your life plan based on the feedback and continue to make specific suggestions.

[1119] In this way, a system that continuously manages a user's income and expenses and supports goal achievement through suggestions that take emotional state into account is realized. Users can safely and effectively manage their financial situation and plan their lives with peace of mind.

[1120] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1121] Step 1:

[1122] A user downloads an app and creates an account. As input, the user provides an email address and password, and the system sends an authentication code. The user enters the authentication code and an account is created. As output, the user account is created and the user remains logged in. In concrete terms, after installing the app, the user accesses the login screen and enters the required information.

[1123] Step 2:

[1124] The user links their electronic payment service and bank account information. As input, the user provides authentication information for each service (user ID, password, etc.). The system authenticates this information via OAuth 2.0 or API and executes the linking. As output, the system completes the linking process, allowing it to securely obtain the user's transaction data. Specifically, the user selects the linking option on the app's settings screen and enters the required authentication information.

[1125] Step 3:

[1126] The terminal periodically retrieves transaction data, encrypts it, and sends it to the server. The input includes data on the electronic payment service and bank account linked by the user. The data is encrypted using an encryption algorithm (e.g., AES-256) and sent to the server using a secure communication protocol (HTTPS). The output is the encrypted transaction data stored on the server. Specifically, the terminal sends an API request, retrieves and encrypts the transaction data, and sends it to the server.

[1127] Step 4:

[1128] The device collects behavioral patterns and voice data from the user's digital device. Input includes the user's frequency of device use, input patterns, and voice data from the microphone. This data is processed locally and temporarily recorded. As output, the collected data is input into the emotion engine. Specifically, the device collects data using the device's sensors and microphone.

[1129] Step 5:

[1130] The emotion engine built into the device analyzes the collected data and recognizes the user's emotional state. The input includes the behavioral patterns and voice data collected in the previous step. Natural language processing (NLP) and voice analysis techniques are used to analyze the data and evaluate the user's emotional state. The output is the recognized emotion data. Specifically, the emotion engine performs data analysis in real time.

[1131] Step 6:

[1132] The device sends the recognized emotion data to the server. The input includes the emotion data output by the emotion engine. This is also encrypted and sent to the server using a secure communication protocol. The output is the emotion data stored on the server. Specifically, the device encrypts the data and issues a request to send it to the server.

[1133] Step 7:

[1134] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories. The input includes encrypted transaction data and emotion data. A database query is executed for storage and categorization in the database. The output is the classified data stored in the database. Specifically, the server issues a database query to store and categorize the data.

[1135] Step 8:

[1136] The server uses generative artificial intelligence to analyze the collected data and evaluate the user's current financial situation. Input includes transaction data and emotion data stored in a database. The generative artificial intelligence model analyzes the data and generates an evaluation of the user's financial situation. The output is the analysis result. Specifically, the server runs the AI ​​model and analyzes the data.

[1137] Step 9:

[1138] The server creates a life plan for the user's goal setting based on the analysis results. The input includes the analysis results of the financial situation and the user's goal information. The algorithm for creating the life plan is executed, and the plan is generated. The output is the generated life plan. Specifically, the server executes the life plan creation algorithm and outputs the results.

[1139] Step 10:

[1140] The server uses past data and big data to predict future economic conditions. Inputs include life plan data and past big data. A machine learning model (e.g., regression analysis or time series analysis model) is used. Outputs include predicted data for economic conditions. Specifically, the server executes the machine learning model to obtain prediction results.

[1141] Step 11:

[1142] The server generates a specific action plan based on the prediction results and emotional state and sends it to the terminal. The input includes predicted data on the economic situation and data on the emotional state. The generative artificial intelligence model creates an action plan based on this data. The output is an action plan that is generated and sent to the terminal. Specifically, the server runs the action plan generation algorithm and sends the results to the terminal.

[1143] Step 12:

[1144] The device sends a notification to the user and presents the suggestion. The input includes the data of the action plan to be notified. The user is notified using a push notification or an in-app message. The output is the suggestion displayed to the user. Specifically, the device uses the notification API to send a message to the user.

[1145] Step 13:

[1146] The user reviews the suggestions and provides any necessary changes or feedback. The input includes the feedback information provided by the user. The feedback is entered using an in-app form or button. The output is feedback data. The specific behavior is that the user fills out a feedback form within the app.

[1147] Step 14:

[1148] The terminal sends user feedback information to the server. The input includes feedback data from the user. The feedback data is encrypted and sent to the server using a secure communication protocol. The output is stored in the server. As a specific operation, the terminal issues a request to encrypt the data and send it to the server.

[1149] Step 15:

[1150] The server reanalyzes and optimizes the life plan based on the feedback and emotional state. The input includes feedback data and emotional data. The generative artificial intelligence model reanalyzes and optimizes the life plan based on this data. The output is an optimized life plan. Specifically, the server runs the reanalysis algorithm and outputs the results.

[1151] (Application example 2)

[1152] 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."

[1153] Conventional life planning systems are limited to simple predictions and suggestions based on income and expenditure information, and therefore are unable to provide optimal action plans that take into account the user's emotional state. As a result, users may feel stressed by the suggestions, reducing their feasibility. To address this issue, a system is needed that not only collects income and expenditure data but also recognizes the user's emotional state and provides optimized suggestions.

[1154] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1155] In this invention, the server includes means for collecting income and expenditure information, means for creating a life plan using generative artificial intelligence, means for recognizing the user's emotional state using an emotion engine and optimizing the proposals and life plan, means for proposing a specific action plan based on the user's future economic situation, and means for displaying the proposals to the user using push notifications or in-app messages. This makes it possible to provide a less stressful action plan that takes the user's emotional state into consideration and increase the feasibility of the plan.

[1156] "Income information" refers to earnings such as salary earned by a user from work or profits from investments.

[1157] "Expense information" is data related to the money consumed by the user, including living expenses, leisure expenses, etc.

[1158] A "life plan" is a plan that predicts a user's future income and expenses and helps them achieve specific financial goals.

[1159] "Generative artificial intelligence" refers to artificial intelligence technology that generates new information based on collected data and makes predictions and suggestions.

[1160] "Future financial situation" refers to the user's future financial situation as predicted based on the collected data.

[1161] An "action plan" is a plan of specific actions to be taken in order to achieve a set goal.

[1162] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state.

[1163] "Electronic payment service" refers to a service that allows users to conduct transactions over the Internet.

[1164] "Bank Account Information" refers to details about a user's bank account.

[1165] "Transaction Data" refers to records of financial transactions conducted by Users.

[1166] "Push notification" refers to a notification sent from an application to a user's device in real time.

[1167] "Feedback" refers to the reactions and opinions of users regarding proposals and plans.

[1168] "Optimization" refers to improving life plans and proposals based on collected data and feedback.

[1169] The present invention is a system that collects income and expenditure data, creates a life plan that takes into account the user's emotional state, and proposes an optimal action plan. Specific embodiments of the system will be described below.

