system

Abstract

Provide a system. A means for acquiring basic information of a user; A means of storing the acquired basic information in a database; means for collecting data relating to the event through communication with the user; means for analyzing the collected data and providing recommendations to the user; a means for providing suggestions to a user; means for analyzing user spending information in conjunction with an electronic payment system; means for providing financial advice to the user based on the analyzed spending information; 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] Today's individuals require accurate and timely information for major events in their lives (exams, employment, marriage, childbirth, child-rearing, retirement, nursing care, and asset formation). However, because this information is so diverse, it is difficult to provide comprehensive support on a single platform. Many services specialize in specific areas of information, forcing users to search in detail for the information they need. Furthermore, in financial management, there is a lack of centralized means for visualizing expenditures and providing advice. There is a need to eliminate this complexity and provide users with optimal support. [Means for solving the problem]

[0005] This invention includes a means for acquiring basic information about a user and storing it in a database. Event-related data is then collected through communication with the user. The collected data is analyzed, and suggestions tailored to the user are provided. The suggestions are information and advice related to life events, and financial advice is provided by analyzing the user's spending information in conjunction with an electronic payment system. Furthermore, the system monitors the user's health status and provides healthcare support, thereby achieving comprehensive life support.

[0006] "User" refers to an individual who uses this system.

[0007] "Basic information" refers to personal data such as the user's age, occupation, and family composition.

[0008] "Database" means a data storage system for storing basic information and data related to events.

[0009] "Communication" refers to the process of passing information between a user and a system.

[0010] "Events" refer to major events in a user's life, such as taking an exam, getting a job, getting married, giving birth, raising children, retirement, caring for the elderly, and building assets.

[0011] "Data" refers to information obtained from the user and information that forms the basis of advice generated by the system.

[0012] "Analysis" refers to the process of using collected data to extract patterns and trends and generate relevant recommendations for users.

[0013] "Recommendation" refers to specific advice or information provided to the user based on the analysis.

[0014] "Electronic payment system" refers to a system that processes payments made by users online.

[0015] "Expense Information" refers to details of payments made by a User through an Electronic Payment System.

[0016] "Financial Advice" refers to advice on saving and asset management provided to a user based on spending information.

[0017] "Healthcare data" refers to information related to a user's health condition.

[0018] "Monitoring" refers to the process of regularly checking a user's health status to see if there are any abnormalities.

[0019] "Healthcare support" refers to health management advice and information provided to users based on monitoring results. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). The system acquires basic information about the user and makes suggestions based on that information, allowing the user to obtain the information and advice they need. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[0042] System Components

[0043] 1. User Device

[0044] A device that allows users to access the system via messaging apps such as LINE.

[0045] Enter basic information, submit data related to your event, receive suggestions, and more.

[0046] 2. Server

[0047] Receives basic information and event data sent by users and stores them in a database.

[0048] Conduct data analysis and generate optimal suggestions for users.

[0049] It works in conjunction with electronic payment systems to manage expenditure information.

[0050] Generates and transmits financial advice to users.

[0051] 3. Database

[0052] Stores and manages user basic information, event data, expenditure information, etc.

[0053] Specific processing content and operation of the program

[0054] 1. User registration and initial settings

[0055] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[0056] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[0057] Server: Receives the basic information sent and stores it in a database.

[0058] 2. Event data collection and analysis

[0059] User: Uses the LINE app on a daily basis to interact with the assist app.

[0060] Terminal: Collects the user's interaction history and periodically sends it to the server.

[0061] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[0062] Server: Generates suggestions for users based on the analysis results.

[0063] 3. Providing concrete support

[0064] Exam

[0065] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[0066] Device: Send study plan reminders to users.

[0067] find work

[0068] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[0069] Terminal: Notifies the user of interview dates and interview tips.

[0070] marriage

[0071] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[0072] Device: Send a reminder to visit wedding venues.

[0073] Childbirth and childcare

[0074] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[0075] Device: Sends users reminders of childcare schedules and important dates.

[0076] Retirement and nursing care

[0077] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[0078] Device: Send reminders for regular health checks.

[0079] Asset formation

[0080] Server: Receives spending data from electronic payment systems such as PayPay and generates monthly reports.

[0081] Server: Provides advice on saving and asset management based on the analysis of spending data.

[0082] Device: Send asset management reminders to users periodically.

[0083] Specific examples

[0084] 1. Specific examples of exam support

[0085] User: The candidate enters basic information on LINE and adds the assist app.

[0086] Server: Calculates the number of days until the exam date and generates a daily study plan.

[0087] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[0088] 2. Specific examples of marriage support

[0089] User: An engaged couple enters wedding preparation information on LINE.

[0090] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[0091] Device: Receive reminders for meetings and tour dates via LINE.

[0092] 3. Specific examples of asset formation

[0093] User: Makes payments using PayPay on a daily basis.

[0094] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[0095] Device: Report results and saving advice are sent to the user via LINE.

[0096] This system connects a server, user devices, and databases to provide users with comprehensive information and support. Users can receive various types of support for a wide range of life events through a single app.

[0097] The processing flow will be explained below.

[0098] Specific processing steps

[0099] User registration and initial settings

[0100] Step 1:

[0101] The user adds the Assist app via LINE and opens the registration page.

[0102] Step 2:

[0103] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[0104] Step 3:

[0105] The user enters basic information and presses the submit button.

[0106] Step 4:

[0107] The terminal sends the entered basic information to the server.

[0108] Step 5:

[0109] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[0110] Event data collection and analysis

[0111] Step 1:

[0112] The user uses LINE on a daily basis to chat with the assist app.

[0113] Step 2:

[0114] The terminal appropriately collects the user's chat history and transmits it to the server.

[0115] Step 3:

[0116] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[0117] Step 4:

[0118] The server prepares to provide the user with necessary information and advice based on the predicted event.

[0119] Providing concrete support

[0120] Exam

[0121] Step 1:

[0122] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[0123] Step 2:

[0124] The server generates study progress checks and reminders and sends them as LINE messages.

[0125] Step 3:

[0126] The device will remind the user about study apps and reference books.

[0127] find work

[0128] Step 1:

[0129] The server collects the user's work history data and retrieves job information via scraping or API.

[0130] Step 2:

[0131] The server compiles a list of job information suitable for the user and sends it via LINE.

[0132] Step 3:

[0133] The device sends the user interview schedule reminders and content related to interview preparation.

[0134] marriage

[0135] Step 1:

[0136] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[0137] Step 2:

[0138] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[0139] Step 3:

[0140] The device will send you a reminder to schedule a tour.

[0141] Childbirth and childcare

[0142] Step 1:

[0143] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[0144] Step 2:

[0145] The device will remind you of childcare schedules and vaccination dates.

[0146] Step 3:

[0147] The server analyzes the user's questions and concerns and provides appropriate advice.

[0148] Retirement and nursing care

[0149] Step 1:

[0150] The server monitors the user's health status and periodically sends health check questionnaires.

[0151] Step 2:

[0152] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[0153] Step 3:

[0154] The device sends the user health checklists and reminders for regular checkups.

[0155] Asset formation

[0156] Step 1:

[0157] A server retrieves spending data from the electronic payment system and generates monthly reports.

[0158] Step 2:

[0159] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[0160] Step 3:

[0161] The terminal notifies the user of periodic asset management reminders.

[0162] PayPay integration

[0163] Step 1:

[0164] A user makes everyday payments through an electronic payment system.

[0165] Step 2:

[0166] The server periodically collects user spending data through the API of the electronic payment system.

[0167] Step 3:

[0168] The server analyzes the collected spending data to detect abnormal or excessive spending.

[0169] Step 4:

[0170] The device will notify the user of their spending status and savings suggestions via LINE.

[0171] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[0172] Example 1

[0173] 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."

[0174] Responding to the diverse needs of users during life events requires the collection and analysis of individualized information. However, current systems struggle to comprehensively collect, analyze, propose, manage expenses, and provide financial advice. Furthermore, the lack of a means to provide users with timely reminders and advice can hinder the smooth progression of life events.

[0175] 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.

[0176] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data with a natural language processing engine and making suggestions to the user, means for providing the suggestions to the user, means for aggregating user expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the aggregated expenditure information, and means for notifying the user of the suggestions and advice via a messaging app. This enables users to receive appropriate support for each life event in a centralized manner, starting with registering their basic information, and also enables smooth management of the progress of events through timely notifications.

[0177] "User" refers to an individual who uses this system to register basic information, input information related to life events, receive advice, etc.

[0178] "Basic information" refers to basic personal data such as the user's age, occupation, and family structure.

[0179] "Database" refers to a storage device for storing and managing basic user information, event data, expenditure information, etc.

[0180] "Event Data" refers to data entered into the system by a user regarding information about a life event and its progress.

[0181] A "natural language processing engine" refers to software that analyzes text data collected from users, understands its meaning, and generates appropriate suggestions.

[0182] "Suggestion" refers to specific guidelines for action or advice for the user that are generated based on the analysis results of the natural language processing engine.

[0183] "Electronic payment system" refers to a system that electronically processes financial transactions made by users and provides expenditure data.

[0184] "Expenditure information" refers to data regarding a user's economic activity obtained from an electronic payment system.

[0185] "Financial advice" refers to specific advice for the user to efficiently manage assets and save money based on the analysis of expenditure information.

[0186] "Messaging app" refers to a communication application that allows a user to interact with a system, enter information, or receive suggestions.

[0187] MODE FOR CARRYING OUT THE INVENTION

[0188] This invention is a system that provides comprehensive support for users regarding life events (e.g., exams, employment, marriage, childbirth, childcare, retirement, nursing care, asset formation). The system acquires basic information about the user, generates suggestions based on that information, and notifies the user at appropriate times. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[0189] Hardware and software used

[0190] 1. Hardware

[0191] User device: Mobile devices such as smartphones and tablets

[0192] Server: A virtual server on the cloud (e.g., AWS (registered trademark) or Google (registered trademark) Cloud Platform)

[0193] Database Server: Cloud data store (e.g., Amazon RDS or Google Cloud SQL)

[0194] 2. Software

[0195] Messaging app: LINE

[0196] Database Management System (DBMS): MySQL (registered trademark), PostgreSQL

[0197] Natural language processing engine: Google Cloud Natural Language API, IBM Watson (registered trademark)

[0198] Payment system: PayPay

[0199] A description of what the program does

[0200] The server receives basic information and event data sent by the user and stores it in a database. The server analyzes the necessary information for each life event, generates appropriate suggestions, and notifies the user via a messaging app. It also works with an electronic payment system to manage and compile the user's spending information and provide financial advice. Meanwhile, the user's device allows the user to access the system through messaging apps such as LINE to enter basic information, send event-related data, and receive suggestions. The database stores and manages the user's basic information, event data, spending information, etc.

[0201] Specific processing examples

[0202] Exam support

[0203] User: The candidate enters basic information (e.g., age, desired school, exam date) on LINE and adds the assist app.

[0204] Server: Calculates the number of days until the exam date and generates a daily study plan.

[0205] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[0206] Example prompt:

[0207] Create a daily study plan for your students and share it with them via LINE. Please take into account the number of days until the exam.

[0208] Marriage Support

[0209] User: An engaged couple enters wedding preparation information (e.g., wedding date, preparation status) on LINE.

[0210] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[0211] Device: Receive reminders for meetings and tour dates via LINE.

[0212] Example prompt:

[0213] Keep engaged couples on track with a list of wedding planning tasks and schedules. Receive reminders for meetings and viewing dates.

[0214] Asset formation support

[0215] User: Makes payments using PayPay on a daily basis.

[0216] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[0217] Device: Report results and saving advice are sent to the user via LINE.

[0218] Example prompt:

[0219] Generate monthly reports based on spending data from the electronic payment system and provide users with money-saving advice. Notify users of the reports and advice via LINE.

[0220] This system provides comprehensive information and support to users by linking a server, user devices, and databases. Users can receive various types of support for a wide range of life events through a single app.

[0221] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0222] System program processing flow

[0223] Step 1: User registration and initial setup

[0224] Input: The user adds the Assist app through the LINE app and enters basic information (age, occupation, family composition, etc.).

[0225] Output: Basic information is sent to the server and stored in a database.

[0226] Specific actions

[0227] User: Adds the Assist app as a friend in the LINE app, and enters his age (30), occupation (engineer), and family composition (wife and two children).

[0228] Terminal: Displays a form for inputting basic information and sends the input information to the server.

[0229] Server: Receives the basic information sent and saves it in the database as "User ID 123".

[0230] Step 2: Collect and analyze event data

[0231] Input: The user interacts with the Assist App using the LINE app on a daily basis and provides event-related information.

[0232] Output: The server analyzes the dialogue history, identifies the user's state and requests, and saves the analysis results.

[0233] Specific actions

[0234] User: Sends a message on LINE saying, "I have an exam this weekend. How should I prepare?"

[0235] Terminal: Record this message and send it to the server.

[0236] Server: Using the Google Cloud Natural Language API, extract keywords such as "exam" and "preparation" and identify that the user is looking to prepare for an exam. Save the analysis results.

[0237] Step 3: Generate and deliver proposals

[0238] Input: The server generates optimal suggestions based on the analysis results and event-related information.

[0239] Output: The proposal is sent to the user terminal and the user is notified.

[0240] Specific actions

[0241] Server: Based on the analysis results, generate suggestions for "study methods during exam preparation."

[0242] Device: Send a notification via LINE saying, "Starting today, use this study book to study for one hour every night in preparation for this weekend's exam."

[0243] Step 4: Collect and analyze spending data

[0244] Input: Users routinely make payments using electronic payment systems.

[0245] Output: At the end of the month, spending data is compiled and analyzed to generate reports and recommendations.

[0246] Specific actions

[0247] User: Makes daily payments using electronic payment systems such as PayPay.

[0248] Server: At the end of the month, spending data is collected using PayPay's API and aggregated and analyzed.

[0249] Server: Based on the aggregated expenditure data, generate "This month's expenditure status and saving advice."

[0250] Step 5: Providing financial advice

[0251] Input: The server creates advice based on the aggregated expenditure data.

[0252] Output: The created advice is sent to the user's terminal and notified to the user.

[0253] Specific actions

[0254] Server: Based on expenditure data, it generates advice such as, "You've spent a lot on eating out this month, so try to save money next month."

[0255] Device: Receive a notification via LINE saying, "This month's spending: Eating out is expensive. To save money, try cooking at home twice a week."

[0256] The above is a specific flow of the processing steps of the system program.

[0257] (Application example 1)

[0258] 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."

[0259] Conventional systems have struggled to provide users with appropriate information and financial advice related to life events. Furthermore, managing events and analyzing expenditure data required manual tasks, placing a significant burden on users. Furthermore, they were unable to analyze dialogue history using natural language processing or make appropriate suggestions in real time using generative AI models. Therefore, a new system is needed that efficiently provides users with the information and advice they need for major life events.

[0260] 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.

[0261] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, means for performing natural language processing using a generative AI model, and means for generating suggestions from the user's dialogue history using prompt sentences. This enables comprehensive support for the user's life events and the provision of appropriate suggestions and financial advice in real time.

[0262] The "means for acquiring basic information about the user" is a means for collecting basic information about the user, such as age, occupation, and family structure.

[0263] "Means for storing in a database" refers to means for safely and effectively storing the acquired basic information of users.

[0264] The "means for collecting data related to events" is a means for collecting data related to life events such as taking an exam, getting a job, getting married, etc. through communication with the user.

[0265] The "means for analyzing data and making suggestions to the user" is a means for analyzing collected data and generating suggestions suited to the user's situation.

[0266] The "means for providing to the user" refers to a means for notifying or displaying the generated proposal to the user.

[0267] The "means for analyzing user expenditure information in cooperation with an electronic payment system" refers to means for analyzing user expenditure data obtained from an electronic payment system.

[0268] The "means for providing financial advice" is a means for providing the user with advice on financial management and saving based on the analyzed expenditure information.

[0269] "Means for performing natural language processing using a generative AI model" refers to means for analyzing a user's dialogue history, etc., using a generative AI model.

[0270] The "means for generating a suggestion from a user's dialogue history using a prompt sentence" refers to a means for generating an appropriate suggestion for a user based on a dialogue history in response to a specific instruction or question.

[0271] The "means for sending reminders" is a means for sending notifications related to life events or deadlines set by the user.

[0272] The "means for generating periodic expenditure reports" refers to a means for aggregating the user's expenditure status at regular intervals and generating a report.

[0273] This invention is a system that provides comprehensive support for users regarding life events. The main components of the system include a user terminal, a server, and a database. The functions of the invention are realized by the cooperation of these components.