[1170] System configuration

[1171] The system consists of the following elements:

[1172] 1. Terminal

[1173] 2. Server

[1174] 3. Users

[1175] 1. Terminal

[1176] The terminal is a digital device such as a smartphone or tablet that provides a means to collect a user's income and expenditure information. The terminal also incorporates an emotion engine that can recognize the user's emotional state. The engine analyzes user behavior and voice data using OpenCV and Google Cloud Speech-to-Text.

[1177] 2. Server

[1178] The server analyzes the collected data and generates a life plan using generative artificial intelligence. It also incorporates emotional data recognized by the emotion engine to optimize the recommendations. The server is built on Django and uses Google Cloud Firestore to store data. It also uses a TensorFlow model for generative artificial intelligence and Dialogflow for natural language generation.

[1179] 3. Users

[1180] Users download the app, create an account, and link their electronic payment service and bank account information. This allows transaction data to be collected periodically. Users can review the life plan and specific proposals and enter feedback. This feedback is then sent back to the server and used to optimize the plan.

[1181] Specific examples

[1182] Achieving the goal of buying a house in three years

[1183] 1. A user downloads the app and creates an account.

[1184] 2. The user connects their electronic payment service and bank account information.

[1185] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[1186] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1187] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[1188] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[1189] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[1190] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[1191] 9. The device notifies the user of the proposal and presents a feasible plan.

[1192] 10. User reviews the proposal and makes adjustments as needed.

[1193] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[1194] Prompt Sentence Examples

[1195] "Create a plan to purchase a house worth 30 million yen in three years. Suggest a specific action plan for managing income and expenses necessary to achieve this, and choose the optimal method taking into account the user's emotional state."

[1196] This invention makes it possible to provide a low-stress life plan that takes into account the user's emotional state through a detailed analysis of the user's financial situation, thereby providing a specific and feasible action plan for achieving goals and improving user satisfaction.

[1197] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1198] Step 1:

[1199] A user downloads the app and creates an account.

[1200] Input: App download and account creation information

[1201] Output: User's account

[1202] Specific operation: A user downloads and installs the app. Then, the user enters the required information on the account creation screen and creates an account. During this process, the user enters information such as an email address and password, and is authenticated using Google Firebase Authentication.

[1203] Step 2:

[1204] The user connects their electronic payment service and bank account information.

[1205] Input: User's electronic payment service and bank account information

[1206] Output: User transaction data acquisition settings

[1207] How it works: Users link their electronic payment service and bank account through the app's settings screen. The Plaid API is used to connect to the bank account, and the app is set up to periodically retrieve the user's transaction data.

[1208] Step 3:

[1209] The terminal collects income and expenditure data and transmits it to a server.

[1210] Input: Transaction data from your electronic payment service and bank account

[1211] Output: Collected transaction data

[1212] Specific operation: The device periodically collects transaction data from the connected electronic payment service and bank account. This transaction data is encrypted in JSON format and sent to the server. The server stores the data in Google Cloud Firestore.

[1213] Step 4:

[1214] The device collects user behavioral and voice data, which is then analyzed by the emotion engine.

[1215] Input: User behavior data (frequency of use, input patterns) and voice data

[1216] Output: User's emotional state data

[1217] How it works: The device uses OpenCV and Google Cloud Speech-to-Text to collect user behavior and voice data in real time. The emotion engine analyzes this data and determines the user's emotional state. This data is then sent to the server.

[1218] Step 5:

[1219] The server analyzes the transaction data and emotion data and generates a life plan.

[1220] Input: Collected transactional and sentiment data

[1221] Output: Generated life plan

[1222] How it works: The server uses generative artificial intelligence (AI) with TensorFlow to analyze transaction data and evaluate the user's financial situation. It then generates an optimal life plan based on emotional data. This life plan is then stored in Google Cloud Firestore.

[1223] Step 6:

[1224] The server predicts future economic conditions and proposes specific action plans.

[1225] Input: Generated life plan and past data

[1226] Output: A concrete action plan

[1227] Specific operation: The server predicts future economic conditions based on the analysis results and big data. Generative AI generates a specific action plan to achieve the user's goals and provides it to the user in an actionable form.

[1228] Step 7:

[1229] The server adjusts the suggestions to be less stressful based on the emotional data and notifies the device.

[1230] Input: Specific action plans and emotional data

[1231] Output: Notification of adjusted action plan

[1232] What it does: The server takes into account the emotion data and adjusts the action plan to make it less stressful for the user. The adjusted action plan is then sent to the device as a push notification or in-app message. Notifications are sent using Firebase Cloud Messaging (FCM).

[1233] Step 8:

[1234] The device presents the suggestions to the user and receives feedback.

[1235] Input: Coordinated Action Plan

[1236] Output: User feedback

[1237] What it does: The device displays the recommended action plan to the user. The user reviews the proposal and makes any necessary adjustments or comments. The collected feedback is then sent to the server.

[1238] Step 9:

[1239] The server analyzes the feedback and optimizes the life plan.

[1240] Input: User feedback and existing life plans

[1241] Output: Optimized Life Plan

[1242] How it works: The server analyzes the user's feedback and regenerates and optimizes the life plan based on it. The generative AI works with the feedback information to create and save the latest life plan.

[1243] These steps allow users to better manage their financial situation and implement optimal life plans that take into account their emotional state.

[1244] 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.

[1245] 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.

[1246] 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.

[1247] [Fourth embodiment]

[1248] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1249] 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.

[1250] 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).

[1251] 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.

[1252] 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.

[1253] 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).

[1254] 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.

[1255] 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.

[1256] 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.

[1257] 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.

[1258] 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.

[1259] 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.

[1260] 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."

[1261] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and then proposes specific action plans to users.

[1262] System Overview

[1263] This system consists of a "terminal" that collects data on income and expenses, a "server" that analyzes the collected data and creates a life plan, and a "server" that receives feedback from users and performs optimization.

[1264] Program processing

[1265] 1. Data Collection

[1266] Users create an account and link their electronic payment service and bank account information to the system.

[1267] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[1268] 2. Data Analysis

[1269] The server stores the received income and expenditure data in a database and analyzes it using generative artificial intelligence.

[1270] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan.

[1271] 3. Predictions and Recommendations

[1272] The server predicts future economic conditions based on the analysis results of generative artificial intelligence.

[1273] The server generates a specific action plan based on the prediction results and transmits it to the terminal.

[1274] The device will display the suggestions to the user via push notifications or in-app messages.

[1275] 4. Feedback and optimization

[1276] The user reviews the suggestions and enters any necessary changes or feedback into the device.

[1277] The terminal sends feedback information to the server.

[1278] The server optimizes the life plan based on the feedback and generates and sends new proposals.

[1279] Specific examples

[1280] Example: Goal to buy a house in 3 years

[1281] 1. A user downloads the app and creates an account.

[1282] 2. The user connects their electronic payment service and bank account information.

[1283] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[1284] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1285] 5. The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[1286] 6. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[1287] 7. The device notifies the user of the proposal and presents a feasible plan.

[1288] 8. The user reviews the proposal and makes adjustments as needed.

[1289] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[1290] In this way, users can manage their income and expenses through the system and implement realistic action plans to achieve their future goals. This system reduces users' financial worries and allows them to plan their lives with greater peace of mind.

[1291] The processing flow will be explained below.

[1292] Step 1:

[1293] A user downloads the app and creates an account.

[1294] The user authenticates and configures the settings to link electronic payment services and bank account information.

[1295] Step 2:

[1296] The terminal periodically acquires transaction data from the linked electronic payment service and bank account.

[1297] The terminal encrypts and stores the acquired transaction data and periodically transmits it to the server.

[1298] Step 3:

[1299] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[1300] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[1301] Step 4:

[1302] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[1303] The server uses past data and big data to predict future economic conditions.

[1304] Step 5:

[1305] The server generates a specific action plan based on the prediction results.

[1306] The server transmits the generated action plan to the terminal.

[1307] Step 6:

[1308] The device will display the suggestions to the user via push notifications or in-app messages.

[1309] The user reviews the proposal and enters any necessary changes or feedback.

[1310] Step 7:

[1311] The terminal transmits feedback information from the user to the server.

[1312] The server reanalyzes and optimizes your life plan based on the collected feedback.

[1313] Step 8:

[1314] The server generates an optimized life plan and new proposals.

[1315] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[1316] In this way, a system is created that continuously collects and analyzes income and expenditure information, and provides users with feedback and suggestions to help them achieve their goals.

[1317] Example 1

[1318] 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."

[1319] In recent years, it has become increasingly important to effectively utilize personal income and expenditure information to specifically plan future life plans. However, current systems do not effectively coordinate data collection, encryption, analysis, and recommendations, and are insufficiently optimized to reflect user feedback. Ensuring safety and efficiency are also issues. To address these issues, a system is needed that efficiently collects and securely transmits income and expenditure data, creates high-quality life plans using generative AI models, and predicts users' future financial situations.

[1320] 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.

[1321] In this invention, the server includes: means for a user to create an account and link with product and service providers; means for periodically acquiring income and expenditure measurement data based on link information via a terminal, encrypting the data, and transmitting the encrypted data to the server; means for the server to analyze the income and expenditure data using a generative AI model and create a life plan; means for predicting future economic conditions based on the created life plan; means for generating a specific action plan based on the prediction results and proposing it to the user via the terminal; and means for collecting user feedback and optimizing the life plan. This makes it possible to analyze the user's income and expenditure in detail, accurately predict future economic conditions, and provide a realistic and specific action plan.

[1322] "User" refers to an individual who uses the system to input income and expense information and receive a financial forecast and suggested action plan.

[1323] "Terminal" refers to a device used by a user that acquires income and expenditure transaction data, encrypts it, and transmits it to a server.

[1324] "Server" refers to the computer system that stores collected income and expenditure data, analyzes the data using generative AI models, and creates and provides life plans.

[1325] "Income and Expense Measure Data" means data that includes transaction information related to a user's income and expenses.

[1326] "Linked information" refers to information related to a user's income and expenditures that is shared with electronic payment services and financial institutions.

[1327] "Generative AI model" refers to an artificial intelligence model that analyzes income and expenditure data to create and optimize life plans.

[1328] "Life Plan" refers to future financial plans and goals created based on a user's income and expenditure data.

[1329] An "action plan" refers to a plan based on the user's life plan that includes proposals for specific income and expenditure management methods, investment plans, etc.

[1330] "Feedback" refers to opinions and requests for corrections made by users regarding the proposed action plan.

[1331] "Encryption" refers to the process used to protect collected income and expense data from being read by third parties.

[1332] To implement this invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using a generative AI model, predicts future economic conditions, and then proposes specific action plans to users.

[1333] System Overview

[1334] The system consists of three main components:

[1335] 1. Terminal: A device used by a user that collects income and expenditure transaction data, encrypts it, and sends it to a server.

[1336] 2. Server: Analyzes the collected income and expenditure data and creates a life plan using a generative AI model. It also predicts future economic situations and generates specific action plans.

[1337] 3. User: A user of the system who creates an account, enters income and expense information, and implements the proposed action plan.

[1338] Hardware and Software Configuration

[1339] 1. Devices: Use mobile devices such as smartphones and tablets. These devices require API access to collect income and expenditure data. Specifically, use APIs provided by major electronic payment services and financial institutions.

[1340] 2. Server: A high-performance computer system that requires software to run the generative AI model and a database management system (e.g., MySQL or PostgreSQL), using a deep learning framework such as TensorFlow or PyTorch.

[1341] Specific examples

[1342] As an example, we will show how the system works when you set a goal of buying a house in three years.

[1343] 1. A user downloads the system app and creates an account.

[1344] 2. The user connects their electronic payment service and bank account information.

[1345] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[1346] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1347] 5. The server analyzes the data received and creates an income and expenditure plan to save 30 million yen in three years.

[1348] 6. The server generates a proposal for the amount of savings needed each month and items of expenses that can be reduced (for example, reducing monthly eating out expenses by 20,000 yen).

[1349] 7. The device notifies the user of the proposal and presents a feasible plan.

[1350] 8. The user reviews the proposal and makes adjustments as needed.

[1351] 9. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[1352] Through this collaboration, the system will efficiently manage users' income and expenses, accurately predict their future financial situation, and provide realistic action plans to help them achieve their life plans.

[1353] Prompt Sentence Examples

[1354] "Based on your income and expenditure data, generate a concrete action plan to purchase a 30 million yen house in three years."

[1355] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1356] Step 1:

[1357] The user creates an account and links their electronic payment service and bank account information to the system. The user downloads the system's app and creates an account by entering basic information such as name, email address, and password. Next, they link their electronic payment service and bank account information to the system and allow API access. Input: Basic information, linked information. Output: Notification of account creation completion, registration of linked information.

[1358] Step 2:

[1359] Based on the linked information, the device periodically obtains income and expenditure transaction data, encrypts it, and sends it to the server. The device periodically (e.g. daily or weekly) accesses the API of financial institutions and electronic payment services to obtain the latest income and expenditure transaction data. The obtained data is encrypted using an encryption algorithm such as AES256. Input: Linkage information, transaction data. Output: Encrypted transaction data.

[1360] Step 3:

[1361] The server stores the received income and expenditure data in a database and analyzes it using a generative AI model. The server receives encrypted transaction data from the terminal and stores it in a database. The generative AI model is then used to analyze the data and understand the user's income and expenditure patterns. Input: Encrypted transaction data. Output: Analysis results, user's income and expenditure patterns.

[1362] Step 4:

[1363] Based on the analysis results, the server evaluates the user's current financial situation and creates a life plan. The server evaluates the user's income and expenditure patterns from the analysis results and uses a generative AI model to create an optimal life plan. For example, a specific plan can be created based on the user's goals for the future (e.g., buying a house, saving for their children's education). Input: Analysis results, user goals. Output: Life plan.

[1364] Step 5:

[1365] The server uses the generated AI model to predict future economic conditions based on the life plan. The server predicts future economic conditions based on the user's income, expenditures, and savings plans described in the life plan. For example, it also takes into account income growth cycles and the risk of unexpected expenditures. Input: Life plan. Output: Future economic situation prediction results.