[0274] 1. User Device

[0275] The user terminal uses a device such as a smartphone or smart glasses and performs the following functions:

[0276] Input of basic information and event data: Users enter basic information (age, occupation, family composition, etc.) and event-related data through a dedicated app. For example, they can access the system using a messaging app such as LINE.

[0277] Data transmission: Collected basic information and event data are sent to the server.

[0278] Receiving suggestions and reminders: Receives suggestions and reminders generated from the server and notifies the user.

[0279] 2. Server

[0280] The server receives and processes the data sent from the above user terminals. It fulfills the following roles.

[0281] Data storage: The server securely stores basic user information and event data using a real-time database such as Firebase.

[0282] Data analysis: Perform natural language processing using Google Cloud Natural Language API, etc. Analyze user interaction history and event data to generate appropriate suggestions based on user requests.

[0283] Integration with electronic payment systems: PayPay's API is used to obtain user spending data and analyze it to generate financial advice for users.

[0284] Generative AI model: A generative AI model is used to generate optimal advice and suggestions for the user based on the prompt text.

[0285] 3. Database

[0286] The database (e.g., Firebase Firestore) stores and manages the following data:

[0287] User Basic Information

[0288] Data related to life events

[0289] Expenditure Data

[0290] Specific examples

[0291] Specific examples of exam support

[0292] User: Candidates enter basic information in the LINE app and access the system.

[0293] Server: Calculates the number of days until the exam date and generates a daily study plan. It also uses the Google Cloud Natural Language API to generate exam advice from the conversation history.

[0294] Device: Every day, the user will receive a LINE message informing them of today's study content and progress check reminders.

[0295] Specific examples of asset formation

[0296] User: Makes payments using electronic payment systems on a daily basis.

[0297] Server: Aggregates spending data at the end of the month, generates spending analysis reports, and provides savings advice based on prompts generated by a generative AI model.

[0298] Device: Report results and saving advice are notified to the user via smartphone or smart glasses.

[0299] Prompt Sentence Examples

[0300] 1. "Provide money-saving advice. User spending categories are food, transportation, entertainment, and health."

[0301] 2. "Please create a study plan taking into account the number of days until the exam. You are currently 30% complete."

[0302] This enables the system to comprehensively support users in a wide range of life events, and also to provide appropriate proposals and financial advice in real time, reducing the burden on users.

[0303] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0304] Step 1:

[0305] User enters basic information

[0306] A user uses a smartphone app to enter their basic information (age, occupation, family composition, etc.). The entered information is temporarily saved on the device and then sent to the server. The input data is sent to the server in JSON format.

[0307] Step 2:

[0308] Saving basic information to a database

[0309] The server saves the basic information data sent from the user's device in the Firebase real-time database. Specifically, the data is stored in the database using the user ID as a key, making it available for later processing.

[0310] Step 3:

[0311] Event data collection

[0312] Users regularly use messaging apps such as LINE to input data related to life events, such as exam schedules or wedding dates. This input data is temporarily stored on the device and then sent to the server.

[0313] Step 4:

[0314] Event data storage in a database

[0315] The server receives the collected event data and stores it in a Firebase database, along with metadata such as the event type and date, allowing for efficient searching and analysis.

[0316] Step 5:

[0317] Data analysis using natural language processing

[0318] The server uses the Google Cloud Natural Language API to analyze user interaction history and event data. The input data is text data from the conversation. The analysis results returned by the API include keyword extraction, sentiment analysis, and context understanding. These analysis results are used as the basis for generating suggestions.

[0319] Step 6:

[0320] Proposal generation using generative AI models

[0321] The server inputs a prompt sentence (e.g., "Please provide money-saving advice. The user's spending categories are food, transportation, entertainment, and health.") into the generative AI model, which generates appropriate suggestions. The generated suggestions are returned to the server in text format, which is used to determine the content of the notification to the user.

[0322] Step 7:

[0323] Acquiring expenditure data from electronic payment systems

[0324] The server obtains the user's expenditure information using the API of the electronic payment system (e.g., PayPay). The obtained data is divided into each item (e.g., date, category, amount) and analyzed. The expenditure data is sent to the server in JSON format and stored in Firebase.

[0325] Step 8:

[0326] Analyzing spending data and generating financial advice

[0327] The server analyzes the acquired spending data and generates monthly and weekly reports. It uses a generative AI model to generate financial advice based on prompts (e.g., "Please analyze my spending at the end of the month."). The generated advice is then sent to the user.

[0328] Step 9:

[0329] Send a reminder

[0330] The device notifies the user of suggestions and reminders received from the server. For example, a reminder such as, "Focus on studying math and English today." Notifications are sent via LINE or the notification function of the smart glasses.

[0331] This enables the system to comprehensively support users in a wide range of life events and provide appropriate proposals and financial advice in real time.

[0332] 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.

[0333] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation) by combining it with an emotion engine that recognizes the user's emotions to make more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. Furthermore, it collects and analyzes data related to events through communication with the user and provides the user with necessary information and advice. It also works with electronic payment systems to manage the user's spending information and provide financial advice. By incorporating an emotion engine, it is possible to adjust suggestions and feedback based on the user's emotional state.

[0334] System Components

[0335] 1. User Device

[0336] A device that allows users to access the system via messaging apps such as LINE.

[0337] Enter basic information, submit data related to your event, receive suggestions, and more.

[0338] 2. Server

[0339] Receives basic information and event data sent by users and stores them in a database.

[0340] Conduct data analysis and generate optimal suggestions for users.

[0341] It works in conjunction with electronic payment systems to manage expenditure information.

[0342] Generates and transmits financial advice to users.

[0343] It has an emotion engine that recognizes the user's emotions and adjusts suggestions accordingly.

[0344] 3. Database

[0345] Stores and manages user basic information, event data, expenditure information, emotional data, etc.

[0346] 4. Emotion Engine

[0347] Recognizes and analyzes emotions from user input, voice data, and dialogue content.

[0348] Specific processing content and operation of the program

[0349] 1. User registration and initial settings

[0350] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[0351] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[0352] Server: Saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[0353] 2. Event data collection and analysis

[0354] User: Uses the LINE app on a daily basis to interact with the assist app.

[0355] Terminal: Collects the user's interaction history and periodically sends it to the server.

[0356] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[0357] Server: Generates suggestions for users based on the analysis results.

[0358] 3. Operation of the Emotion Engine

[0359] Server: Collects and analyzes emotion data from user input and dialogue.

[0360] Emotion engine: Sends the results of emotion analysis to the server.

[0361] Server: Based on the sentiment analysis results, the server adjusts the suggestions and provides them to the user.

[0362] 4. Providing concrete support

[0363] Exam

[0364] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[0365] Emotion engine: If the user loses motivation, it will suggest encouraging messages or a break.

[0366] Device: Send study plans and reminders to users.

[0367] find work

[0368] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[0369] Emotion Engine: Provides relaxation and stress management advice based on the user's stress level.

[0370] Terminal: Notifies the user of interview dates and interview tips.

[0371] marriage

[0372] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[0373] Emotion engine: Flexible adjustment of advice and suggestions based on the user's emotional state.

[0374] Device: Send a reminder to visit wedding venues.

[0375] Childbirth and childcare

[0376] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[0377] Emotion engine: Detects anxiety and stress about child-rearing and sends appropriate support messages.

[0378] Device: Sends users reminders of childcare schedules and important dates.

[0379] Retirement and nursing care

[0380] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[0381] Emotion Engine: Monitors the user's emotional state and provides emotional support when needed.

[0382] Device: Send reminders for regular health checks.

[0383] Asset formation

[0384] Server: Receives spending data from the electronic payment system and generates monthly reports.

[0385] Server: Provides advice on saving and asset management based on the analysis of spending data.

[0386] Emotion Engine: If the user's emotional state indicates financial stress, it will provide appropriate advice and offer payment instalments.

[0387] Device: Send asset management reminders to users periodically.

[0388] Specific examples

[0389] 1. Specific examples of exam support

[0390] User: The candidate enters basic information on LINE and adds the assist app.

[0391] Server: Calculates the number of days until the exam date and generates a daily study plan.

[0392] Emotion Engine: Detects when users are losing motivation and suggests encouraging messages or breaks.

[0393] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[0394] 2. Specific examples of marriage support

[0395] User: An engaged couple enters wedding preparation information on LINE.

[0396] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[0397] Emotion Engine: Detects when the user is feeling stressed and provides advice on how to relax.

[0398] Device: Receive reminders for meetings and tour dates via LINE.

[0399] 3. Specific examples of asset formation

[0400] User: Makes payments using electronic payment systems on a daily basis.

[0401] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[0402] Emotion Engine: Detects when users are experiencing financial stress and provides appropriate advice and payment instalments.

[0403] Device: Report results and saving advice are sent to the user via LINE.

[0404] This system connects a server, user devices, a database, and an emotion engine to provide users with comprehensive information and support. Through a single app, users can receive support for a wide range of life events, as well as suggestions and advice tailored to their emotional state.

[0405] The processing flow will be explained below.

[0406] Specific processing steps

[0407] User registration and initial settings

[0408] Step 1:

[0409] The user adds the Assist app via LINE and opens the registration page.

[0410] Step 2:

[0411] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[0412] Step 3:

[0413] The user enters basic information and presses the submit button.

[0414] Step 4:

[0415] The terminal sends the entered basic information to the server.

[0416] Step 5:

[0417] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[0418] Event data collection and analysis

[0419] Step 1:

[0420] The user uses LINE on a daily basis to chat with the assist app.

[0421] Step 2:

[0422] The terminal appropriately collects the user's chat history and transmits it to the server.

[0423] Step 3:

[0424] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[0425] Step 4:

[0426] The server prepares to provide the user with necessary information and advice based on the predicted event.

[0427] Emotion Engine Operation

[0428] Step 1:

[0429] The user types or sends a voice message via LINE.

[0430] Step 2:

[0431] The device sends user input and voice messages to the emotion engine.

[0432] Step 3:

[0433] An emotion engine analyzes the input data and identifies the user's emotional state.

[0434] Step 4:

[0435] The emotion engine transmits the identified emotion data to a server.

[0436] Step 5:

[0437] The server adjusts the suggestions and advice based on the emotional data.

[0438] Providing concrete support

[0439] Exam

[0440] Step 1:

[0441] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[0442] Step 2:

[0443] The emotion engine checks the user's motivation and suggests encouraging messages or breaks as needed.

[0444] Step 3:

[0445] The server generates study progress checks and reminders and sends them as LINE messages.

[0446] Step 4:

[0447] The device will remind the user about study apps and reference books.

[0448] find work

[0449] Step 1:

[0450] The server collects the user's work history data and retrieves job information via scraping or API.

[0451] Step 2:

[0452] The server compiles a list of job information suitable for the user and sends it via LINE.

[0453] Step 3:

[0454] The emotion engine identifies the user's stress level and provides relaxation and stress management advice.

[0455] Step 4:

[0456] The device sends the user interview schedule reminders and content related to interview preparation.

[0457] marriage

[0458] Step 1:

[0459] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[0460] Step 2:

[0461] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[0462] Step 3:

[0463] The emotion engine checks the user's emotional state and flexibly adjusts advice and suggestions.

[0464] Step 4:

[0465] The device will send you a reminder to schedule a tour.

[0466] Childbirth and childcare

[0467] Step 1:

[0468] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[0469] Step 2:

[0470] The emotion engine detects the user's anxiety and stress about child-rearing and sends support messages.

[0471] Step 3:

[0472] The device will remind you of childcare schedules and vaccination dates.

[0473] Step 4:

[0474] The server analyzes the user's questions and concerns and provides appropriate advice.

[0475] Retirement and nursing care

[0476] Step 1:

[0477] The server monitors the user's health status and periodically sends health check questionnaires.

[0478] Step 2:

[0479] An emotion engine checks the user's emotional state and provides emotional support as needed.

[0480] Step 3:

[0481] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[0482] Step 4:

[0483] The device sends the user health checklists and reminders for regular checkups.

[0484] Asset formation

[0485] Step 1:

[0486] A server retrieves spending data from the electronic payment system and generates monthly reports.

[0487] Step 2:

[0488] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[0489] Step 3:

[0490] The emotion engine identifies the user's financial stress and provides optimal advice and payment installment suggestions.

[0491] Step 4:

[0492] The terminal notifies the user of periodic asset management reminders.

[0493] PayPay integration

[0494] Step 1:

[0495] A user makes everyday payments through an electronic payment system.

[0496] Step 2:

[0497] The server periodically collects user spending data through the API of the electronic payment system.

[0498] Step 3:

[0499] The server analyzes the collected spending data to detect abnormal or excessive spending.

[0500] Step 4:

[0501] The emotion engine checks the user's emotional state and provides appropriate feedback and advice.

[0502] Step 5:

[0503] The device will notify the user of their spending status and savings suggestions via LINE.

[0504] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[0505] Example 2

[0506] 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."

[0507] Users face challenges in receiving appropriate and timely information and advice for major life events. Furthermore, personalized support tailored to the user's emotional and financial situation is rarely provided for each event. Furthermore, there is a lack of comprehensive management of expenditure information and integrated analysis of data related to life events. To address these challenges, a comprehensive system is needed to support users' overall life events.

[0508] 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.

[0509] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data using natural language processing technology, means for making personalized suggestions to the user based on the analysis results, means for providing the suggestions to the user, means for collecting and analyzing emotional data of the user using emotion analysis technology, means for adjusting the suggestions based on the emotion analysis results, means for analyzing the user's expenditure information in cooperation with an electronic payment system, and means for providing the user with financial advice based on the analyzed expenditure information. This allows the user to receive comprehensive support for each life event through a single system, and provides personalized suggestions and advice tailored to their emotions and financial status.

[0510] "Means for acquiring basic information about the user" refers to a function for collecting basic information such as the user's age, occupation, and family composition.

[0511] "Means for saving acquired basic information in a database" refers to a function for saving basic information collected from users in a dedicated database.

[0512] "Means of collecting event-related data through communication with users" refers to a function for interactively collecting information related to a user's life events through messaging apps, etc.

[0513] "Means for analyzing collected data using natural language processing technology" refers to a function that uses natural language processing technology (e.g., text analysis algorithms) to analyze collected text data.

[0514] "Means of making personalized suggestions to users based on the analysis results" refers to a function that makes optimal suggestions to users based on insights gained from analyzed data.

[0515] The "means for providing suggestions to the user" refers to a function for notifying the user of the generated suggestions.

[0516] "Means of collecting and analyzing user emotional data using emotion analysis technology" refers to a function that uses technology to extract and analyze emotional information from user input and dialogue.

[0517] "Means for adjusting suggestions based on emotion analysis results" refers to a function for appropriately changing the suggestions and advice provided depending on the user's emotional state.

[0518] "Means for analyzing user expenditure information in cooperation with an electronic payment system" refers to a function for collecting and analyzing user expenditure data in cooperation with an electronic payment service.

[0519] "Means for providing financial advice to the user based on the analyzed expenditure information" refers to a function for providing appropriate financial advice to the user based on the analyzed expenditure data.

[0520] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. It collects and analyzes data related to events through communication with the user, and provides the user with the information and advice they need. It also works with electronic payment systems to manage the user's spending information and provide financial advice.

[0521] Specific examples of hardware and software used

[0522] User device: Messaging app running on a smartphone or tablet (e.g., LINE)

[0523] Server: Cloud server or local server (e.g. AWS, Google Cloud)

[0524] Database: SQL or NoSQL database (e.g. MySQL, MongoDB)

[0525] Natural language processing technology: text analysis algorithms (e.g., spaCy, NLTK)

[0526] Sentiment engine: Sentiment analysis algorithm (e.g., IBM Watson Tone Analyzer, Azure® Text Analytics)

[0527] Specific examples

[0528] 1. User registration and initial settings

[0529] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.).

[0530] The terminal displays a basic information input form to the user and sends the submitted data to the server.

[0531] The server saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[0532] 2. Event data collection and analysis

[0533] Users interact with the assist app using the LINE app on a daily basis.

[0534] The terminal collects the user's interaction history and periodically transmits it to the server.

[0535] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[0536] The server generates suggestions for the user based on the analysis results.

[0537] 3. Operation of the Emotion Engine

[0538] The server collects and analyzes emotional data from user input and dialogue.

[0539] The emotion engine sends the results of the emotion analysis to the server.

[0540] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[0541] Prompt Sentence Examples

[0542] 1. Test-taking support prompts

[0543] "Generate encouraging messages when your motivation to study is low"

[0544] 2. Marriage Support Prompts

[0545] "If you're feeling stressed while planning your wedding, we'll generate advice on how to relax."

[0546] 3. Wealth Building Prompts

[0547] "Generate monthly expenditure analysis reports based on data from the electronic payment system."