[1366] Step 6:

[1367] The server generates a specific action plan based on the prediction results and sends it to the device. The server generates specific actions that the user should take (e.g., monthly savings amount, which items to cut spending on) based on the future economic situation prediction results and sends it to the device. Input: Future economic situation prediction results. Output: Action plan.

[1368] Step 7:

[1369] The device notifies the user of the proposed action plan and presents an actionable plan. The device displays the action plan received from the server to the user and informs them of the proposed action plan via push notification or in-app message. The user reviews the displayed plan and considers what can be done. Input: Action plan. Output: Notification to user, presentation of action plan.

[1370] Step 8:

[1371] The user reviews the proposal and inputs any necessary changes or feedback into the device. The user reviews the proposed action plan, makes any necessary changes to suit their own living situation, and inputs feedback into the device. Input: Feedback, changes. Output: Feedback information.

[1372] Step 9:

[1373] The device sends feedback information to the server, which then optimizes the life plan based on this. The device sends feedback information received from the user to the server, which updates the generative AI model to optimize the life plan. This generates new proposals and presents them to the user again. Input: Feedback information. Output: Optimized life plan.

[1374] (Application example 1)

[1375] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1376] In modern society, understanding one's financial situation and establishing a future life plan are extremely important. However, many people find it difficult to properly manage their income and expenses and predict their future financial situation. In particular, creating a specific action plan and implementing it is not easy. Furthermore, there is a lack of a system that allows users to review proposals and provide feedback to continuously optimize their life plans.

[1377] 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.

[1378] In this invention, the server includes means for collecting income and expenditure information, means for using generative artificial intelligence to create a life plan based on the income and expenditure information, means for predicting future economic conditions based on the life plan created by the generative artificial intelligence, means for proposing a specific action plan based on the predicted economic conditions, and means for notifying the user of the specific action plan. This allows the user to create a specific life plan based on income and expenditure information and predict future economic conditions. Furthermore, by proposing specific action plans to the user and incorporating their feedback, the life plan can be continuously optimized.

[1379] "Income and Expense Information" means all data relating to the sources of income and related expenses of an individual or legal entity.

[1380] "Means of collecting income and expenditure information" refers to mechanisms for collecting transaction data from electronic payment services and financial institutions.

[1381] "Means of using generative artificial intelligence to create a life plan based on the income and expenditure information" refers to a system that uses generative artificial intelligence to analyze collected economic data and automatically create a future life plan.

[1382] "Means for predicting future economic conditions based on a life plan created by the generative artificial intelligence" refers to a mechanism for predicting future income and expenditures based on a life plan created by the generative artificial intelligence.

[1383] "Means for proposing a specific action plan based on the predicted economic situation" refers to a mechanism for presenting a specific, feasible economic action plan to a user based on the results of a prediction of future economic conditions.

[1384] The term "means for notifying the user of the specific action plan" refers to a notification means for effectively communicating the generated action plan to the user.

[1385] "Collecting transaction data in cooperation with electronic payment services and financial institution information" refers to automatically obtaining user transaction data in cooperation with electronic payment systems and bank account information.

[1386] "Collecting user feedback and optimizing the life plan" refers to the process of collecting opinions and impressions from users and refining and improving the life plan based on them.

[1387] A "generative AI model" refers to an artificial intelligence system that learns patterns and relationships from given data and generates predictions and suggestions.

[1388] A "prompt sentence" is a sentence that is input into a generative AI model and is text data that serves as a guideline for the subsequent analysis and generation process.

[1389] To put this invention into practice, it is necessary to build a system that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, and proposes specific action plans to users. This system is composed of a terminal that collects data on income and expenditure, a server that analyzes the collected data and creates a life plan, and a server that receives feedback from users and performs optimization.

[1390] First, a user creates an account and connects their electronic payment service and financial institution information to the system. Through this connection, transaction data is periodically collected, encrypted, and sent to a server. The server then analyzes the collected data using generative artificial intelligence, evaluates the user's current financial situation, and creates a life plan.

[1391] Specifically, the server sends the following prompt to the generative AI to analyze the data:

[1392] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[1393] Next, the server predicts future economic conditions based on the analysis results of the generative AI. Based on this prediction, the server generates a specific action plan and sends it to the device. The device then displays the proposal to the user via push notifications or in-app messages.

[1394] The user reviews the proposal and enters any necessary changes or feedback into the device, which then sends the feedback to the server. The server then optimizes the life plan based on the user's feedback and generates and sends a new proposal. Through this series of processes, the user can manage their income and expenses through the system and implement a realistic action plan to achieve their future goals.

[1395] The hardware and software used in realizing this invention include a server for managing collected data, computer resources for executing generative artificial intelligence models, and a smartphone or PC as a user interface. Specific software includes a generative artificial intelligence API (e.g., OpenAI's GPT-3) and a standard protocol for encrypting and transferring data (e.g., SSL / TLS).

[1396] For example, if a user sets a goal of "buying a house in three years," the system will propose a savings plan based on the user's transaction data for the next three years, and provide specific suggestions for reducing monthly dining out expenses, etc. Based on these suggestions, the user can adjust their daily economic activities and implement a plan to achieve their goal.

[1397] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1398] Step 1:

[1399] The terminal creates a user account and configures the connection to electronic payment services and financial institution information. As input, the user's account information and bank account information are required, which are used for API connection to obtain encrypted transaction data. As output, the terminal establishes the source information of the data to be collected and sets the trigger for data collection based on this.

[1400] Step 2:

[1401] The terminal periodically retrieves transaction data from electronic payment services and financial institutions, encrypts it, and sends it to the server. As input, the user's bank account and electronic payment service authentication information are required, and the retrieved transaction data is encrypted and sent to the server. As output, the transaction data is retrieved on the server side and prepared for analysis.

[1402] Step 3:

[1403] The server stores the collected transaction data in a database and analyzes the income and expenditure data using a generative AI model. The inputs are encrypted transaction data and a generative AI model for analysis, which analyzes income and expenditure patterns based on the transaction data stored in the database. The output is an assessment of the user's current financial situation.

[1404] Step 4:

[1405] The server creates a life plan based on the analysis results obtained using the generative AI model and predicts future economic situations. The evaluation results obtained in step 3 and the generative AI model are required as input, and the life plan and economic prediction are made by inputting a prompt statement into the generative AI model. As a specific example, the following text is used as the prompt statement:

[1406] "User Income and Expense Data: {Collected Data} Evaluate the user's current financial situation and suggest a future income and expenditure plan."

[1407] As output, a predicted outcome and a life plan are generated.

[1408] Step 5:

[1409] The server generates a specific action plan based on the prediction of future economic conditions and sends the details to the device. The server requires a life plan and economic prediction results as input, and uses a generative AI model to generate an action plan, including specific items to cut and savings plans. The specific action plan is sent to the device as output.

[1410] Step 6:

[1411] The device notifies the user of a specific action plan. As input, it requires the action plan received from the server, and displays the proposal to the user using push notifications or in-app messages. As output, the user reviews the proposal and enters any necessary changes or feedback.

[1412] Step 7:

[1413] The user checks the proposal and enters the necessary feedback into the terminal. The input requires an action plan and the user's opinions and impressions, which are entered into the terminal and sent to the server. The output is the user's feedback, which is reflected in the server.