[0548] The basic components of this system are a user device, a server, a database, a natural language processing tool, and an emotion engine, all working closely together. Users can receive support for a variety of life events through a single application. Emotion analysis also makes it possible to provide more personalized suggestions in real time. In this way, users can receive comprehensive and personalized assistance.

[0549] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0550] System program processing flow

[0551] Processing Steps:

[0552] Step 1:

[0553] Step 2:

[0554] Step 3:

[0555] ...

[0556] Processing step details

[0557] Step 1:

[0558] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.)

[0559] Input: User's basic information data

[0560] Action: The user opens the LINE app and taps the "Assist App" button. A basic information input form is displayed. The user enters basic information such as age, occupation, and family composition, and presses the "Send" button.

[0561] Output: Basic information data entered by the user

[0562] Step 2:

[0563] The device displays a form for inputting basic information to the user and sends the submitted data to the server.

[0564] Input: Basic information entered by the user

[0565] Operation: The terminal displays a basic information input form to the user, converts the information entered by the user into a data format to be sent to the server, and sends the data to the server in the form of an HTTP request.

[0566] Output: Basic information sent to the server

[0567] Step 3:

[0568] The server saves the basic information sent to the database and sends a registration completion message to the user via LINE.

[0569] Input: Basic information received by the server

[0570] Operation: The server saves basic information to the database. After saving is complete, it generates a registration completion message and sends it to the user using the LINE API.

[0571] Output: Basic information stored in the database and a successful registration message sent to the user.

[0572] Step 4:

[0573] Users interact with the Assist App using the LINE app on a daily basis.

[0574] Input: User interaction message

[0575] How it works: A user sends a message about a daily event through the LINE app.

[0576] Output: Interactive message from the user

[0577] Step 5:

[0578] The device collects the user's interaction history and periodically sends it to the server.

[0579] Input: User interaction history

[0580] How it works: The device collects conversation history via the LINE API and uploads it to the server on a specified schedule (e.g., at a certain time every day).

[0581] Output: Dialogue history sent to the server

[0582] Step 6:

[0583] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[0584] Input: Dialogue history received by the server

[0585] How it works: The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the dialogue history and perform text tokenization, sentiment analysis, and semantic analysis to identify the user's emotional state and information needs.

[0586] Output: Analyzed user status and desired information

[0587] Step 7:

[0588] The server generates suggestions for the user based on the analysis results.

[0589] Input: Analyzed user status and desired information

[0590] How it works: The server uses the generative AI model to generate suggestions based on the analysis results. The suggestions are generated based on the prompt (e.g., "If your motivation to study is declining, generate an encouraging message").

[0591] Output: Generated proposals

[0592] Step 8:

[0593] The server provides suggestions to the user via LINE

[0594] Input: Generated proposals

[0595] How it works: The server uses the LINE API to send the generated suggestions to the user.

[0596] Output: Suggestions sent to the user

[0597] Step 9:

[0598] The server collects and analyzes emotional data from user input and dialogue.

[0599] Input: User input and interaction data

[0600] How it works: The server uses the emotion engine to analyze the user's emotional state from their input and dialogue. It uses an emotion analysis algorithm to analyze the input text and identify the user's emotional state.

[0601] Output: Parsed emotion data

[0602] Step 10:

[0603] The emotion engine sends the results of emotion analysis to the server.

[0604] Input: Parsed emotion data

[0605] How it works: The emotion engine sends the analysis results to the server, which then updates the user's emotional state based on the analysis results.

[0606] Output: Sentiment analysis results sent to the server

[0607] Step 11:

[0608] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[0609] Input: Sentiment analysis results

[0610] How it works: The server adjusts the generated suggestions based on the results of emotion analysis. For example, if the user is feeling stressed, it adds suggestions for relaxation methods. The adjusted suggestions are then sent to the user via LINE.

[0611] Output: Adjusted proposal and send to user

[0612] (Application example 2)

[0613] 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."

[0614] Conventional user support systems make suggestions based on the user's basic information and event data, but they have the problem of not being able to take into account the user's emotional state. As a result, they are unable to provide personalized advice that adapts to the user's emotions, making it difficult to provide effective user support. In particular, because they do not take into account emotional changes related to financial stress or life events, they are unable to provide appropriate support that meets the user's needs.

[0615] 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.

[0616] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, and means for recognizing the user's emotions and adjusting the suggestions based thereon, thereby enabling the provision of personalized suggestions and financial advice that take the user's emotional state into consideration.

[0617] "Basic user information" refers to basic data about each individual user, such as the user's age, occupation, family structure, and income.

[0618] A "database" is an electronic information system that stores acquired information and data and allows it to be searched and updated as needed.

[0619] "Communication" refers to the means by which information is exchanged between users and systems, including messaging apps and email.

[0620] "Event-related data" is information related to major events in a user's life, such as taking an exam, getting a job, getting married, giving birth, raising children, retirement, caring for elderly relatives, and building assets.

[0621] "Recommendations" refers to specific advice, plans, information, etc. provided to users based on collected and analyzed data.

[0622] An "electronic payment system" is a system that allows users to pay electronically when purchasing goods or using services, and includes credit cards and digital wallets.

[0623] "Expense information" is data relating to the flow of money involved in purchases and payments made by a user.

[0624] "Financial advice" refers to recommendations on the user's household finances, saving methods, investment strategies, etc. based on expenditure and income information.

[0625] Recognizing "emotions" means analyzing and identifying a user's emotional state from their text messages, voice, facial expressions, etc.

[0626] "Emotion analysis" is the process of using data processing techniques to recognize emotions to determine a user's emotional state and sending that information to a server.

[0627] This invention is a system that provides comprehensive support for major events in a user's life, and by combining it with an emotion engine that recognizes the user's emotions, it makes personalized suggestions and advice. Specific embodiments for implementing this invention are described below.

[0628] System Configuration

[0629] The system consists of the following components:

[0630] 1. User Device

[0631] Users access the system using their smartphones.

[0632] Enter basic information, submit data related to your event, and receive suggestions.

[0633] To communicate with the system, messaging apps such as LINE are used.

[0634] 2. Server

[0635] Receives basic information and event data and stores it in a database.

[0636] Data analysis is performed to generate optimal suggestions for users.

[0637] It works in conjunction with electronic payment systems to manage expenditure information.

[0638] It uses an emotion engine to analyze the user's emotional state and tailor suggestions and advice.

[0639] 3. Database

[0640] Stores and manages user basic information, event data, expenditure information, and emotional data.

[0641] 4. Emotion Engine

[0642] It analyzes the user's input and voice data to recognize their emotional state.

[0643] Hardware and software used

[0644] Hardware: Smartphone (iOS, ANDROID (registered trademark))

[0645] software:

[0646] LINE Messaging API (sending messages, notifications)

[0647] AWS Lambda (serverless computing)

[0648] AWS RDS (database)

[0649] Amazon Rekognition (emotion engine)

[0650] NumPy, Pandas (data analysis)

[0651] TENSORFLOW (registered trademark) (emotion analysis model)

[0652] Program processing overview

[0653] 1. User registration and initial settings

[0654] The user enters basic information using the LINE app and sends it to the server. The server saves the basic information in a database and sends a registration completion message.

[0655] 2. Data collection and analysis

[0656] Users regularly send event-related data and information about their emotional state via the LINE app.

[0657] The server periodically receives this data and analyzes it using natural language processing technology. The analyzed information is then stored in a database.

[0658] 3. Spending data management and financial advice

[0659] Spending data is collected from users' electronic payment systems and aggregated and analyzed on the server.

[0660] Based on the analysis results, appropriate financial advice is provided to the user.

[0661] 4. Operation of the Emotion Engine

[0662] The emotion engine recognizes emotions from the user's text messages and voice data and sends that information to the server.

[0663] The server adjusts the suggestions and advice based on the results of the emotion analysis.

[0664] Specific examples

[0665] 1. Exam support

[0666] Users input their exam dates and study plans, and the server creates a daily study plan based on that information, and sends encouraging messages if the emotion engine detects a drop in motivation.

[0667] Example prompt: "I'm a 30-year-old office worker. My expenses are piling up at the end of the month. I'm feeling stressed. Please suggest some appropriate advice."

[0668] 2. Asset formation

[0669] The server aggregates monthly spending data, analyzes the user's emotional state, and provides advice to ease financial stress.

[0670] Example prompt: "I'm busy planning my wedding. Can you offer some advice on how to reduce stress?"

[0671] This allows for personalized offers and financial advice that take into account the user's emotional state.

[0672] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0673] Step 1:

[0674] User registration and basic information entry

[0675] Input: The user uses the LINE app to enter basic information such as age, occupation, and family composition.

[0676] Specific operation: The device displays a basic information input form via the LINE Messaging API and sends the information entered by the user to the server.

[0677] Data processing: The server stores the received basic information in AWS RDS via AWS Lambda.

[0678] Output: The server generates a registration completion message and sends it to the user as a LINE message.

[0679] Step 2:

[0680] Event data collection

[0681] Input: Users use the LINE app to input information related to events on a daily basis, such as the progress of their exam preparations or the status of their wedding preparations.

[0682] Specific operation: The terminal periodically collects the user's interaction history and sends it to the server.

[0683] Data processing: The server analyzes the received event data using natural language processing (NLP) technology. Specifically, it saves the dialogue history in text format and appropriately tags it.

[0684] Output: The analysis results are stored in AWS RDS and a feedback message is sent to the user if necessary.

[0685] Step 3:

[0686] Emotion data collection and analysis

[0687] Input: User text messages and voice data.

[0688] Specific operation: The device uses the LINE Messaging API to send text and voice messages to the server.

[0689] Data processing: The server uses Amazon Rekognition to perform sentiment analysis and identify the user's emotional state.

[0690] Output: The results of the sentiment analysis are stored in AWS RDS and used to inform tailoring suggestions based on the analysis results.

[0691] Step 4:

[0692] Spending data management and financial advice

[0693] Input: Spending data obtained from the user's electronic payment system.

[0694] Specific operation: The terminal periodically sends daily expenditure data to the server.

[0695] Data processing: The server aggregates and analyzes spending data using NumPy and Pandas, and generates monthly reports.

[0696] Output: Financial advice based on the analysis results is sent to the user as a LINE message.

[0697] Step 5:

[0698] Proposal generation and delivery

[0699] Input: Basic information, event data, sentiment data, and analysis results of expenditure data.

[0700] Specific operation: The server integrates the analysis results and generates optimal suggestions for the user. It uses a generative AI model (TensorFlow) to predict user behavior.

[0701] Data calculation: Calculates optimal suggestions and advice based on the user's situation and stores them on the server.

[0702] Output: The generated suggestion is notified to the user as a LINE message.

[0703] Specific examples

[0704] Exam support suggestions:

[0705] Example prompt: "I'm a 30-year-old office worker. My expenses are piling up at the end of the month. I'm feeling stressed. Please suggest some appropriate advice."

[0706] Through the specific processing of each step and the explanation of the input and output based on it, the system can provide comprehensive support to the user.

[0707] 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.

[0708] 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.

[0709] 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.

[0710] [Second embodiment]

[0711] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0712] 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.

[0713] 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).

[0714] 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.

[0715] 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.

[0716] 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).

[0717] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0718] 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.

[0719] 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.

[0720] 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.

[0721] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0722] 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."

[0723] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). The system acquires basic information about the user and makes suggestions based on that information, allowing the user to obtain the information and advice they need. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[0724] System Components

[0725] 1. User Device

[0726] A device that allows users to access the system via messaging apps such as LINE.

[0727] Enter basic information, submit data related to your event, receive suggestions, and more.

[0728] 2. Server

[0729] Receives basic information and event data sent by users and stores them in a database.

[0730] Conduct data analysis and generate optimal suggestions for users.

[0731] It works in conjunction with electronic payment systems to manage expenditure information.

[0732] Generates and transmits financial advice to users.

[0733] 3. Database

[0734] Stores and manages user basic information, event data, expenditure information, etc.

[0735] Specific processing content and operation of the program

[0736] 1. User registration and initial settings

[0737] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[0738] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[0739] Server: Receives the basic information sent and stores it in a database.

[0740] 2. Event data collection and analysis

[0741] User: Uses the LINE app on a daily basis to interact with the assist app.

[0742] Terminal: Collects the user's interaction history and periodically sends it to the server.

[0743] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[0744] Server: Generates suggestions for users based on the analysis results.

[0745] 3. Providing concrete support

[0746] Exam

[0747] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[0748] Device: Send study plan reminders to users.

[0749] find work

[0750] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[0751] Terminal: Notifies the user of interview dates and interview tips.

[0752] marriage

[0753] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[0754] Device: Send a reminder to visit wedding venues.

[0755] Childbirth and childcare

[0756] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[0757] Device: Sends users reminders of childcare schedules and important dates.

[0758] Retirement and nursing care

[0759] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[0760] Device: Send reminders for regular health checks.

[0761] Asset formation

[0762] Server: Receives spending data from electronic payment systems such as PayPay and generates monthly reports.

[0763] Server: Provides advice on saving and asset management based on the analysis of spending data.

[0764] Device: Send asset management reminders to users periodically.

[0765] Specific examples

[0766] 1. Specific examples of exam support

[0767] User: The candidate enters basic information on LINE and adds the assist app.

[0768] Server: Calculates the number of days until the exam date and generates a daily study plan.

[0769] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[0770] 2. Specific examples of marriage support

[0771] User: An engaged couple enters wedding preparation information on LINE.

[0772] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[0773] Device: Receive reminders for meetings and tour dates via LINE.

[0774] 3. Specific examples of asset formation

[0775] User: Makes payments using PayPay on a daily basis.

[0776] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[0777] Device: Report results and saving advice are sent to the user via LINE.

[0778] This system connects a server, user devices, and databases to provide users with comprehensive information and support. Users can receive various types of support for a wide range of life events through a single app.

[0779] The processing flow will be explained below.

[0780] Specific processing steps

[0781] User registration and initial settings

[0782] Step 1:

[0783] The user adds the Assist app via LINE and opens the registration page.

[0784] Step 2:

[0785] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[0786] Step 3:

[0787] The user enters basic information and presses the submit button.

[0788] Step 4:

[0789] The terminal sends the entered basic information to the server.

[0790] Step 5:

[0791] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[0792] Event data collection and analysis

[0793] Step 1:

[0794] The user uses LINE on a daily basis to chat with the assist app.

[0795] Step 2:

[0796] The terminal appropriately collects the user's chat history and transmits it to the server.

[0797] Step 3:

[0798] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[0799] Step 4:

[0800] The server prepares to provide the user with necessary information and advice based on the predicted event.

[0801] Providing concrete support

[0802] Exam

[0803] Step 1:

[0804] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[0805] Step 2:

[0806] The server generates study progress checks and reminders and sends them as LINE messages.

[0807] Step 3:

[0808] The device will remind the user about study apps and reference books.

[0809] find work

[0810] Step 1:

[0811] The server collects the user's work history data and retrieves job information via scraping or API.

[0812] Step 2:

[0813] The server compiles a list of job information suitable for the user and sends it via LINE.

[0814] Step 3:

[0815] The device sends the user interview schedule reminders and content related to interview preparation.

[0816] marriage

[0817] Step 1:

[0818] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[0819] Step 2:

[0820] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[0821] Step 3:

[0822] The device will send you a reminder to schedule a tour.

[0823] Childbirth and childcare

[0824] Step 1:

[0825] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[0826] Step 2:

[0827] The device will remind you of childcare schedules and vaccination dates.

[0828] Step 3:

[0829] The server analyzes the user's questions and concerns and provides appropriate advice.

[0830] Retirement and nursing care

[0831] Step 1:

[0832] The server monitors the user's health status and periodically sends health check questionnaires.

[0833] Step 2:

[0834] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[0835] Step 3:

[0836] The device sends the user health checklists and reminders for regular checkups.

[0837] Asset formation

[0838] Step 1:

[0839] A server retrieves spending data from the electronic payment system and generates monthly reports.

[0840] Step 2:

[0841] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[0842] Step 3:

[0843] The terminal notifies the user of periodic asset management reminders.

[0844] PayPay integration

[0845] Step 1:

[0846] A user makes everyday payments through an electronic payment system.

[0847] Step 2:

[0848] The server periodically collects user spending data through the API of the electronic payment system.

[0849] Step 3:

[0850] The server analyzes the collected spending data to detect abnormal or excessive spending.

[0851] Step 4:

[0852] The device will notify the user of their spending status and savings suggestions via LINE.

[0853] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[0854] Example 1

[0855] 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."

[0856] Responding to the diverse needs of users during life events requires the collection and analysis of individualized information. However, current systems struggle to comprehensively collect, analyze, propose, manage expenses, and provide financial advice. Furthermore, the lack of a means to provide users with timely reminders and advice can hinder the smooth progression of life events.