[1414] Step 8:

[1415] The server optimizes the life plan based on the user's feedback and generates and transmits new proposals. The server requires the user's feedback and existing life plan as input, and reevaluates and optimizes the life plan based on the feedback. The server outputs the optimized new life plan and action plan to the device.

[1416] 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.

[1417] To implement the present invention, a series of systems is constructed that collects income and expenditure information, creates a life plan based on that information using generative artificial intelligence, predicts future economic conditions, proposes specific action plans to users, and further recognizes the user's emotions using an emotion engine to optimize the proposals and life plans.

[1418] System Overview

[1419] The system consists of the following elements:

[1420] 1. Terminal: Provides a means of collecting data on income and expenditures and incorporates an emotion engine that recognizes the user's emotions.

[1421] 2. Server: Analyzes the collected data, creates a life plan using generative AI, predicts future economic situations, and incorporates data from the emotion engine to optimize the recommendations.

[1422] 3. User: Create an account, connect electronic payment services and bank account information, and provide emotional data.

[1423] Program processing

[1424] 1. Data Collection

[1425] A user downloads the app and creates an account.

[1426] The user authenticates and configures the settings for linking electronic payment services and bank account information.

[1427] Based on this link information, the terminal periodically acquires income and expenditure transaction data, encrypts it, and sends it to the server.

[1428] 2. Emotion recognition

[1429] The device collects data on the user's behavior on the digital device (e.g., frequency of use, input patterns) and voice data.

[1430] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[1431] The terminal transmits the recognized emotion data to the server.

[1432] 3. Data Analysis

[1433] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories.

[1434] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[1435] 4. Predictions and Recommendations

[1436] Based on the analysis results, the server creates a life plan to help the user achieve their goals.

[1437] The server uses past data and big data to predict future economic conditions.

[1438] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[1439] The server transmits the generated action plan to the terminal.

[1440] 5. Feedback and optimization

[1441] The device will display the suggestions to the user via push notifications or in-app messages.

[1442] The user reviews the proposal and enters any necessary changes or feedback.

[1443] The terminal transmits feedback information from the user to the server.

[1444] The server reanalyzes and optimizes the life plan based on the collected feedback and emotional state.

[1445] Specific examples

[1446] Example: Goal of buying a house in 3 years and emotion recognition

[1447] 1. A user downloads the app and creates an account.

[1448] 2. The user connects their electronic payment service and bank account information.

[1449] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[1450] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1451] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[1452] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[1453] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[1454] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[1455] 9. The device notifies the user of the proposal and presents a feasible plan.

[1456] 10. User reviews the proposal and makes adjustments as needed.

[1457] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[1458] In this way, a system is realized that continuously manages the user's income and expenses and supports goal achievement through suggestions that take into account the user's emotional state, reducing financial anxiety and enabling users to plan their lives with emotional peace of mind.

[1459] The processing flow will be explained below.

[1460] Step 1:

[1461] A user downloads the app and creates an account.

[1462] The user authenticates and configures the electronic payment service and bank account information.

[1463] Step 2:

[1464] The device periodically retrieves income and expenditure transaction data from linked electronic payment and bank accounts.

[1465] The terminal encrypts the acquired transaction data and transmits it to the server.

[1466] Step 3:

[1467] The server stores the received transaction data in a database and categorizes it into income and expense categories.

[1468] The server uses generative artificial intelligence to analyze the collected data and assess the user's current financial situation.

[1469] Step 4:

[1470] The device collects behavioral and voice data from users' digital devices.

[1471] An emotion engine built into the device analyzes the collected data and recognizes the user's emotional state.

[1472] The terminal transmits the recognized emotion data to the server.

[1473] Step 5:

[1474] The server creates a life plan based on the analysis results to help the user achieve their goals.

[1475] The server uses past data and big data to predict future economic conditions.

[1476] Step 6:

[1477] The server generates a specific action plan based on the predicted results and the recognized emotional state.

[1478] The server transmits the generated action plan to the terminal.

[1479] Step 7:

[1480] The device will display the suggestions to the user via push notifications or in-app messages.

[1481] The user reviews the proposal and provides any necessary changes or feedback.

[1482] Step 8:

[1483] The terminal transmits feedback information from the user to the server.

[1484] The server reanalyzes and optimizes the life plan based on the collected feedback and perceived emotional state.

[1485] Step 9:

[1486] The server generates an optimized life plan and new proposals.

[1487] The server sends the new proposal content to the terminal, and the terminal notifies the user again.

[1488] In this way, a system is built that continuously collects and analyzes income and expenditure information, and provides feedback and suggestions to users to help them achieve their goals. Furthermore, by providing suggestions that take into account the user's emotional state, it is possible to reduce financial anxiety and enable them to plan their lives with emotional peace of mind.

[1489] Example 2

[1490] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1491] In recent years, personal financial management has become increasingly demanding, requiring users to predict their future financial situation based on income and expenditure information and provide beneficial action plans. However, existing systems have not taken the user's emotional state into account when making proposals, and the proposed plans are not necessarily easy for users to implement. Furthermore, they lack the functionality to efficiently incorporate user feedback and optimize life plans. This has resulted in reduced user satisfaction and feasibility, preventing effective financial management.

[1492] 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.

[1493] In this invention, the server includes: a means for a user to create an account and link their electronic payment service and bank account information; a means for periodically acquiring and encrypting income and expenditure transaction data based on the linked information and transmitting the encrypted data to the server; a means for collecting behavioral patterns and voice data from the user's digital device and using an emotion engine to recognize emotions; a means for transmitting data recognized by the emotion engine to the server; a means for storing and classifying the transaction data and emotion data received by the server; a means for analyzing the collected data using generative artificial intelligence to evaluate the user's current financial situation; a means for creating a life plan based on the analysis results and predicting future financial circumstances; a means for generating a specific action plan based on the prediction results and the user's emotional state and transmitting the plan to the terminal; a means for notifying the user of the generated action plan and collecting feedback; and a means for reanalyzing and optimizing the life plan based on the feedback and the user's emotional state. This enables the system to effectively manage the user's income and expenditure data and provide a feasible action plan that takes the user's emotional state into account. Furthermore, optimizing the life plan based on the user's feedback improves the satisfaction and feasibility of the user's financial management.

[1494] "User" means any person or entity that utilizes the System to provide income and expense information and manage their own financial affairs.

[1495] "Device" refers to a digital device used by a user, such as a computer, smartphone, or tablet, that collects income and expenditure data and information for emotion recognition.

[1496] "Server" refers to a computer system that analyzes, stores, and categorizes collected data and uses generative artificial intelligence to create life plans and predict future economic situations.

[1497] "Income" means any financial gain earned by a User, including salary, bonuses, investment income, etc.

[1498] "Expenses" refers to financial expenses that a user uses for consumption or investment, including food, rent, entertainment, etc.

[1499] "Transaction Data" refers to detailed information about income and expenditure collected through electronic payment services and bank accounts.

[1500] An "emotion engine" refers to technology that analyzes data collected from a user's digital device (behavioral patterns, voice data, etc.) and recognizes the user's emotional state.

[1501] "Generative AI" refers to artificial intelligence technology that creates and optimizes users' life plans based on collected data, and specifically includes machine learning models and data analysis algorithms.

[1502] "Life Plan" refers to a plan for achieving future financial goals that is created using generative artificial intelligence based on a user's income and expenditure data.

[1503] "Action plan" refers to a specific action plan proposed to a user based on a life plan and emotional data created by generative artificial intelligence.

[1504] "Feedback" refers to evaluations, comments, correction requests, etc. provided by users regarding proposed action plans.

[1505] The present invention provides a series of systems that collect income and expenditure information, use generative artificial intelligence to create a life plan based on that information, predict future economic situations, and propose specific action plans to users. The system of the present invention is characterized by further recognizing the user's emotions using an emotion engine and optimizing the proposals and life plan. This system is implemented using the following hardware and software.

[1506] 1. Hardware Elements

[1507] Device: A digital device used by a user, including a smartphone, tablet, or computer. These devices collect income and expenditure data and recognize the user's emotional state through an emotion engine.

[1508] Server: A computer system that analyzes, stores, and classifies data to generate and optimize life plans. This can be a cloud server or an on-premise server.

[1509] 2. Software Elements

[1510] Generative artificial intelligence (AI): AI techniques used to analyze collected data and generate life plans. Examples include machine learning models and data analysis algorithms implemented in Python or R.

[1511] Emotion engine: A technology that recognizes emotions by analyzing the behavioral patterns and voice data of users' digital devices. It uses natural language processing (NLP) and voice analysis technology.

[1512] 3. Data processing and calculation

[1513] Data collection: The user creates an account and links their electronic payment service and bank account information. Based on this information, the device periodically collects transaction data, encrypts it, and sends it to the server.

[1514] Data Analysis and Classification: The server stores the received transaction data and sentiment data in a database and categorizes them into income and expenditure categories. Generative artificial intelligence is used to analyze the collected data and evaluate the user's current financial situation.

[1515] Prediction and proposal: The server creates a life plan based on the analysis results and predicts the user's future economic situation. Based on the prediction results and the user's emotional state, the server generates a specific action plan and sends it to the device.

[1516] 4. Example of a system

[1517] Example: The system operates based on prompts such as, "I am a 30-year-old office worker with an annual income of 5 million yen. My goal is to purchase a house worth 30 million yen in three years. Please record your current monthly income and expenses in detail and tell me a specific action plan for purchasing a house. Also, since I have a lot of stress at work, please include suggestions to reduce the stress."

[1518] A user downloads the app and creates an account.

[1519] The user connects their electronic payment service and bank account information and sets a goal of "buying a house worth 30 million yen in three years."

[1520] Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1521] The device collects behavioral and voice data from the user's digital devices, and the emotion engine analyzes this to recognize the user's emotional state.

[1522] The server analyzes the data and creates an income and expenditure plan to save 30 million yen in three years.

[1523] The server suggests the amount of savings needed each month and items of expenditure that can be reduced, and generates an optimized plan that takes emotional data into account.

[1524] The device will notify the user of the proposal and present a feasible plan.

[1525] The user reviews the proposal and makes adjustments as needed.

[1526] The server will optimize your life plan based on the feedback and continue to make specific suggestions.

[1527] In this way, a system that continuously manages a user's income and expenses and supports goal achievement through suggestions that take emotional state into account is realized. Users can safely and effectively manage their financial situation and plan their lives with peace of mind.

[1528] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1529] Step 1:

[1530] A user downloads an app and creates an account. As input, the user provides an email address and password, and the system sends an authentication code. The user enters the authentication code and an account is created. As output, the user account is created and the user remains logged in. In concrete terms, after installing the app, the user accesses the login screen and enters the required information.

[1531] Step 2:

[1532] The user links their electronic payment service and bank account information. As input, the user provides authentication information for each service (user ID, password, etc.). The system authenticates this information via OAuth 2.0 or API and executes the linking. As output, the system completes the linking process, allowing it to securely obtain the user's transaction data. Specifically, the user selects the linking option on the app's settings screen and enters the required authentication information.

[1533] Step 3:

[1534] The terminal periodically retrieves transaction data, encrypts it, and sends it to the server. The input includes data on the electronic payment service and bank account linked by the user. The data is encrypted using an encryption algorithm (e.g., AES-256) and sent to the server using a secure communication protocol (HTTPS). The output is the encrypted transaction data stored on the server. Specifically, the terminal sends an API request, retrieves and encrypts the transaction data, and sends it to the server.

[1535] Step 4:

[1536] The device collects behavioral patterns and voice data from the user's digital device. Input includes the user's frequency of device use, input patterns, and voice data from the microphone. This data is processed locally and temporarily recorded. As output, the collected data is input into the emotion engine. Specifically, the device collects data using the device's sensors and microphone.

[1537] Step 5:

[1538] The emotion engine built into the device analyzes the collected data and recognizes the user's emotional state. The input includes the behavioral patterns and voice data collected in the previous step. Natural language processing (NLP) and voice analysis techniques are used to analyze the data and evaluate the user's emotional state. The output is the recognized emotion data. Specifically, the emotion engine performs data analysis in real time.

[1539] Step 6:

[1540] The device sends the recognized emotion data to the server. The input includes the emotion data output by the emotion engine. This is also encrypted and sent to the server using a secure communication protocol. The output is the emotion data stored on the server. Specifically, the device encrypts the data and issues a request to send it to the server.

[1541] Step 7:

[1542] The server stores the received transaction data and emotion data in a database and categorizes them into income and expense categories. The input includes encrypted transaction data and emotion data. A database query is executed for storage and categorization in the database. The output is the classified data stored in the database. Specifically, the server issues a database query to store and categorize the data.

[1543] Step 8:

[1544] The server uses generative artificial intelligence to analyze the collected data and evaluate the user's current financial situation. Input includes transaction data and emotion data stored in a database. The generative artificial intelligence model analyzes the data and generates an evaluation of the user's financial situation. The output is the analysis result. Specifically, the server runs the AI ​​model and analyzes the data.

[1545] Step 9:

[1546] The server creates a life plan for the user's goal setting based on the analysis results. The input includes the analysis results of the financial situation and the user's goal information. The algorithm for creating the life plan is executed, and the plan is generated. The output is the generated life plan. Specifically, the server executes the life plan creation algorithm and outputs the results.

[1547] Step 10:

[1548] The server uses past data and big data to predict future economic conditions. Inputs include life plan data and past big data. A machine learning model (e.g., regression analysis or time series analysis model) is used. Outputs include predicted data for economic conditions. Specifically, the server executes the machine learning model to obtain prediction results.

[1549] Step 11:

[1550] The server generates a specific action plan based on the prediction results and emotional state and sends it to the terminal. The input includes predicted data on the economic situation and data on the emotional state. The generative artificial intelligence model creates an action plan based on this data. The output is an action plan that is generated and sent to the terminal. Specifically, the server runs the action plan generation algorithm and sends the results to the terminal.