[0857] 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.

[0858] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data with a natural language processing engine and making suggestions to the user, means for providing the suggestions to the user, means for aggregating user expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the aggregated expenditure information, and means for notifying the user of the suggestions and advice via a messaging app. This enables users to receive appropriate support for each life event in a centralized manner, starting with registering their basic information, and also enables smooth management of the progress of events through timely notifications.

[0859] "User" refers to an individual who uses this system to register basic information, input information related to life events, receive advice, etc.

[0860] "Basic information" refers to basic personal data such as the user's age, occupation, and family structure.

[0861] "Database" refers to a storage device for storing and managing basic user information, event data, expenditure information, etc.

[0862] "Event Data" refers to data entered into the system by a user regarding information about a life event and its progress.

[0863] A "natural language processing engine" refers to software that analyzes text data collected from users, understands its meaning, and generates appropriate suggestions.

[0864] "Suggestion" refers to specific guidelines for action or advice for the user that are generated based on the analysis results of the natural language processing engine.

[0865] "Electronic payment system" refers to a system that electronically processes financial transactions made by users and provides expenditure data.

[0866] "Expenditure information" refers to data regarding a user's economic activity obtained from an electronic payment system.

[0867] "Financial advice" refers to specific advice for the user to efficiently manage assets and save money based on the analysis of expenditure information.

[0868] "Messaging app" refers to a communication application that allows a user to interact with a system, enter information, or receive suggestions.

[0869] MODE FOR CARRYING OUT THE INVENTION

[0870] This invention is a system that provides comprehensive support for users regarding life events (e.g., exams, employment, marriage, childbirth, childcare, retirement, nursing care, asset formation). The system acquires basic information about the user, generates suggestions based on that information, and notifies the user at appropriate times. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[0871] Hardware and software used

[0872] 1. Hardware

[0873] User device: Mobile devices such as smartphones and tablets

[0874] Server: A virtual server on the cloud (e.g., AWS or Google Cloud Platform)

[0875] Database Server: Cloud data store (e.g., Amazon RDS or Google Cloud SQL)

[0876] 2. Software

[0877] Messaging app: LINE

[0878] Database Management System (DBMS): MySQL, PostgreSQL

[0879] Natural language processing engine: Google Cloud Natural Language API, IBM Watson

[0880] Payment system: PayPay

[0881] A description of what the program does

[0882] The server receives basic information and event data sent by the user and stores it in a database. The server analyzes the necessary information for each life event, generates appropriate suggestions, and notifies the user via a messaging app. It also works with an electronic payment system to manage and compile the user's spending information and provide financial advice. Meanwhile, the user's device allows the user to access the system through messaging apps such as LINE to enter basic information, send event-related data, and receive suggestions. The database stores and manages the user's basic information, event data, spending information, etc.

[0883] Specific processing examples

[0884] Exam support

[0885] User: The candidate enters basic information (e.g., age, desired school, exam date) on LINE and adds the assist app.

[0886] Server: Calculates the number of days until the exam date and generates a daily study plan.

[0887] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[0888] Example prompt:

[0889] Create a daily study plan for your students and share it with them via LINE. Please take into account the number of days until the exam.

[0890] Marriage Support

[0891] User: An engaged couple enters wedding preparation information (e.g., wedding date, preparation status) on LINE.

[0892] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[0893] Device: Receive reminders for meetings and tour dates via LINE.

[0894] Example prompt:

[0895] Keep engaged couples on track with a list of wedding planning tasks and schedules. Receive reminders for meetings and viewing dates.

[0896] Asset formation support

[0897] User: Makes payments using PayPay on a daily basis.

[0898] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[0899] Device: Report results and saving advice are sent to the user via LINE.

[0900] Example prompt:

[0901] Generate monthly reports based on spending data from the electronic payment system and provide users with money-saving advice. Notify users of the reports and advice via LINE.

[0902] This system provides comprehensive information and support to users by linking a server, user devices, and databases. Users can receive various types of support for a wide range of life events through a single app.

[0903] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0904] System program processing flow

[0905] Step 1: User registration and initial setup

[0906] Input: The user adds the Assist app through the LINE app and enters basic information (age, occupation, family composition, etc.).

[0907] Output: Basic information is sent to the server and stored in a database.

[0908] Specific actions

[0909] User: Adds the Assist app as a friend in the LINE app, and enters his age (30), occupation (engineer), and family composition (wife and two children).

[0910] Terminal: Displays a form for inputting basic information and sends the input information to the server.

[0911] Server: Receives the basic information sent and saves it in the database as "User ID 123".

[0912] Step 2: Collect and analyze event data

[0913] Input: The user interacts with the Assist App using the LINE app on a daily basis and provides event-related information.

[0914] Output: The server analyzes the dialogue history, identifies the user's state and requests, and saves the analysis results.

[0915] Specific actions

[0916] User: Sends a message on LINE saying, "I have an exam this weekend. How should I prepare?"

[0917] Terminal: Record this message and send it to the server.

[0918] Server: Using the Google Cloud Natural Language API, extract keywords such as "exam" and "preparation" and identify that the user is looking to prepare for an exam. Save the analysis results.

[0919] Step 3: Generate and deliver proposals

[0920] Input: The server generates optimal suggestions based on the analysis results and event-related information.

[0921] Output: The proposal is sent to the user terminal and the user is notified.

[0922] Specific actions

[0923] Server: Based on the analysis results, generate suggestions for "study methods during exam preparation."

[0924] Device: Send a notification via LINE saying, "Starting today, use this study book to study for one hour every night in preparation for this weekend's exam."

[0925] Step 4: Collect and analyze spending data

[0926] Input: Users routinely make payments using electronic payment systems.

[0927] Output: At the end of the month, spending data is compiled and analyzed to generate reports and recommendations.

[0928] Specific actions

[0929] User: Makes daily payments using electronic payment systems such as PayPay.

[0930] Server: At the end of the month, spending data is collected using PayPay's API and aggregated and analyzed.

[0931] Server: Based on the aggregated expenditure data, generate "This month's expenditure status and saving advice."

[0932] Step 5: Providing financial advice

[0933] Input: The server creates advice based on the aggregated expenditure data.

[0934] Output: The created advice is sent to the user's terminal and notified to the user.

[0935] Specific actions

[0936] Server: Based on expenditure data, it generates advice such as, "You've spent a lot on eating out this month, so try to save money next month."

[0937] Device: Receive a notification via LINE saying, "This month's spending: Eating out is expensive. To save money, try cooking at home twice a week."

[0938] The above is a specific flow of the processing steps of the system program.

[0939] (Application example 1)

[0940] 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."

[0941] Conventional systems have struggled to provide users with appropriate information and financial advice related to life events. Furthermore, managing events and analyzing expenditure data required manual tasks, placing a significant burden on users. Furthermore, they were unable to analyze dialogue history using natural language processing or make appropriate suggestions in real time using generative AI models. Therefore, a new system is needed that efficiently provides users with the information and advice they need for major life events.

[0942] 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.

[0943] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, means for performing natural language processing using a generative AI model, and means for generating suggestions from the user's dialogue history using prompt sentences. This enables comprehensive support for the user's life events and the provision of appropriate suggestions and financial advice in real time.

[0944] The "means for acquiring basic information about the user" is a means for collecting basic information about the user, such as age, occupation, and family structure.

[0945] "Means for storing in a database" refers to means for safely and effectively storing the acquired basic information of users.

[0946] The "means for collecting data related to events" is a means for collecting data related to life events such as taking an exam, getting a job, getting married, etc. through communication with the user.

[0947] The "means for analyzing data and making suggestions to the user" is a means for analyzing collected data and generating suggestions suited to the user's situation.

[0948] The "means for providing to the user" refers to a means for notifying or displaying the generated proposal to the user.

[0949] The "means for analyzing user expenditure information in cooperation with an electronic payment system" refers to means for analyzing user expenditure data obtained from an electronic payment system.

[0950] The "means for providing financial advice" is a means for providing the user with advice on financial management and saving based on the analyzed expenditure information.

[0951] "Means for performing natural language processing using a generative AI model" refers to means for analyzing a user's dialogue history, etc., using a generative AI model.

[0952] The "means for generating a suggestion from a user's dialogue history using a prompt sentence" refers to a means for generating an appropriate suggestion for a user based on a dialogue history in response to a specific instruction or question.

[0953] The "means for sending reminders" is a means for sending notifications related to life events or deadlines set by the user.

[0954] The "means for generating periodic expenditure reports" refers to a means for aggregating the user's expenditure status at regular intervals and generating a report.

[0955] This invention is a system that provides comprehensive support for users regarding life events. The main components of the system include a user terminal, a server, and a database. The functions of the invention are realized by the cooperation of these components.

[0956] 1. User Device

[0957] The user terminal uses a device such as a smartphone or smart glasses and performs the following functions:

[0958] Input of basic information and event data: Users enter basic information (age, occupation, family composition, etc.) and event-related data through a dedicated app. For example, they can access the system using a messaging app such as LINE.

[0959] Data transmission: Collected basic information and event data are sent to the server.

[0960] Receiving suggestions and reminders: Receives suggestions and reminders generated from the server and notifies the user.

[0961] 2. Server

[0962] The server receives and processes the data sent from the above user terminals. It fulfills the following roles.

[0963] Data storage: The server securely stores basic user information and event data using a real-time database such as Firebase.

[0964] Data analysis: Perform natural language processing using Google Cloud Natural Language API, etc. Analyze user interaction history and event data to generate appropriate suggestions based on user requests.

[0965] Integration with electronic payment systems: PayPay's API is used to obtain user spending data and analyze it to generate financial advice for users.

[0966] Generative AI model: A generative AI model is used to generate optimal advice and suggestions for the user based on the prompt text.

[0967] 3. Database

[0968] The database (e.g., Firebase Firestore) stores and manages the following data:

[0969] User Basic Information

[0970] Data related to life events

[0971] Expenditure Data

[0972] Specific examples

[0973] Specific examples of exam support

[0974] User: Candidates enter basic information in the LINE app and access the system.

[0975] Server: Calculates the number of days until the exam date and generates a daily study plan. It also uses the Google Cloud Natural Language API to generate exam advice from the conversation history.

[0976] Device: Every day, the user will receive a LINE message informing them of today's study content and progress check reminders.

[0977] Specific examples of asset formation

[0978] User: Makes payments using electronic payment systems on a daily basis.

[0979] Server: Aggregates spending data at the end of the month, generates spending analysis reports, and provides savings advice based on prompts generated by a generative AI model.

[0980] Device: Report results and saving advice are notified to the user via smartphone or smart glasses.

[0981] Prompt Sentence Examples

[0982] 1. "Provide money-saving advice. User spending categories are food, transportation, entertainment, and health."

[0983] 2. "Please create a study plan taking into account the number of days until the exam. You are currently 30% complete."

[0984] This enables the system to comprehensively support users in a wide range of life events, and also to provide appropriate proposals and financial advice in real time, reducing the burden on users.

[0985] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0986] Step 1:

[0987] User enters basic information

[0988] A user uses a smartphone app to enter their basic information (age, occupation, family composition, etc.). The entered information is temporarily saved on the device and then sent to the server. The input data is sent to the server in JSON format.

[0989] Step 2:

[0990] Saving basic information to a database

[0991] The server saves the basic information data sent from the user's device in the Firebase real-time database. Specifically, the data is stored in the database using the user ID as a key, making it available for later processing.

[0992] Step 3:

[0993] Event data collection

[0994] Users regularly use messaging apps such as LINE to input data related to life events, such as exam schedules or wedding dates. This input data is temporarily stored on the device and then sent to the server.

[0995] Step 4:

[0996] Event data storage in a database

[0997] The server receives the collected event data and stores it in a Firebase database, along with metadata such as the event type and date, allowing for efficient searching and analysis.

[0998] Step 5:

[0999] Data analysis using natural language processing

[1000] The server uses the Google Cloud Natural Language API to analyze user interaction history and event data. The input data is text data from the conversation. The analysis results returned by the API include keyword extraction, sentiment analysis, and context understanding. These analysis results are used as the basis for generating suggestions.

[1001] Step 6:

[1002] Proposal generation using generative AI models

[1003] The server inputs a prompt sentence (e.g., "Please provide money-saving advice. The user's spending categories are food, transportation, entertainment, and health.") into the generative AI model, which generates appropriate suggestions. The generated suggestions are returned to the server in text format, which is used to determine the content of the notification to the user.

[1004] Step 7:

[1005] Acquiring expenditure data from electronic payment systems

[1006] The server obtains the user's expenditure information using the API of the electronic payment system (e.g., PayPay). The obtained data is divided into each item (e.g., date, category, amount) and analyzed. The expenditure data is sent to the server in JSON format and stored in Firebase.

[1007] Step 8:

[1008] Analyzing spending data and generating financial advice

[1009] The server analyzes the acquired spending data and generates monthly and weekly reports. It uses a generative AI model to generate financial advice based on prompts (e.g., "Please analyze my spending at the end of the month."). The generated advice is then sent to the user.

[1010] Step 9:

[1011] Send a reminder

[1012] The device notifies the user of suggestions and reminders received from the server. For example, a reminder such as, "Focus on studying math and English today." Notifications are sent via LINE or the notification function of the smart glasses.

[1013] This enables the system to comprehensively support users in a wide range of life events and provide appropriate proposals and financial advice in real time.

[1014] 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.

[1015] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation) by combining it with an emotion engine that recognizes the user's emotions to make more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. Furthermore, it collects and analyzes data related to events through communication with the user and provides the user with necessary information and advice. It also works with electronic payment systems to manage the user's spending information and provide financial advice. By incorporating an emotion engine, it is possible to adjust suggestions and feedback based on the user's emotional state.

[1016] System Components

[1017] 1. User Device

[1018] A device that allows users to access the system via messaging apps such as LINE.

[1019] Enter basic information, submit data related to your event, receive suggestions, and more.

[1020] 2. Server

[1021] Receives basic information and event data sent by users and stores them in a database.

[1022] Conduct data analysis and generate optimal suggestions for users.

[1023] It works in conjunction with electronic payment systems to manage expenditure information.

[1024] Generates and transmits financial advice to users.

[1025] It has an emotion engine that recognizes the user's emotions and adjusts suggestions accordingly.

[1026] 3. Database

[1027] Stores and manages user basic information, event data, expenditure information, emotional data, etc.

[1028] 4. Emotion Engine

[1029] Recognizes and analyzes emotions from user input, voice data, and dialogue content.

[1030] Specific processing content and operation of the program

[1031] 1. User registration and initial settings

[1032] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[1033] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[1034] Server: Saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[1035] 2. Event data collection and analysis

[1036] User: Uses the LINE app on a daily basis to interact with the assist app.

[1037] Terminal: Collects the user's interaction history and periodically sends it to the server.

[1038] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[1039] Server: Generates suggestions for users based on the analysis results.

[1040] 3. Operation of the Emotion Engine

[1041] Server: Collects and analyzes emotion data from user input and dialogue.

[1042] Emotion engine: Sends the results of emotion analysis to the server.

[1043] Server: Based on the sentiment analysis results, the server adjusts the suggestions and provides them to the user.

[1044] 4. Providing concrete support

[1045] Exam

[1046] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[1047] Emotion engine: If the user loses motivation, it will suggest encouraging messages or a break.

[1048] Device: Send study plans and reminders to users.

[1049] find work

[1050] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[1051] Emotion Engine: Provides relaxation and stress management advice based on the user's stress level.

[1052] Terminal: Notifies the user of interview dates and interview tips.

[1053] marriage

[1054] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[1055] Emotion engine: Flexible adjustment of advice and suggestions based on the user's emotional state.

[1056] Device: Send a reminder to visit wedding venues.

[1057] Childbirth and childcare

[1058] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[1059] Emotion engine: Detects anxiety and stress about child-rearing and sends appropriate support messages.

[1060] Device: Sends users reminders of childcare schedules and important dates.

[1061] Retirement and nursing care

[1062] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[1063] Emotion Engine: Monitors the user's emotional state and provides emotional support when needed.

[1064] Device: Send reminders for regular health checks.

[1065] Asset formation

[1066] Server: Receives spending data from the electronic payment system and generates monthly reports.

[1067] Server: Provides advice on saving and asset management based on the analysis of spending data.

[1068] Emotion Engine: If the user's emotional state indicates financial stress, it will provide appropriate advice and offer payment instalments.

[1069] Device: Send asset management reminders to users periodically.

[1070] Specific examples

[1071] 1. Specific examples of exam support

[1072] User: The candidate enters basic information on LINE and adds the assist app.

[1073] Server: Calculates the number of days until the exam date and generates a daily study plan.