[1551] Step 12:

[1552] The device sends a notification to the user and presents the suggestion. The input includes the data of the action plan to be notified. The user is notified using a push notification or an in-app message. The output is the suggestion displayed to the user. Specifically, the device uses the notification API to send a message to the user.

[1553] Step 13:

[1554] The user reviews the suggestions and provides any necessary changes or feedback. The input includes the feedback information provided by the user. The feedback is entered using an in-app form or button. The output is feedback data. The specific behavior is that the user fills out a feedback form within the app.

[1555] Step 14:

[1556] The terminal sends user feedback information to the server. The input includes feedback data from the user. The feedback data is encrypted and sent to the server using a secure communication protocol. The output is stored in the server. As a specific operation, the terminal issues a request to encrypt the data and send it to the server.

[1557] Step 15:

[1558] The server reanalyzes and optimizes the life plan based on the feedback and emotional state. The input includes feedback data and emotional data. The generative artificial intelligence model reanalyzes and optimizes the life plan based on this data. The output is an optimized life plan. Specifically, the server runs the reanalysis algorithm and outputs the results.

[1559] (Application example 2)

[1560] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1561] Conventional life planning systems are limited to simple predictions and suggestions based on income and expenditure information, and therefore are unable to provide optimal action plans that take into account the user's emotional state. As a result, users may feel stressed by the suggestions, reducing their feasibility. To address this issue, a system is needed that not only collects income and expenditure data but also recognizes the user's emotional state and provides optimized suggestions.

[1562] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1563] In this invention, the server includes means for collecting income and expenditure information, means for creating a life plan using generative artificial intelligence, means for recognizing the user's emotional state using an emotion engine and optimizing the proposals and life plan, means for proposing a specific action plan based on the user's future economic situation, and means for displaying the proposals to the user using push notifications or in-app messages. This makes it possible to provide a less stressful action plan that takes the user's emotional state into consideration and increase the feasibility of the plan.

[1564] "Income information" refers to earnings such as salary earned by a user from work or profits from investments.

[1565] "Expense information" is data related to the money consumed by the user, including living expenses, leisure expenses, etc.

[1566] A "life plan" is a plan that predicts a user's future income and expenses and helps them achieve specific financial goals.

[1567] "Generative artificial intelligence" refers to artificial intelligence technology that generates new information based on collected data and makes predictions and suggestions.

[1568] "Future financial situation" refers to the user's future financial situation as predicted based on the collected data.

[1569] An "action plan" is a plan of specific actions to be taken in order to achieve a set goal.

[1570] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state.

[1571] "Electronic payment service" refers to a service that allows users to conduct transactions over the Internet.

[1572] "Bank Account Information" refers to details about a user's bank account.

[1573] "Transaction Data" refers to records of financial transactions conducted by Users.

[1574] "Push notification" refers to a notification sent from an application to a user's device in real time.

[1575] "Feedback" refers to the reactions and opinions of users regarding proposals and plans.

[1576] "Optimization" refers to improving life plans and proposals based on collected data and feedback.

[1577] The present invention is a system that collects income and expenditure data, creates a life plan that takes into account the user's emotional state, and proposes an optimal action plan. Specific embodiments of the system will be described below.

[1578] System configuration

[1579] The system consists of the following elements:

[1580] 1. Terminal

[1581] 2. Server

[1582] 3. Users

[1583] 1. Terminal

[1584] The terminal is a digital device such as a smartphone or tablet that provides a means to collect a user's income and expenditure information. The terminal also incorporates an emotion engine that can recognize the user's emotional state. The engine analyzes user behavior and voice data using OpenCV and Google Cloud Speech-to-Text.

[1585] 2. Server

[1586] The server analyzes the collected data and generates a life plan using generative artificial intelligence. It also incorporates emotional data recognized by the emotion engine to optimize the recommendations. The server is built on Django and uses Google Cloud Firestore to store data. It also uses a TensorFlow model for generative artificial intelligence and Dialogflow for natural language generation.

[1587] 3. Users

[1588] Users download the app, create an account, and link their electronic payment service and bank account information. This allows transaction data to be collected periodically. Users can review the life plan and specific proposals and enter feedback. This feedback is then sent back to the server and used to optimize the plan.

[1589] Specific examples

[1590] Achieving the goal of buying a house in three years

[1591] 1. A user downloads the app and creates an account.

[1592] 2. The user connects their electronic payment service and bank account information.

[1593] 3. The user sets a goal of "buying a house worth 30 million yen in three years."

[1594] 4. Based on the information linked to the device, daily income and expenditure data is collected and sent to the server.

[1595] 5. The device collects the user's digital device behavior and voice data, and the emotion engine analyzes this to recognize the user's emotional state.

[1596] 6. The server analyzes the data and creates a budget to save 30 million yen in three years.

[1597] 7. The server generates suggestions for the amount of savings needed per month and items of expenses that can be reduced (e.g., reducing monthly eating out expenses by 20,000 yen).

[1598] 8. The server takes into account the emotional data and adjusts the suggestions to make them less stressful for the user.

[1599] 9. The device notifies the user of the proposal and presents a feasible plan.

[1600] 10. User reviews the proposal and makes adjustments as needed.

[1601] 11. The server will optimize your life plan based on your feedback and continue to make specific suggestions.

[1602] Prompt Sentence Examples

[1603] "Create a plan to purchase a house worth 30 million yen in three years. Suggest a specific action plan for managing income and expenses necessary to achieve this, and choose the optimal method taking into account the user's emotional state."

[1604] This invention makes it possible to provide a low-stress life plan that takes into account the user's emotional state through a detailed analysis of the user's financial situation, thereby providing a specific and feasible action plan for achieving goals and improving user satisfaction.

[1605] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1606] Step 1:

[1607] A user downloads the app and creates an account.

[1608] Input: App download and account creation information

[1609] Output: User's account

[1610] Specific operation: A user downloads and installs the app. Then, the user enters the required information on the account creation screen and creates an account. During this process, the user enters information such as an email address and password, and is authenticated using Google Firebase Authentication.

[1611] Step 2:

[1612] The user connects their electronic payment service and bank account information.

[1613] Input: User's electronic payment service and bank account information

[1614] Output: User transaction data acquisition settings

[1615] How it works: Users link their electronic payment service and bank account through the app's settings screen. The Plaid API is used to connect to the bank account, and the app is set up to periodically retrieve the user's transaction data.

[1616] Step 3:

[1617] The terminal collects income and expenditure data and transmits it to a server.

[1618] Input: Transaction data from your electronic payment service and bank account

[1619] Output: Collected transaction data

[1620] Specific operation: The device periodically collects transaction data from the connected electronic payment service and bank account. This transaction data is encrypted in JSON format and sent to the server. The server stores the data in Google Cloud Firestore.

[1621] Step 4:

[1622] The device collects user behavioral and voice data, which is then analyzed by the emotion engine.

[1623] Input: User behavior data (frequency of use, input patterns) and voice data

[1624] Output: User's emotional state data

[1625] How it works: The device uses OpenCV and Google Cloud Speech-to-Text to collect user behavior and voice data in real time. The emotion engine analyzes this data and determines the user's emotional state. This data is then sent to the server.