[1074] Emotion Engine: Detects when users are losing motivation and suggests encouraging messages or breaks.

[1075] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[1076] 2. Specific examples of marriage support

[1077] User: An engaged couple enters wedding preparation information on LINE.

[1078] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[1079] Emotion Engine: Detects when the user is feeling stressed and provides advice on how to relax.

[1080] Device: Receive reminders for meetings and tour dates via LINE.

[1081] 3. Specific examples of asset formation

[1082] User: Makes payments using electronic payment systems on a daily basis.

[1083] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[1084] Emotion Engine: Detects when users are experiencing financial stress and provides appropriate advice and payment instalments.

[1085] Device: Report results and saving advice are sent to the user via LINE.

[1086] This system connects a server, user devices, a database, and an emotion engine to provide users with comprehensive information and support. Through a single app, users can receive support for a wide range of life events, as well as suggestions and advice tailored to their emotional state.

[1087] The processing flow will be explained below.

[1088] Specific processing steps

[1089] User registration and initial settings

[1090] Step 1:

[1091] The user adds the Assist app via LINE and opens the registration page.

[1092] Step 2:

[1093] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[1094] Step 3:

[1095] The user enters basic information and presses the submit button.

[1096] Step 4:

[1097] The terminal sends the entered basic information to the server.

[1098] Step 5:

[1099] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[1100] Event data collection and analysis

[1101] Step 1:

[1102] The user uses LINE on a daily basis to chat with the assist app.

[1103] Step 2:

[1104] The terminal appropriately collects the user's chat history and transmits it to the server.

[1105] Step 3:

[1106] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[1107] Step 4:

[1108] The server prepares to provide the user with necessary information and advice based on the predicted event.

[1109] Emotion Engine Operation

[1110] Step 1:

[1111] The user types or sends a voice message via LINE.

[1112] Step 2:

[1113] The device sends user input and voice messages to the emotion engine.

[1114] Step 3:

[1115] An emotion engine analyzes the input data and identifies the user's emotional state.

[1116] Step 4:

[1117] The emotion engine transmits the identified emotion data to a server.

[1118] Step 5:

[1119] The server adjusts the suggestions and advice based on the emotional data.

[1120] Providing concrete support

[1121] Exam

[1122] Step 1:

[1123] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[1124] Step 2:

[1125] The emotion engine checks the user's motivation and suggests encouraging messages or breaks as needed.

[1126] Step 3:

[1127] The server generates study progress checks and reminders and sends them as LINE messages.

[1128] Step 4:

[1129] The device will remind the user about study apps and reference books.

[1130] find work

[1131] Step 1:

[1132] The server collects the user's work history data and retrieves job information via scraping or API.

[1133] Step 2:

[1134] The server compiles a list of job information suitable for the user and sends it via LINE.

[1135] Step 3:

[1136] The emotion engine identifies the user's stress level and provides relaxation and stress management advice.

[1137] Step 4:

[1138] The device sends the user interview schedule reminders and content related to interview preparation.

[1139] marriage

[1140] Step 1:

[1141] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[1142] Step 2:

[1143] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[1144] Step 3:

[1145] The emotion engine checks the user's emotional state and flexibly adjusts advice and suggestions.

[1146] Step 4:

[1147] The device will send you a reminder to schedule a tour.

[1148] Childbirth and childcare

[1149] Step 1:

[1150] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[1151] Step 2:

[1152] The emotion engine detects the user's anxiety and stress about child-rearing and sends support messages.

[1153] Step 3:

[1154] The device will remind you of childcare schedules and vaccination dates.

[1155] Step 4:

[1156] The server analyzes the user's questions and concerns and provides appropriate advice.

[1157] Retirement and nursing care

[1158] Step 1:

[1159] The server monitors the user's health status and periodically sends health check questionnaires.

[1160] Step 2:

[1161] An emotion engine checks the user's emotional state and provides emotional support as needed.

[1162] Step 3:

[1163] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[1164] Step 4:

[1165] The device sends the user health checklists and reminders for regular checkups.

[1166] Asset formation

[1167] Step 1:

[1168] A server retrieves spending data from the electronic payment system and generates monthly reports.

[1169] Step 2:

[1170] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[1171] Step 3:

[1172] The emotion engine identifies the user's financial stress and provides optimal advice and payment installment suggestions.

[1173] Step 4:

[1174] The terminal notifies the user of periodic asset management reminders.

[1175] PayPay integration

[1176] Step 1:

[1177] A user makes everyday payments through an electronic payment system.

[1178] Step 2:

[1179] The server periodically collects user spending data through the API of the electronic payment system.

[1180] Step 3:

[1181] The server analyzes the collected spending data to detect abnormal or excessive spending.

[1182] Step 4:

[1183] The emotion engine checks the user's emotional state and provides appropriate feedback and advice.

[1184] Step 5:

[1185] The device will notify the user of their spending status and savings suggestions via LINE.

[1186] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[1187] Example 2

[1188] 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."

[1189] Users face challenges in receiving appropriate and timely information and advice for major life events. Furthermore, personalized support tailored to the user's emotional and financial situation is rarely provided for each event. Furthermore, there is a lack of comprehensive management of expenditure information and integrated analysis of data related to life events. To address these challenges, a comprehensive system is needed to support users' overall life events.

[1190] 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.

[1191] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data using natural language processing technology, means for making personalized suggestions to the user based on the analysis results, means for providing the suggestions to the user, means for collecting and analyzing emotional data of the user using emotion analysis technology, means for adjusting the suggestions based on the emotion analysis results, means for analyzing the user's expenditure information in cooperation with an electronic payment system, and means for providing the user with financial advice based on the analyzed expenditure information. This allows the user to receive comprehensive support for each life event through a single system, and provides personalized suggestions and advice tailored to their emotions and financial status.

[1192] "Means for acquiring basic information about the user" refers to a function for collecting basic information such as the user's age, occupation, and family composition.

[1193] "Means for saving acquired basic information in a database" refers to a function for saving basic information collected from users in a dedicated database.

[1194] "Means of collecting event-related data through communication with users" refers to a function for interactively collecting information related to a user's life events through messaging apps, etc.

[1195] "Means for analyzing collected data using natural language processing technology" refers to a function that uses natural language processing technology (e.g., text analysis algorithms) to analyze collected text data.

[1196] "Means of making personalized suggestions to users based on the analysis results" refers to a function that makes optimal suggestions to users based on insights gained from analyzed data.

[1197] The "means for providing suggestions to the user" refers to a function for notifying the user of the generated suggestions.

[1198] "Means of collecting and analyzing user emotional data using emotion analysis technology" refers to a function that uses technology to extract and analyze emotional information from user input and dialogue.

[1199] "Means for adjusting suggestions based on emotion analysis results" refers to a function for appropriately changing the suggestions and advice provided depending on the user's emotional state.

[1200] "Means for analyzing user expenditure information in cooperation with an electronic payment system" refers to a function for collecting and analyzing user expenditure data in cooperation with an electronic payment service.

[1201] "Means for providing financial advice to the user based on the analyzed expenditure information" refers to a function for providing appropriate financial advice to the user based on the analyzed expenditure data.

[1202] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. It collects and analyzes data related to events through communication with the user, and provides the user with the information and advice they need. It also works with electronic payment systems to manage the user's spending information and provide financial advice.

[1203] Specific examples of hardware and software used

[1204] User device: Messaging app running on a smartphone or tablet (e.g., LINE)

[1205] Server: Cloud server or local server (e.g. AWS, Google Cloud)

[1206] Database: SQL or NoSQL database (e.g. MySQL, MongoDB)

[1207] Natural language processing technology: text analysis algorithms (e.g., spaCy, NLTK)

[1208] Sentiment engine: Sentiment analysis algorithm (e.g. IBM Watson Tone Analyzer, Azure Text Analytics)

[1209] Specific examples

[1210] 1. User registration and initial settings

[1211] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.).

[1212] The terminal displays a basic information input form to the user and sends the submitted data to the server.

[1213] The server saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[1214] 2. Event data collection and analysis

[1215] Users interact with the assist app using the LINE app on a daily basis.

[1216] The terminal collects the user's interaction history and periodically transmits it to the server.

[1217] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[1218] The server generates suggestions for the user based on the analysis results.

[1219] 3. Operation of the Emotion Engine

[1220] The server collects and analyzes emotional data from user input and dialogue.

[1221] The emotion engine sends the results of the emotion analysis to the server.

[1222] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[1223] Prompt Sentence Examples

[1224] 1. Test-taking support prompts

[1225] "Generate encouraging messages when your motivation to study is low"

[1226] 2. Marriage Support Prompts

[1227] "If you're feeling stressed while planning your wedding, we'll generate advice on how to relax."

[1228] 3. Wealth Building Prompts

[1229] "Generate monthly expenditure analysis reports based on data from the electronic payment system."

[1230] The basic components of this system are a user device, a server, a database, a natural language processing tool, and an emotion engine, all working closely together. Users can receive support for a variety of life events through a single application. Emotion analysis also makes it possible to provide more personalized suggestions in real time. In this way, users can receive comprehensive and personalized assistance.

[1231] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1232] System program processing flow

[1233] Processing Steps:

[1234] Step 1:

[1235] Step 2:

[1236] Step 3:

[1237] ...

[1238] Processing step details

[1239] Step 1:

[1240] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.)

[1241] Input: User's basic information data

[1242] Action: The user opens the LINE app and taps the "Assist App" button. A basic information input form is displayed. The user enters basic information such as age, occupation, and family composition, and presses the "Send" button.

[1243] Output: Basic information data entered by the user

[1244] Step 2:

[1245] The device displays a form for inputting basic information to the user and sends the submitted data to the server.

[1246] Input: Basic information entered by the user

[1247] Operation: The terminal displays a basic information input form to the user, converts the information entered by the user into a data format to be sent to the server, and sends the data to the server in the form of an HTTP request.

[1248] Output: Basic information sent to the server

[1249] Step 3:

[1250] The server saves the basic information sent to the database and sends a registration completion message to the user via LINE.

[1251] Input: Basic information received by the server

[1252] Operation: The server saves basic information to the database. After saving is complete, it generates a registration completion message and sends it to the user using the LINE API.

[1253] Output: Basic information stored in the database and a successful registration message sent to the user.

[1254] Step 4:

[1255] Users interact with the Assist App using the LINE app on a daily basis.

[1256] Input: User interaction message

[1257] How it works: A user sends a message about a daily event through the LINE app.

[1258] Output: Interactive message from the user

[1259] Step 5:

[1260] The device collects the user's interaction history and periodically sends it to the server.

[1261] Input: User interaction history

[1262] How it works: The device collects conversation history via the LINE API and uploads it to the server on a specified schedule (e.g., at a certain time every day).

[1263] Output: Dialogue history sent to the server

[1264] Step 6:

[1265] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[1266] Input: Dialogue history received by the server

[1267] How it works: The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the dialogue history and perform text tokenization, sentiment analysis, and semantic analysis to identify the user's emotional state and information needs.

[1268] Output: Analyzed user status and desired information

[1269] Step 7:

[1270] The server generates suggestions for the user based on the analysis results.

[1271] Input: Analyzed user status and desired information

[1272] How it works: The server uses the generative AI model to generate suggestions based on the analysis results. The suggestions are generated based on the prompt (e.g., "If your motivation to study is declining, generate an encouraging message").

[1273] Output: Generated proposals

[1274] Step 8:

[1275] The server provides suggestions to the user via LINE

[1276] Input: Generated proposals

[1277] How it works: The server uses the LINE API to send the generated suggestions to the user.

[1278] Output: Suggestions sent to the user

[1279] Step 9:

[1280] The server collects and analyzes emotional data from user input and dialogue.

[1281] Input: User input and interaction data

[1282] How it works: The server uses the emotion engine to analyze the user's emotional state from their input and dialogue. It uses an emotion analysis algorithm to analyze the input text and identify the user's emotional state.

[1283] Output: Parsed emotion data

[1284] Step 10:

[1285] The emotion engine sends the results of emotion analysis to the server.

[1286] Input: Parsed emotion data

[1287] How it works: The emotion engine sends the analysis results to the server, which then updates the user's emotional state based on the analysis results.

[1288] Output: Sentiment analysis results sent to the server

[1289] Step 11:

[1290] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[1291] Input: Sentiment analysis results

[1292] How it works: The server adjusts the generated suggestions based on the results of emotion analysis. For example, if the user is feeling stressed, it adds suggestions for relaxation methods. The adjusted suggestions are then sent to the user via LINE.

[1293] Output: Adjusted proposal and send to user

[1294] (Application example 2)

[1295] 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."

[1296] Conventional user support systems make suggestions based on the user's basic information and event data, but they have the problem of not being able to take into account the user's emotional state. As a result, they are unable to provide personalized advice that adapts to the user's emotions, making it difficult to provide effective user support. In particular, because they do not take into account emotional changes related to financial stress or life events, they are unable to provide appropriate support that meets the user's needs.

[1297] 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.

[1298] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, and means for recognizing the user's emotions and adjusting the suggestions based thereon, thereby enabling the provision of personalized suggestions and financial advice that take the user's emotional state into consideration.

[1299] "Basic user information" refers to basic data about each individual user, such as the user's age, occupation, family structure, and income.

[1300] A "database" is an electronic information system that stores acquired information and data and allows it to be searched and updated as needed.

[1301] "Communication" refers to the means by which information is exchanged between users and systems, including messaging apps and email.

[1302] "Event-related data" is information related to major events in a user's life, such as taking an exam, getting a job, getting married, giving birth, raising children, retirement, caring for elderly relatives, and building assets.

[1303] "Recommendations" refers to specific advice, plans, information, etc. provided to users based on collected and analyzed data.

[1304] An "electronic payment system" is a system that allows users to pay electronically when purchasing goods or using services, and includes credit cards and digital wallets.

[1305] "Expense information" is data relating to the flow of money involved in purchases and payments made by a user.

[1306] "Financial advice" refers to recommendations on the user's household finances, saving methods, investment strategies, etc. based on expenditure and income information.

[1307] Recognizing "emotions" means analyzing and identifying a user's emotional state from their text messages, voice, facial expressions, etc.

[1308] "Emotion analysis" is the process of using data processing techniques to recognize emotions to determine a user's emotional state and sending that information to a server.

[1309] This invention is a system that provides comprehensive support for major events in a user's life, and by combining it with an emotion engine that recognizes the user's emotions, it makes personalized suggestions and advice. Specific embodiments for implementing this invention are described below.

[1310] System Configuration

[1311] The system consists of the following components:

[1312] 1. User Device

[1313] Users access the system using their smartphones.

[1314] Enter basic information, submit data related to your event, and receive suggestions.

[1315] To communicate with the system, messaging apps such as LINE are used.

[1316] 2. Server

[1317] Receives basic information and event data and stores it in a database.

[1318] Data analysis is performed to generate optimal suggestions for users.

[1319] It works in conjunction with electronic payment systems to manage expenditure information.

[1320] It uses an emotion engine to analyze the user's emotional state and tailor suggestions and advice.

[1321] 3. Database

[1322] Stores and manages user basic information, event data, expenditure information, and emotional data.

[1323] 4. Emotion Engine

[1324] It analyzes the user's input and voice data to recognize their emotional state.

[1325] Hardware and software used

[1326] Hardware: Smartphone (iOS, Android)

[1327] software:

[1328] LINE Messaging API (sending messages, notifications)

[1329] AWS Lambda (serverless computing)

[1330] AWS RDS (database)

[1331] Amazon Rekognition (emotion engine)

[1332] NumPy, Pandas (data analysis)

[1333] TensorFlow (sentiment analysis model)

[1334] Program processing overview

[1335] 1. User registration and initial settings

[1336] The user enters basic information using the LINE app and sends it to the server. The server saves the basic information in a database and sends a registration completion message.

[1337] 2. Data collection and analysis

[1338] Users regularly send event-related data and information about their emotional state via the LINE app.

[1339] The server periodically receives this data and analyzes it using natural language processing technology. The analyzed information is then stored in a database.

[1340] 3. Spending data management and financial advice

[1341] Spending data is collected from users' electronic payment systems and aggregated and analyzed on the server.

[1342] Based on the analysis results, appropriate financial advice is provided to the user.

[1343] 4. Operation of the Emotion Engine

[1344] The emotion engine recognizes emotions from the user's text messages and voice data and sends that information to the server.

[1345] The server adjusts the suggestions and advice based on the results of the emotion analysis.

[1346] Specific examples

[1347] 1. Exam support

[1348] Users input their exam dates and study plans, and the server creates a daily study plan based on that information, and sends encouraging messages if the emotion engine detects a drop in motivation.

[1349] Example prompt: "I'm a 30-year-old office worker. My expenses are piling up at the end of the month. I'm feeling stressed. Please suggest some appropriate advice."

[1350] 2. Asset formation

[1351] The server aggregates monthly spending data, analyzes the user's emotional state, and provides advice to ease financial stress.

[1352] Example prompt: "I'm busy planning my wedding. Can you offer some advice on how to reduce stress?"

[1353] This allows for personalized offers and financial advice that take into account the user's emotional state.

[1354] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1355] Step 1:

[1356] User registration and basic information entry

[1357] Input: The user uses the LINE app to enter basic information such as age, occupation, and family composition.

[1358] Specific operation: The device displays a basic information input form via the LINE Messaging API and sends the information entered by the user to the server.

[1359] Data processing: The server stores the received basic information in AWS RDS via AWS Lambda.

[1360] Output: The server generates a registration completion message and sends it to the user as a LINE message.

[1361] Step 2:

[1362] Event data collection

[1363] Input: Users use the LINE app to input information related to events on a daily basis, such as the progress of their exam preparations or the status of their wedding preparations.

[1364] Specific operation: The terminal periodically collects the user's interaction history and sends it to the server.

[1365] Data processing: The server analyzes the received event data using natural language processing (NLP) technology. Specifically, it saves the dialogue history in text format and appropriately tags it.

[1366] Output: The analysis results are stored in AWS RDS and a feedback message is sent to the user if necessary.

[1367] Step 3:

[1368] Emotion data collection and analysis

[1369] Input: User text messages and voice data.

[1370] Specific operation: The device uses the LINE Messaging API to send text and voice messages to the server.

[1371] Data processing: The server uses Amazon Rekognition to perform sentiment analysis and identify the user's emotional state.

[1372] Output: The results of the sentiment analysis are stored in AWS RDS and used to inform tailoring suggestions based on the analysis results.

[1373] Step 4:

[1374] Spending data management and financial advice

[1375] Input: Spending data obtained from the user's electronic payment system.

[1376] Specific operation: The terminal periodically sends daily expenditure data to the server.

[1377] Data processing: The server aggregates and analyzes spending data using NumPy and Pandas, and generates monthly reports.

[1378] Output: Financial advice based on the analysis results is sent to the user as a LINE message.

[1379] Step 5:

[1380] Proposal generation and delivery

[1381] Input: Basic information, event data, sentiment data, and analysis results of expenditure data.

[1382] Specific operation: The server integrates the analysis results and generates optimal suggestions for the user. It uses a generative AI model (TensorFlow) to predict user behavior.

[1383] Data calculation: Calculates optimal suggestions and advice based on the user's situation and stores them on the server.

[1384] Output: The generated suggestion is notified to the user as a LINE message.

[1385] Specific examples

[1386] Exam support suggestions:

[1387] Example prompt: "I'm a 30-year-old office worker. My expenses are piling up at the end of the month. I'm feeling stressed. Please suggest some appropriate advice."

[1388] Through the specific processing of each step and the explanation of the input and output based on it, the system can provide comprehensive support to the user.

[1389] 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.

[1390] 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.

[1391] 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.

[1392] [Third embodiment]

[1393] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1394] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1395] 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).

[1396] 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.

[1397] 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.

[1398] 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).

[1399] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1400] 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.

[1401] 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.

[1402] 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.

[1403] 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.

[1404] 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."

[1405] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). The system acquires basic information about the user and makes suggestions based on that information, allowing the user to obtain the information and advice they need. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[1406] System Components

[1407] 1. User Device

[1408] A device that allows users to access the system via messaging apps such as LINE.

[1409] Enter basic information, submit data related to your event, receive suggestions, and more.

[1410] 2. Server

[1411] Receives basic information and event data sent by users and stores them in a database.

[1412] Conduct data analysis and generate optimal suggestions for users.

[1413] It works in conjunction with electronic payment systems to manage expenditure information.

[1414] Generates and transmits financial advice to users.

[1415] 3. Database

[1416] Stores and manages user basic information, event data, expenditure information, etc.

[1417] Specific processing content and operation of the program

[1418] 1. User registration and initial settings

[1419] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[1420] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[1421] Server: Receives the basic information sent and stores it in a database.

[1422] 2. Event data collection and analysis

[1423] User: Uses the LINE app on a daily basis to interact with the assist app.

[1424] Terminal: Collects the user's interaction history and periodically sends it to the server.

[1425] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[1426] Server: Generates suggestions for users based on the analysis results.

[1427] 3. Providing concrete support

[1428] Exam

[1429] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[1430] Device: Send study plan reminders to users.

[1431] find work

[1432] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[1433] Terminal: Notifies the user of interview dates and interview tips.

[1434] marriage

[1435] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[1436] Device: Send a reminder to visit wedding venues.

[1437] Childbirth and childcare

[1438] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[1439] Device: Sends users reminders of childcare schedules and important dates.

[1440] Retirement and nursing care

[1441] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[1442] Device: Send reminders for regular health checks.

[1443] Asset formation

[1444] Server: Receives spending data from electronic payment systems such as PayPay and generates monthly reports.

[1445] Server: Provides advice on saving and asset management based on the analysis of spending data.

[1446] Device: Send asset management reminders to users periodically.

[1447] Specific examples

[1448] 1. Specific examples of exam support

[1449] User: The candidate enters basic information on LINE and adds the assist app.

[1450] Server: Calculates the number of days until the exam date and generates a daily study plan.

[1451] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[1452] 2. Specific examples of marriage support

[1453] User: An engaged couple enters wedding preparation information on LINE.

[1454] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[1455] Device: Receive reminders for meetings and tour dates via LINE.

[1456] 3. Specific examples of asset formation

[1457] User: Makes payments using PayPay on a daily basis.

[1458] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[1459] Device: Report results and saving advice are sent to the user via LINE.

[1460] This system connects a server, user devices, and databases to provide users with comprehensive information and support. Users can receive various types of support for a wide range of life events through a single app.

[1461] The processing flow will be explained below.

[1462] Specific processing steps

[1463] User registration and initial settings

[1464] Step 1:

[1465] The user adds the Assist app via LINE and opens the registration page.

[1466] Step 2:

[1467] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[1468] Step 3:

[1469] The user enters basic information and presses the submit button.

[1470] Step 4:

[1471] The terminal sends the entered basic information to the server.

[1472] Step 5:

[1473] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[1474] Event data collection and analysis

[1475] Step 1:

[1476] The user uses LINE on a daily basis to chat with the assist app.

[1477] Step 2:

[1478] The terminal appropriately collects the user's chat history and transmits it to the server.

[1479] Step 3:

[1480] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[1481] Step 4:

[1482] The server prepares to provide the user with necessary information and advice based on the predicted event.

[1483] Providing concrete support

[1484] Exam

[1485] Step 1:

[1486] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[1487] Step 2:

[1488] The server generates study progress checks and reminders and sends them as LINE messages.

[1489] Step 3:

[1490] The device will remind the user about study apps and reference books.

[1491] find work

[1492] Step 1:

[1493] The server collects the user's work history data and retrieves job information via scraping or API.

[1494] Step 2:

[1495] The server compiles a list of job information suitable for the user and sends it via LINE.

[1496] Step 3:

[1497] The device sends the user interview schedule reminders and content related to interview preparation.

[1498] marriage

[1499] Step 1:

[1500] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[1501] Step 2:

[1502] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[1503] Step 3:

[1504] The device will send you a reminder to schedule a tour.

[1505] Childbirth and childcare

[1506] Step 1:

[1507] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[1508] Step 2:

[1509] The device will remind you of childcare schedules and vaccination dates.

[1510] Step 3:

[1511] The server analyzes the user's questions and concerns and provides appropriate advice.

[1512] Retirement and nursing care

[1513] Step 1:

[1514] The server monitors the user's health status and periodically sends health check questionnaires.

[1515] Step 2:

[1516] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[1517] Step 3:

[1518] The device sends the user health checklists and reminders for regular checkups.

[1519] Asset formation

[1520] Step 1:

[1521] A server retrieves spending data from the electronic payment system and generates monthly reports.

[1522] Step 2:

[1523] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[1524] Step 3:

[1525] The terminal notifies the user of periodic asset management reminders.

[1526] PayPay integration

[1527] Step 1:

[1528] A user makes everyday payments through an electronic payment system.

[1529] Step 2:

[1530] The server periodically collects user spending data through the API of the electronic payment system.

[1531] Step 3:

[1532] The server analyzes the collected spending data to detect abnormal or excessive spending.

[1533] Step 4:

[1534] The device will notify the user of their spending status and savings suggestions via LINE.

[1535] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[1536] Example 1

[1537] 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."

[1538] Responding to the diverse needs of users during life events requires the collection and analysis of individualized information. However, current systems struggle to comprehensively collect, analyze, propose, manage expenses, and provide financial advice. Furthermore, the lack of a means to provide users with timely reminders and advice can hinder the smooth progression of life events.

[1539] 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.

[1540] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data with a natural language processing engine and making suggestions to the user, means for providing the suggestions to the user, means for aggregating user expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the aggregated expenditure information, and means for notifying the user of the suggestions and advice via a messaging app. This enables users to receive appropriate support for each life event in a centralized manner, starting with registering their basic information, and also enables smooth management of the progress of events through timely notifications.

[1541] "User" refers to an individual who uses this system to register basic information, input information related to life events, receive advice, etc.

[1542] "Basic information" refers to basic personal data such as the user's age, occupation, and family structure.

[1543] "Database" refers to a storage device for storing and managing basic user information, event data, expenditure information, etc.

[1544] "Event Data" refers to data entered into the system by a user regarding information about a life event and its progress.

[1545] A "natural language processing engine" refers to software that analyzes text data collected from users, understands its meaning, and generates appropriate suggestions.

[1546] "Suggestion" refers to specific guidelines for action or advice for the user that are generated based on the analysis results of the natural language processing engine.

[1547] "Electronic payment system" refers to a system that electronically processes financial transactions made by users and provides expenditure data.

[1548] "Expenditure information" refers to data regarding a user's economic activity obtained from an electronic payment system.

[1549] "Financial advice" refers to specific advice for the user to efficiently manage assets and save money based on the analysis of expenditure information.

[1550] "Messaging app" refers to a communication application that allows a user to interact with a system, enter information, or receive suggestions.

[1551] MODE FOR CARRYING OUT THE INVENTION

[1552] This invention is a system that provides comprehensive support for users regarding life events (e.g., exams, employment, marriage, childbirth, childcare, retirement, nursing care, asset formation). The system acquires basic information about the user, generates suggestions based on that information, and notifies the user at appropriate times. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[1553] Hardware and software used

[1554] 1. Hardware

[1555] User device: Mobile devices such as smartphones and tablets

[1556] Server: A virtual server on the cloud (e.g., AWS or Google Cloud Platform)

[1557] Database Server: Cloud data store (e.g., Amazon RDS or Google Cloud SQL)

[1558] 2. Software

[1559] Messaging app: LINE

[1560] Database Management System (DBMS): MySQL, PostgreSQL

[1561] Natural language processing engine: Google Cloud Natural Language API, IBM Watson

[1562] Payment system: PayPay

[1563] A description of what the program does

[1564] The server receives basic information and event data sent by the user and stores it in a database. The server analyzes the necessary information for each life event, generates appropriate suggestions, and notifies the user via a messaging app. It also works with an electronic payment system to manage and compile the user's spending information and provide financial advice. Meanwhile, the user's device allows the user to access the system through messaging apps such as LINE to enter basic information, send event-related data, and receive suggestions. The database stores and manages the user's basic information, event data, spending information, etc.

[1565] Specific processing examples

[1566] Exam support

[1567] User: The candidate enters basic information (e.g., age, desired school, exam date) on LINE and adds the assist app.

[1568] Server: Calculates the number of days until the exam date and generates a daily study plan.

[1569] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[1570] Example prompt:

[1571] Create a daily study plan for your students and share it with them via LINE. Please take into account the number of days until the exam.

[1572] Marriage Support

[1573] User: An engaged couple enters wedding preparation information (e.g., wedding date, preparation status) on LINE.

[1574] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[1575] Device: Receive reminders for meetings and tour dates via LINE.

[1576] Example prompt:

[1577] Keep engaged couples on track with a list of wedding planning tasks and schedules. Receive reminders for meetings and viewing dates.

[1578] Asset formation support

[1579] User: Makes payments using PayPay on a daily basis.

[1580] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[1581] Device: Report results and saving advice are sent to the user via LINE.

[1582] Example prompt:

[1583] Generate monthly reports based on spending data from the electronic payment system and provide users with money-saving advice. Notify users of the reports and advice via LINE.

[1584] This system provides comprehensive information and support to users by linking a server, user devices, and databases. Users can receive various types of support for a wide range of life events through a single app.

[1585] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1586] System program processing flow

[1587] Step 1: User registration and initial setup

[1588] Input: The user adds the Assist app through the LINE app and enters basic information (age, occupation, family composition, etc.).

[1589] Output: Basic information is sent to the server and stored in a database.

[1590] Specific actions

[1591] User: Adds the Assist app as a friend in the LINE app, and enters his age (30), occupation (engineer), and family composition (wife and two children).

[1592] Terminal: Displays a form for inputting basic information and sends the input information to the server.

[1593] Server: Receives the basic information sent and saves it in the database as "User ID 123".

[1594] Step 2: Collect and analyze event data

[1595] Input: The user interacts with the Assist App using the LINE app on a daily basis and provides event-related information.

[1596] Output: The server analyzes the dialogue history, identifies the user's state and requests, and saves the analysis results.

[1597] Specific actions

[1598] User: Sends a message on LINE saying, "I have an exam this weekend. How should I prepare?"

[1599] Terminal: Record this message and send it to the server.

[1600] Server: Using the Google Cloud Natural Language API, extract keywords such as "exam" and "preparation" and identify that the user is looking to prepare for an exam. Save the analysis results.

[1601] Step 3: Generate and deliver proposals

[1602] Input: The server generates optimal suggestions based on the analysis results and event-related information.

[1603] Output: The proposal is sent to the user terminal and the user is notified.

[1604] Specific actions

[1605] Server: Based on the analysis results, generate suggestions for "study methods during exam preparation."

[1606] Device: Send a notification via LINE saying, "Starting today, use this study book to study for one hour every night in preparation for this weekend's exam."

[1607] Step 4: Collect and analyze spending data

[1608] Input: Users routinely make payments using electronic payment systems.

[1609] Output: At the end of the month, spending data is compiled and analyzed to generate reports and recommendations.

[1610] Specific actions

[1611] User: Makes daily payments using electronic payment systems such as PayPay.

[1612] Server: At the end of the month, spending data is collected using PayPay's API and aggregated and analyzed.

[1613] Server: Based on the aggregated expenditure data, generate "This month's expenditure status and saving advice."

[1614] Step 5: Providing financial advice

[1615] Input: The server creates advice based on the aggregated expenditure data.

[1616] Output: The created advice is sent to the user's terminal and notified to the user.

[1617] Specific actions

[1618] Server: Based on expenditure data, it generates advice such as, "You've spent a lot on eating out this month, so try to save money next month."

[1619] Device: Receive a notification via LINE saying, "This month's spending: Eating out is expensive. To save money, try cooking at home twice a week."

[1620] The above is a specific flow of the processing steps of the system program.

[1621] (Application example 1)

[1622] 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."

[1623] Conventional systems have struggled to provide users with appropriate information and financial advice related to life events. Furthermore, managing events and analyzing expenditure data required manual tasks, placing a significant burden on users. Furthermore, they were unable to analyze dialogue history using natural language processing or make appropriate suggestions in real time using generative AI models. Therefore, a new system is needed that efficiently provides users with the information and advice they need for major life events.

[1624] 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.

[1625] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, means for performing natural language processing using a generative AI model, and means for generating suggestions from the user's dialogue history using prompt sentences. This enables comprehensive support for the user's life events and the provision of appropriate suggestions and financial advice in real time.

[1626] The "means for acquiring basic information about the user" is a means for collecting basic information about the user, such as age, occupation, and family structure.

[1627] "Means for storing in a database" refers to means for safely and effectively storing the acquired basic information of users.

[1628] The "means for collecting data related to events" is a means for collecting data related to life events such as taking an exam, getting a job, getting married, etc. through communication with the user.

[1629] The "means for analyzing data and making suggestions to the user" is a means for analyzing collected data and generating suggestions suited to the user's situation.

[1630] The "means for providing to the user" refers to a means for notifying or displaying the generated proposal to the user.

[1631] The "means for analyzing user expenditure information in cooperation with an electronic payment system" refers to means for analyzing user expenditure data obtained from an electronic payment system.

[1632] The "means for providing financial advice" is a means for providing the user with advice on financial management and saving based on the analyzed expenditure information.