[1626] Step 5:

[1627] The server analyzes the transaction data and emotion data and generates a life plan.

[1628] Input: Collected transactional and sentiment data

[1629] Output: Generated life plan

[1630] How it works: The server uses generative artificial intelligence (AI) with TensorFlow to analyze transaction data and evaluate the user's financial situation. It then generates an optimal life plan based on emotional data. This life plan is then stored in Google Cloud Firestore.

[1631] Step 6:

[1632] The server predicts future economic conditions and proposes specific action plans.

[1633] Input: Generated life plan and past data

[1634] Output: A concrete action plan

[1635] Specific operation: The server predicts future economic conditions based on the analysis results and big data. Generative AI generates a specific action plan to achieve the user's goals and provides it to the user in an actionable form.

[1636] Step 7:

[1637] The server adjusts the suggestions to be less stressful based on the emotional data and notifies the device.

[1638] Input: Specific action plans and emotional data

[1639] Output: Notification of adjusted action plan

[1640] What it does: The server takes into account the emotion data and adjusts the action plan to make it less stressful for the user. The adjusted action plan is then sent to the device as a push notification or in-app message. Notifications are sent using Firebase Cloud Messaging (FCM).

[1641] Step 8:

[1642] The device presents the suggestions to the user and receives feedback.

[1643] Input: Coordinated Action Plan

[1644] Output: User feedback

[1645] What it does: The device displays the recommended action plan to the user. The user reviews the proposal and makes any necessary adjustments or comments. The collected feedback is then sent to the server.

[1646] Step 9:

[1647] The server analyzes the feedback and optimizes the life plan.

[1648] Input: User feedback and existing life plans

[1649] Output: Optimized Life Plan

[1650] How it works: The server analyzes the user's feedback and regenerates and optimizes the life plan based on it. The generative AI works with the feedback information to create and save the latest life plan.

[1651] These steps allow users to better manage their financial situation and implement optimal life plans that take into account their emotional state.

[1652] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1653] 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.

[1654] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1655] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1656] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1657] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1658] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1659] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1660] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1661] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1662] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1663] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1664] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1665] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1666] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1667] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1668] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1669] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1670] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1671] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1672] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1673] The following is further disclosed regarding the above embodiment.

[1674] (Claim 1)

[1675] means of collecting income and expenditure information;

[1676] a means for using a generative artificial intelligence to create a life plan based on the income and expenditure information;

[1677] A means for predicting future economic situations based on the life plan created by the generative artificial intelligence;

[1678] a means for proposing a specific action plan based on the predicted economic situation;

[1679] A system including:

[1680] (Claim 2)

[1681] 10. The system of claim 1, wherein the system collects transaction data in conjunction with electronic payment services and bank account information.

[1682] (Claim 3)

[1683] 10. The system of claim 1, wherein the system collects user feedback and optimizes the life plan.

[1684] "Example 1"

[1685] (Claim 1)

[1686] A means for users to create accounts and connect with providers of goods and services;

[1687] a means for periodically acquiring measurement data of income and expenditure based on the linked information by the terminal, encrypting the data, and transmitting the data to the server;

[1688] A means for the server to analyze income and expenditure data using a generative AI model to create a life plan;

[1689] A means for predicting future economic situations based on the created life plan;

[1690] A means for generating a specific action plan based on the prediction result and proposing the plan to the user via the terminal;

[1691] A means of collecting user feedback and optimizing life plans;

[1692] A system including:

[1693] (Claim 2)

[1694] 10. The system of claim 1, wherein the system collects transaction data in cooperation with electronic transaction services and financial institution information.

[1695] (Claim 3)

[1696] The system according to claim 1, wherein secure data transmission is performed using a data encryption means, and the data stored on the server is analyzed using a generative AI model.

[1697] "Application Example 1"

[1698] (Claim 1)

[1699] means of collecting income and expenditure information;

[1700] a means for using a generative artificial intelligence to create a life plan based on the income and expenditure information;

[1701] A means for predicting future economic situations based on the life plan created by the generative artificial intelligence;

[1702] a means for proposing a specific action plan based on the predicted economic situation;

[1703] means for notifying a user of the specific action plan;

[1704] A system including:

[1705] (Claim 2)

[1706] 10. The system of claim 1, wherein the system collects transaction data in conjunction with electronic payment services and financial institution information.

[1707] (Claim 3)

[1708] 10. The system of claim 1, wherein the system collects user feedback and optimizes the life plan.

[1709] "Example 2: Combining Emotion Engines"

[1710] (Claim 1)

[1711] a means for users to create accounts and link electronic payment services and bank account information;

[1712] A means for periodically acquiring, encrypting, and transmitting transaction data of income and expenditure based on the linked information to a server;

[1713] A means for using an emotion engine that collects behavioral patterns and voice data from a user's digital device and recognizes emotions;

[1714] means for transmitting data recognized by the emotion engine to a server;

[1715] means for storing and classifying the transaction data and emotion data received by the server;

[1716] a means for analyzing the collected data using generative artificial intelligence to assess the user's current financial situation;

[1717] A means to create a life plan based on the analysis results and predict future economic situations,

[1718] means for generating a specific action plan based on the prediction result and the emotional state and transmitting the action plan to the terminal;

[1719] a means for informing users of the generated action plan and collecting their feedback;

[1720] A means of reanalyzing and optimizing life plans based on feedback and emotional state;

[1721] A system including:

[1722] (Claim 2)

[1723] 10. The system of claim 1, wherein the system collects transaction data in conjunction with electronic payment services and bank account information.

[1724] (Claim 3)

[1725] 10. The system of claim 1, wherein the system collects user feedback and optimizes the life plan.

[1726] "Application example 2 when combining emotion engines"

[1727] (Claim 1)

[1728] means of collecting income and expenditure information;

[1729] a means for using a generative artificial intelligence to create a life plan based on the income and expenditure information;

[1730] A means for predicting future economic situations based on the life plan created by the generative artificial intelligence;

[1731] a means for proposing a specific action plan based on the predicted economic situation;

[1732] a means for recognizing the emotional state of the user using an emotion engine and optimizing the content of the proposal and the life plan;

[1733] A system including:

[1734] (Claim 2)

[1735] 10. The system of claim 1, wherein the system collects transaction data in conjunction with electronic payment services and bank account information.

[1736] (Claim 3)

[1737] 10. The system of claim 1, wherein the system collects user feedback and optimizes the life plan.

[1738] (Claim 4)

[1739] 2. The system according to claim 1, further comprising means for adjusting the content of the suggestions to be less stressful based on the emotional state.

[1740] (Claim 5)

[1741] 10. The system of claim 1, further comprising means for displaying the suggestions to the user using push notifications or in-app messages. [Explanation of symbols]

[1742] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means of collecting income and expenditure information; a means for using a generative artificial intelligence to create a life plan based on the income and expenditure information; A means for predicting future economic situations based on the life plan created by the generative artificial intelligence; a means for proposing a specific action plan based on the predicted economic situation; A system including:

2. The system of claim 1 , wherein the system collects transaction data in cooperation with an electronic payment service and bank account information.

3. The system of claim 1 , further comprising: collecting user feedback to optimize the life plan.

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