[1633] "Means for performing natural language processing using a generative AI model" refers to means for analyzing a user's dialogue history, etc., using a generative AI model.

[1634] The "means for generating a suggestion from a user's dialogue history using a prompt sentence" refers to a means for generating an appropriate suggestion for a user based on a dialogue history in response to a specific instruction or question.

[1635] The "means for sending reminders" is a means for sending notifications related to life events or deadlines set by the user.

[1636] The "means for generating periodic expenditure reports" refers to a means for aggregating the user's expenditure status at regular intervals and generating a report.

[1637] This invention is a system that provides comprehensive support for users regarding life events. The main components of the system include a user terminal, a server, and a database. The functions of the invention are realized by the cooperation of these components.

[1638] 1. User Device

[1639] The user terminal uses a device such as a smartphone or smart glasses and performs the following functions:

[1640] Input of basic information and event data: Users enter basic information (age, occupation, family composition, etc.) and event-related data through a dedicated app. For example, they can access the system using a messaging app such as LINE.

[1641] Data transmission: Collected basic information and event data are sent to the server.

[1642] Receiving suggestions and reminders: Receives suggestions and reminders generated from the server and notifies the user.

[1643] 2. Server

[1644] The server receives and processes the data sent from the above user terminals. It fulfills the following roles.

[1645] Data storage: The server securely stores basic user information and event data using a real-time database such as Firebase.

[1646] Data analysis: Perform natural language processing using Google Cloud Natural Language API, etc. Analyze user interaction history and event data to generate appropriate suggestions based on user requests.

[1647] Integration with electronic payment systems: PayPay's API is used to obtain user spending data and analyze it to generate financial advice for users.

[1648] Generative AI model: A generative AI model is used to generate optimal advice and suggestions for the user based on the prompt text.

[1649] 3. Database

[1650] The database (e.g., Firebase Firestore) stores and manages the following data:

[1651] User Basic Information

[1652] Data related to life events

[1653] Expenditure Data

[1654] Specific examples

[1655] Specific examples of exam support

[1656] User: Candidates enter basic information in the LINE app and access the system.

[1657] Server: Calculates the number of days until the exam date and generates a daily study plan. It also uses the Google Cloud Natural Language API to generate exam advice from the conversation history.

[1658] Device: Every day, the user will receive a LINE message informing them of today's study content and progress check reminders.

[1659] Specific examples of asset formation

[1660] User: Makes payments using electronic payment systems on a daily basis.

[1661] Server: Aggregates spending data at the end of the month, generates spending analysis reports, and provides savings advice based on prompts generated by a generative AI model.

[1662] Device: Report results and saving advice are notified to the user via smartphone or smart glasses.

[1663] Prompt Sentence Examples

[1664] 1. "Provide money-saving advice. User spending categories are food, transportation, entertainment, and health."

[1665] 2. "Please create a study plan taking into account the number of days until the exam. You are currently 30% complete."

[1666] This enables the system to comprehensively support users in a wide range of life events, and also to provide appropriate proposals and financial advice in real time, reducing the burden on users.

[1667] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1668] Step 1:

[1669] User enters basic information

[1670] A user uses a smartphone app to enter their basic information (age, occupation, family composition, etc.). The entered information is temporarily saved on the device and then sent to the server. The input data is sent to the server in JSON format.

[1671] Step 2:

[1672] Saving basic information to a database

[1673] The server saves the basic information data sent from the user's device in the Firebase real-time database. Specifically, the data is stored in the database using the user ID as a key, making it available for later processing.

[1674] Step 3:

[1675] Event data collection

[1676] Users regularly use messaging apps such as LINE to input data related to life events, such as exam schedules or wedding dates. This input data is temporarily stored on the device and then sent to the server.

[1677] Step 4:

[1678] Event data storage in a database

[1679] The server receives the collected event data and stores it in a Firebase database, along with metadata such as the event type and date, allowing for efficient searching and analysis.

[1680] Step 5:

[1681] Data analysis using natural language processing

[1682] The server uses the Google Cloud Natural Language API to analyze user interaction history and event data. The input data is text data from the conversation. The analysis results returned by the API include keyword extraction, sentiment analysis, and context understanding. These analysis results are used as the basis for generating suggestions.

[1683] Step 6:

[1684] Proposal generation using generative AI models

[1685] The server inputs a prompt sentence (e.g., "Please provide money-saving advice. The user's spending categories are food, transportation, entertainment, and health.") into the generative AI model, which generates appropriate suggestions. The generated suggestions are returned to the server in text format, which is used to determine the content of the notification to the user.

[1686] Step 7:

[1687] Acquiring expenditure data from electronic payment systems

[1688] The server obtains the user's expenditure information using the API of the electronic payment system (e.g., PayPay). The obtained data is divided into each item (e.g., date, category, amount) and analyzed. The expenditure data is sent to the server in JSON format and stored in Firebase.

[1689] Step 8:

[1690] Analyzing spending data and generating financial advice

[1691] The server analyzes the acquired spending data and generates monthly and weekly reports. It uses a generative AI model to generate financial advice based on prompts (e.g., "Please analyze my spending at the end of the month."). The generated advice is then sent to the user.

[1692] Step 9:

[1693] Send a reminder

[1694] The device notifies the user of suggestions and reminders received from the server. For example, a reminder such as, "Focus on studying math and English today." Notifications are sent via LINE or the notification function of the smart glasses.

[1695] This enables the system to comprehensively support users in a wide range of life events and provide appropriate proposals and financial advice in real time.

[1696] 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.

[1697] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation) by combining it with an emotion engine that recognizes the user's emotions to make more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. Furthermore, it collects and analyzes data related to events through communication with the user and provides the user with necessary information and advice. It also works with electronic payment systems to manage the user's spending information and provide financial advice. By incorporating an emotion engine, it is possible to adjust suggestions and feedback based on the user's emotional state.

[1698] System Components

[1699] 1. User Device

[1700] A device that allows users to access the system via messaging apps such as LINE.

[1701] Enter basic information, submit data related to your event, receive suggestions, and more.

[1702] 2. Server

[1703] Receives basic information and event data sent by users and stores them in a database.

[1704] Conduct data analysis and generate optimal suggestions for users.

[1705] It works in conjunction with electronic payment systems to manage expenditure information.

[1706] Generates and transmits financial advice to users.

[1707] It has an emotion engine that recognizes the user's emotions and adjusts suggestions accordingly.

[1708] 3. Database

[1709] Stores and manages user basic information, event data, expenditure information, emotional data, etc.

[1710] 4. Emotion Engine

[1711] Recognizes and analyzes emotions from user input, voice data, and dialogue content.

[1712] Specific processing content and operation of the program

[1713] 1. User registration and initial settings

[1714] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[1715] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[1716] Server: Saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[1717] 2. Event data collection and analysis

[1718] User: Uses the LINE app on a daily basis to interact with the assist app.

[1719] Terminal: Collects the user's interaction history and periodically sends it to the server.

[1720] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[1721] Server: Generates suggestions for users based on the analysis results.

[1722] 3. Operation of the Emotion Engine

[1723] Server: Collects and analyzes emotion data from user input and dialogue.

[1724] Emotion engine: Sends the results of emotion analysis to the server.

[1725] Server: Based on the sentiment analysis results, the server adjusts the suggestions and provides them to the user.

[1726] 4. Providing concrete support

[1727] Exam

[1728] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[1729] Emotion engine: If the user loses motivation, it will suggest encouraging messages or a break.

[1730] Device: Send study plans and reminders to users.

[1731] find work

[1732] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[1733] Emotion Engine: Provides relaxation and stress management advice based on the user's stress level.

[1734] Terminal: Notifies the user of interview dates and interview tips.

[1735] marriage

[1736] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[1737] Emotion engine: Flexible adjustment of advice and suggestions based on the user's emotional state.

[1738] Device: Send a reminder to visit wedding venues.

[1739] Childbirth and childcare

[1740] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[1741] Emotion engine: Detects anxiety and stress about child-rearing and sends appropriate support messages.

[1742] Device: Sends users reminders of childcare schedules and important dates.

[1743] Retirement and nursing care

[1744] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[1745] Emotion Engine: Monitors the user's emotional state and provides emotional support when needed.

[1746] Device: Send reminders for regular health checks.

[1747] Asset formation

[1748] Server: Receives spending data from the electronic payment system and generates monthly reports.

[1749] Server: Provides advice on saving and asset management based on the analysis of spending data.

[1750] Emotion Engine: If the user's emotional state indicates financial stress, it will provide appropriate advice and offer payment instalments.

[1751] Device: Send asset management reminders to users periodically.

[1752] Specific examples

[1753] 1. Specific examples of exam support

[1754] User: The candidate enters basic information on LINE and adds the assist app.

[1755] Server: Calculates the number of days until the exam date and generates a daily study plan.

[1756] Emotion Engine: Detects when users are losing motivation and suggests encouraging messages or breaks.

[1757] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[1758] 2. Specific examples of marriage support

[1759] User: An engaged couple enters wedding preparation information on LINE.

[1760] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[1761] Emotion Engine: Detects when the user is feeling stressed and provides advice on how to relax.

[1762] Device: Receive reminders for meetings and tour dates via LINE.

[1763] 3. Specific examples of asset formation

[1764] User: Makes payments using electronic payment systems on a daily basis.

[1765] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[1766] Emotion Engine: Detects when users are experiencing financial stress and provides appropriate advice and payment instalments.

[1767] Device: Report results and saving advice are sent to the user via LINE.

[1768] This system connects a server, user devices, a database, and an emotion engine to provide users with comprehensive information and support. Through a single app, users can receive support for a wide range of life events, as well as suggestions and advice tailored to their emotional state.

[1769] The processing flow will be explained below.

[1770] Specific processing steps

[1771] User registration and initial settings

[1772] Step 1:

[1773] The user adds the Assist app via LINE and opens the registration page.

[1774] Step 2:

[1775] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[1776] Step 3:

[1777] The user enters basic information and presses the submit button.

[1778] Step 4:

[1779] The terminal sends the entered basic information to the server.

[1780] Step 5:

[1781] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[1782] Event data collection and analysis

[1783] Step 1:

[1784] The user uses LINE on a daily basis to chat with the assist app.

[1785] Step 2:

[1786] The terminal appropriately collects the user's chat history and transmits it to the server.

[1787] Step 3:

[1788] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[1789] Step 4:

[1790] The server prepares to provide the user with necessary information and advice based on the predicted event.

[1791] Emotion Engine Operation

[1792] Step 1:

[1793] The user types or sends a voice message via LINE.

[1794] Step 2:

[1795] The device sends user input and voice messages to the emotion engine.

[1796] Step 3:

[1797] An emotion engine analyzes the input data and identifies the user's emotional state.

[1798] Step 4:

[1799] The emotion engine transmits the identified emotion data to a server.

[1800] Step 5:

[1801] The server adjusts the suggestions and advice based on the emotional data.

[1802] Providing concrete support

[1803] Exam

[1804] Step 1:

[1805] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[1806] Step 2:

[1807] The emotion engine checks the user's motivation and suggests encouraging messages or breaks as needed.

[1808] Step 3:

[1809] The server generates study progress checks and reminders and sends them as LINE messages.

[1810] Step 4:

[1811] The device will remind the user about study apps and reference books.

[1812] find work

[1813] Step 1:

[1814] The server collects the user's work history data and retrieves job information via scraping or API.

[1815] Step 2:

[1816] The server compiles a list of job information suitable for the user and sends it via LINE.

[1817] Step 3:

[1818] The emotion engine identifies the user's stress level and provides relaxation and stress management advice.

[1819] Step 4:

[1820] The device sends the user interview schedule reminders and content related to interview preparation.

[1821] marriage

[1822] Step 1:

[1823] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[1824] Step 2:

[1825] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[1826] Step 3:

[1827] The emotion engine checks the user's emotional state and flexibly adjusts advice and suggestions.

[1828] Step 4:

[1829] The device will send you a reminder to schedule a tour.

[1830] Childbirth and childcare

[1831] Step 1:

[1832] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[1833] Step 2:

[1834] The emotion engine detects the user's anxiety and stress about child-rearing and sends support messages.

[1835] Step 3:

[1836] The device will remind you of childcare schedules and vaccination dates.

[1837] Step 4:

[1838] The server analyzes the user's questions and concerns and provides appropriate advice.

[1839] Retirement and nursing care

[1840] Step 1:

[1841] The server monitors the user's health status and periodically sends health check questionnaires.

[1842] Step 2:

[1843] An emotion engine checks the user's emotional state and provides emotional support as needed.

[1844] Step 3:

[1845] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[1846] Step 4:

[1847] The device sends the user health checklists and reminders for regular checkups.

[1848] Asset formation

[1849] Step 1:

[1850] A server retrieves spending data from the electronic payment system and generates monthly reports.

[1851] Step 2:

[1852] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[1853] Step 3:

[1854] The emotion engine identifies the user's financial stress and provides optimal advice and payment installment suggestions.

[1855] Step 4:

[1856] The terminal notifies the user of periodic asset management reminders.

[1857] PayPay integration

[1858] Step 1:

[1859] A user makes everyday payments through an electronic payment system.

[1860] Step 2:

[1861] The server periodically collects user spending data through the API of the electronic payment system.

[1862] Step 3:

[1863] The server analyzes the collected spending data to detect abnormal or excessive spending.

[1864] Step 4:

[1865] The emotion engine checks the user's emotional state and provides appropriate feedback and advice.

[1866] Step 5:

[1867] The device will notify the user of their spending status and savings suggestions via LINE.

[1868] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[1869] Example 2

[1870] 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."

[1871] Users face challenges in receiving appropriate and timely information and advice for major life events. Furthermore, personalized support tailored to the user's emotional and financial situation is rarely provided for each event. Furthermore, there is a lack of comprehensive management of expenditure information and integrated analysis of data related to life events. To address these challenges, a comprehensive system is needed to support users' overall life events.

[1872] 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.

[1873] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data using natural language processing technology, means for making personalized suggestions to the user based on the analysis results, means for providing the suggestions to the user, means for collecting and analyzing emotional data of the user using emotion analysis technology, means for adjusting the suggestions based on the emotion analysis results, means for analyzing the user's expenditure information in cooperation with an electronic payment system, and means for providing the user with financial advice based on the analyzed expenditure information. This allows the user to receive comprehensive support for each life event through a single system, and provides personalized suggestions and advice tailored to their emotions and financial status.

[1874] "Means for acquiring basic information about the user" refers to a function for collecting basic information such as the user's age, occupation, and family composition.

[1875] "Means for saving acquired basic information in a database" refers to a function for saving basic information collected from users in a dedicated database.

[1876] "Means of collecting event-related data through communication with users" refers to a function for interactively collecting information related to a user's life events through messaging apps, etc.

[1877] "Means for analyzing collected data using natural language processing technology" refers to a function that uses natural language processing technology (e.g., text analysis algorithms) to analyze collected text data.

[1878] "Means of making personalized suggestions to users based on the analysis results" refers to a function that makes optimal suggestions to users based on insights gained from analyzed data.

[1879] The "means for providing suggestions to the user" refers to a function for notifying the user of the generated suggestions.

[1880] "Means of collecting and analyzing user emotional data using emotion analysis technology" refers to a function that uses technology to extract and analyze emotional information from user input and dialogue.

[1881] "Means for adjusting suggestions based on emotion analysis results" refers to a function for appropriately changing the suggestions and advice provided depending on the user's emotional state.

[1882] "Means for analyzing user expenditure information in cooperation with an electronic payment system" refers to a function for collecting and analyzing user expenditure data in cooperation with an electronic payment service.

[1883] "Means for providing financial advice to the user based on the analyzed expenditure information" refers to a function for providing appropriate financial advice to the user based on the analyzed expenditure data.

[1884] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. It collects and analyzes data related to events through communication with the user, and provides the user with the information and advice they need. It also works with electronic payment systems to manage the user's spending information and provide financial advice.

[1885] Specific examples of hardware and software used

[1886] User device: Messaging app running on a smartphone or tablet (e.g., LINE)

[1887] Server: Cloud server or local server (e.g. AWS, Google Cloud)

[1888] Database: SQL or NoSQL database (e.g. MySQL, MongoDB)

[1889] Natural language processing technology: text analysis algorithms (e.g., spaCy, NLTK)

[1890] Sentiment engine: Sentiment analysis algorithm (e.g. IBM Watson Tone Analyzer, Azure Text Analytics)

[1891] Specific examples

[1892] 1. User registration and initial settings

[1893] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.).

[1894] The terminal displays a basic information input form to the user and sends the submitted data to the server.

[1895] The server saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[1896] 2. Event data collection and analysis

[1897] Users interact with the assist app using the LINE app on a daily basis.

[1898] The terminal collects the user's interaction history and periodically transmits it to the server.

[1899] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[1900] The server generates suggestions for the user based on the analysis results.

[1901] 3. Operation of the Emotion Engine

[1902] The server collects and analyzes emotional data from user input and dialogue.

[1903] The emotion engine sends the results of the emotion analysis to the server.

[1904] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[1905] Prompt Sentence Examples

[1906] 1. Test-taking support prompts

[1907] "Generate encouraging messages when your motivation to study is low"

[1908] 2. Marriage Support Prompts

[1909] "If you're feeling stressed while planning your wedding, we'll generate advice on how to relax."

[1910] 3. Wealth Building Prompts

[1911] "Generate monthly expenditure analysis reports based on data from the electronic payment system."

[1912] The basic components of this system are a user device, a server, a database, a natural language processing tool, and an emotion engine, all working closely together. Users can receive support for a variety of life events through a single application. Emotion analysis also makes it possible to provide more personalized suggestions in real time. In this way, users can receive comprehensive and personalized assistance.

[1913] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1914] System program processing flow

[1915] Processing Steps:

[1916] Step 1:

[1917] Step 2:

[1918] Step 3:

[1919] ...

[1920] Processing step details

[1921] Step 1:

[1922] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.)

[1923] Input: User's basic information data

[1924] Action: The user opens the LINE app and taps the "Assist App" button. A basic information input form is displayed. The user enters basic information such as age, occupation, and family composition, and presses the "Send" button.

[1925] Output: Basic information data entered by the user

[1926] Step 2:

[1927] The device displays a form for inputting basic information to the user and sends the submitted data to the server.

[1928] Input: Basic information entered by the user

[1929] Operation: The terminal displays a basic information input form to the user, converts the information entered by the user into a data format to be sent to the server, and sends the data to the server in the form of an HTTP request.

[1930] Output: Basic information sent to the server

[1931] Step 3:

[1932] The server saves the basic information sent to the database and sends a registration completion message to the user via LINE.

[1933] Input: Basic information received by the server

[1934] Operation: The server saves basic information to the database. After saving is complete, it generates a registration completion message and sends it to the user using the LINE API.

[1935] Output: Basic information stored in the database and a successful registration message sent to the user.

[1936] Step 4:

[1937] Users interact with the Assist App using the LINE app on a daily basis.

[1938] Input: User interaction message

[1939] How it works: A user sends a message about a daily event through the LINE app.

[1940] Output: Interactive message from the user

[1941] Step 5:

[1942] The device collects the user's interaction history and periodically sends it to the server.

[1943] Input: User interaction history

[1944] How it works: The device collects conversation history via the LINE API and uploads it to the server on a specified schedule (e.g., at a certain time every day).

[1945] Output: Dialogue history sent to the server

[1946] Step 6:

[1947] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[1948] Input: Dialogue history received by the server

[1949] How it works: The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the dialogue history and perform text tokenization, sentiment analysis, and semantic analysis to identify the user's emotional state and information needs.

[1950] Output: Analyzed user status and desired information

[1951] Step 7:

[1952] The server generates suggestions for the user based on the analysis results.

[1953] Input: Analyzed user status and desired information

[1954] How it works: The server uses the generative AI model to generate suggestions based on the analysis results. The suggestions are generated based on the prompt (e.g., "If your motivation to study is declining, generate an encouraging message").

[1955] Output: Generated proposals

[1956] Step 8:

[1957] The server provides suggestions to the user via LINE

[1958] Input: Generated proposals

[1959] How it works: The server uses the LINE API to send the generated suggestions to the user.

[1960] Output: Suggestions sent to the user

[1961] Step 9:

[1962] The server collects and analyzes emotional data from user input and dialogue.

[1963] Input: User input and interaction data

[1964] How it works: The server uses the emotion engine to analyze the user's emotional state from their input and dialogue. It uses an emotion analysis algorithm to analyze the input text and identify the user's emotional state.

[1965] Output: Parsed emotion data

[1966] Step 10:

[1967] The emotion engine sends the results of emotion analysis to the server.

[1968] Input: Parsed emotion data

[1969] How it works: The emotion engine sends the analysis results to the server, which then updates the user's emotional state based on the analysis results.

[1970] Output: Sentiment analysis results sent to the server

[1971] Step 11:

[1972] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[1973] Input: Sentiment analysis results

[1974] How it works: The server adjusts the generated suggestions based on the results of emotion analysis. For example, if the user is feeling stressed, it adds suggestions for relaxation methods. The adjusted suggestions are then sent to the user via LINE.

[1975] Output: Adjusted proposal and send to user

[1976] (Application example 2)

[1977] 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."

[1978] Conventional user support systems make suggestions based on the user's basic information and event data, but they have the problem of not being able to take into account the user's emotional state. As a result, they are unable to provide personalized advice that adapts to the user's emotions, making it difficult to provide effective user support. In particular, because they do not take into account emotional changes related to financial stress or life events, they are unable to provide appropriate support that meets the user's needs.

[1979] 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.

[1980] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, and means for recognizing the user's emotions and adjusting the suggestions based thereon, thereby enabling the provision of personalized suggestions and financial advice that take the user's emotional state into consideration.

[1981] "Basic user information" refers to basic data about each individual user, such as the user's age, occupation, family structure, and income.

[1982] A "database" is an electronic information system that stores acquired information and data and allows it to be searched and updated as needed.

[1983] "Communication" refers to the means by which information is exchanged between users and systems, including messaging apps and email.

[1984] "Event-related data" is information related to major events in a user's life, such as taking an exam, getting a job, getting married, giving birth, raising children, retirement, caring for elderly relatives, and building assets.

[1985] "Recommendations" refers to specific advice, plans, information, etc. provided to users based on collected and analyzed data.

[1986] An "electronic payment system" is a system that allows users to pay electronically when purchasing goods or using services, and includes credit cards and digital wallets.

[1987] "Expense information" is data relating to the flow of money involved in purchases and payments made by a user.

[1988] "Financial advice" refers to recommendations on the user's household finances, saving methods, investment strategies, etc. based on expenditure and income information.

[1989] Recognizing "emotions" means analyzing and identifying a user's emotional state from their text messages, voice, facial expressions, etc.

[1990] "Emotion analysis" is the process of using data processing techniques to recognize emotions to determine a user's emotional state and sending that information to a server.

[1991] This invention is a system that provides comprehensive support for major events in a user's life, and by combining it with an emotion engine that recognizes the user's emotions, it makes personalized suggestions and advice. Specific embodiments for implementing this invention are described below.

[1992] System Configuration

[1993] The system consists of the following components:

[1994] 1. User Device

[1995] Users access the system using their smartphones.

[1996] Enter basic information, submit data related to your event, and receive suggestions.

[1997] To communicate with the system, messaging apps such as LINE are used.

[1998] 2. Server

[1999] Receives basic information and event data and stores it in a database.

[2000] Data analysis is performed to generate optimal suggestions for users.

[2001] It works in conjunction with electronic payment systems to manage expenditure information.

[2002] It uses an emotion engine to analyze the user's emotional state and tailor suggestions and advice.

[2003] 3. Database

[2004] Stores and manages user basic information, event data, expenditure information, and emotional data.

[2005] 4. Emotion Engine

[2006] It analyzes the user's input and voice data to recognize their emotional state.

[2007] Hardware and software used

[2008] Hardware: Smartphone (iOS, Android)

[2009] software:

[2010] LINE Messaging API (sending messages, notifications)

[2011] AWS Lambda (serverless computing)

[2012] AWS RDS (database)

[2013] Amazon Rekognition (emotion engine)

[2014] NumPy, Pandas (data analysis)

[2015] TensorFlow (sentiment analysis model)

[2016] Program processing overview

[2017] 1. User registration and initial settings

[2018] The user enters basic information using the LINE app and sends it to the server. The server saves the basic information in a database and sends a registration completion message.

[2019] 2. Data collection and analysis

[2020] Users regularly send event-related data and information about their emotional state via the LINE app.

[2021] The server periodically receives this data and analyzes it using natural language processing technology. The analyzed information is then stored in a database.

[2022] 3. Spending data management and financial advice

[2023] Spending data is collected from users' electronic payment systems and aggregated and analyzed on the server.

[2024] Based on the analysis results, appropriate financial advice is provided to the user.

[2025] 4. Operation of the Emotion Engine

[2026] The emotion engine recognizes emotions from the user's text messages and voice data and sends that information to the server.

[2027] The server adjusts the suggestions and advice based on the results of the emotion analysis.

[2028] Specific examples

[2029] 1. Exam support

[2030] Users input their exam dates and study plans, and the server creates a daily study plan based on that information, and sends encouraging messages if the emotion engine detects a drop in motivation.

[2031] Example prompt: "I'm a 30-year-old office worker. My expenses are piling up at the end of the month. I'm feeling stressed. Please suggest some appropriate advice."

[2032] 2. Asset formation

[2033] The server aggregates monthly spending data, analyzes the user's emotional state, and provides advice to ease financial stress.

[2034] Example prompt: "I'm busy planning my wedding. Can you offer some advice on how to reduce stress?"

[2035] This allows for personalized offers and financial advice that take into account the user's emotional state.

[2036] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2037] Step 1:

[2038] User registration and basic information entry

[2039] Input: The user uses the LINE app to enter basic information such as age, occupation, and family composition.

[2040] Specific operation: The device displays a basic information input form via the LINE Messaging API and sends the information entered by the user to the server.

[2041] Data processing: The server stores the received basic information in AWS RDS via AWS Lambda.

[2042] Output: The server generates a registration completion message and sends it to the user as a LINE message.

[2043] Step 2:

[2044] Event data collection

[2045] Input: Users use the LINE app to input information related to events on a daily basis, such as the progress of their exam preparations or the status of their wedding preparations.

[2046] Specific operation: The terminal periodically collects the user's interaction history and sends it to the server.

[2047] Data processing: The server analyzes the received event data using natural language processing (NLP) technology. Specifically, it saves the dialogue history in text format and appropriately tags it.

[2048] Output: The analysis results are stored in AWS RDS and a feedback message is sent to the user if necessary.

[2049] Step 3:

[2050] Emotion data collection and analysis

[2051] Input: User text messages and voice data.

[2052] Specific operation: The device uses the LINE Messaging API to send text and voice messages to the server.

[2053] Data processing: The server uses Amazon Rekognition to perform sentiment analysis and identify the user's emotional state.

[2054] Output: The results of the sentiment analysis are stored in AWS RDS and used to inform tailoring suggestions based on the analysis results.

[2055] Step 4:

[2056] Spending data management and financial advice

[2057] Input: Spending data obtained from the user's electronic payment system.

[2058] Specific operation: The terminal periodically sends daily expenditure data to the server.

[2059] Data processing: The server aggregates and analyzes spending data using NumPy and Pandas, and generates monthly reports.

[2060] Output: Financial advice based on the analysis results is sent to the user as a LINE message.

[2061] Step 5:

[2062] Proposal generation and delivery

[2063] Input: Basic information, event data, sentiment data, and analysis results of expenditure data.

[2064] Specific operation: The server integrates the analysis results and generates optimal suggestions for the user. It uses a generative AI model (TensorFlow) to predict user behavior.

[2065] Data calculation: Calculates optimal suggestions and advice based on the user's situation and stores them on the server.

[2066] Output: The generated suggestion is notified to the user as a LINE message.

[2067] Specific examples

[2068] Exam support suggestions:

[2069] Example prompt: "I'm a 30-year-old office worker. My expenses are piling up at the end of the month. I'm feeling stressed. Please suggest some appropriate advice."

[2070] Through the specific processing of each step and the explanation of the input and output based on it, the system can provide comprehensive support to the user.

[2071] 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.

[2072] 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.

[2073] 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.

[2074] [Fourth embodiment]

[2075] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2076] 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.

[2077] 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).

[2078] 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.

[2079] 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.

[2080] 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).

[2081] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2082] 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.

[2083] 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.

[2084] 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.

[2085] 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.

[2086] 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.

[2087] 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."

[2088] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). The system acquires basic information about the user and makes suggestions based on that information, allowing the user to obtain the information and advice they need. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[2089] System Components

[2090] 1. User Device

[2091] A device that allows users to access the system via messaging apps such as LINE.

[2092] Enter basic information, submit data related to your event, receive suggestions, and more.

[2093] 2. Server

[2094] Receives basic information and event data sent by users and stores them in a database.

[2095] Conduct data analysis and generate optimal suggestions for users.

[2096] It works in conjunction with electronic payment systems to manage expenditure information.

[2097] Generates and transmits financial advice to users.

[2098] 3. Database

[2099] Stores and manages user basic information, event data, expenditure information, etc.

[2100] Specific processing content and operation of the program

[2101] 1. User registration and initial settings

[2102] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[2103] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[2104] Server: Receives the basic information sent and stores it in a database.

[2105] 2. Event data collection and analysis

[2106] User: Uses the LINE app on a daily basis to interact with the assist app.

[2107] Terminal: Collects the user's interaction history and periodically sends it to the server.

[2108] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[2109] Server: Generates suggestions for users based on the analysis results.

[2110] 3. Providing concrete support

[2111] Exam

[2112] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[2113] Device: Send study plan reminders to users.

[2114] find work

[2115] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[2116] Terminal: Notifies the user of interview dates and interview tips.

[2117] marriage

[2118] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[2119] Device: Send a reminder to visit wedding venues.

[2120] Childbirth and childcare

[2121] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[2122] Device: Sends users reminders of childcare schedules and important dates.

[2123] Retirement and nursing care

[2124] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[2125] Device: Send reminders for regular health checks.

[2126] Asset formation

[2127] Server: Receives spending data from electronic payment systems such as PayPay and generates monthly reports.

[2128] Server: Provides advice on saving and asset management based on the analysis of spending data.

[2129] Device: Send asset management reminders to users periodically.

[2130] Specific examples

[2131] 1. Specific examples of exam support

[2132] User: The candidate enters basic information on LINE and adds the assist app.

[2133] Server: Calculates the number of days until the exam date and generates a daily study plan.

[2134] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[2135] 2. Specific examples of marriage support

[2136] User: An engaged couple enters wedding preparation information on LINE.

[2137] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[2138] Device: Receive reminders for meetings and tour dates via LINE.

[2139] 3. Specific examples of asset formation

[2140] User: Makes payments using PayPay on a daily basis.

[2141] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[2142] Device: Report results and saving advice are sent to the user via LINE.

[2143] This system connects a server, user devices, and databases to provide users with comprehensive information and support. Users can receive various types of support for a wide range of life events through a single app.

[2144] The processing flow will be explained below.

[2145] Specific processing steps

[2146] User registration and initial settings

[2147] Step 1:

[2148] The user adds the Assist app via LINE and opens the registration page.

[2149] Step 2:

[2150] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[2151] Step 3:

[2152] The user enters basic information and presses the submit button.

[2153] Step 4:

[2154] The terminal sends the entered basic information to the server.

[2155] Step 5:

[2156] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[2157] Event data collection and analysis

[2158] Step 1:

[2159] The user uses LINE on a daily basis to chat with the assist app.

[2160] Step 2:

[2161] The terminal appropriately collects the user's chat history and transmits it to the server.

[2162] Step 3:

[2163] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[2164] Step 4:

[2165] The server prepares to provide the user with necessary information and advice based on the predicted event.

[2166] Providing concrete support

[2167] Exam

[2168] Step 1:

[2169] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[2170] Step 2:

[2171] The server generates study progress checks and reminders and sends them as LINE messages.

[2172] Step 3:

[2173] The device will remind the user about study apps and reference books.

[2174] find work

[2175] Step 1:

[2176] The server collects the user's work history data and retrieves job information via scraping or API.

[2177] Step 2:

[2178] The server compiles a list of job information suitable for the user and sends it via LINE.

[2179] Step 3:

[2180] The device sends the user interview schedule reminders and content related to interview preparation.

[2181] marriage

[2182] Step 1:

[2183] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[2184] Step 2:

[2185] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[2186] Step 3:

[2187] The device will send you a reminder to schedule a tour.

[2188] Childbirth and childcare

[2189] Step 1:

[2190] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[2191] Step 2:

[2192] The device will remind you of childcare schedules and vaccination dates.

[2193] Step 3:

[2194] The server analyzes the user's questions and concerns and provides appropriate advice.

[2195] Retirement and nursing care

[2196] Step 1:

[2197] The server monitors the user's health status and periodically sends health check questionnaires.

[2198] Step 2:

[2199] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[2200] Step 3:

[2201] The device sends the user health checklists and reminders for regular checkups.

[2202] Asset formation

[2203] Step 1:

[2204] A server retrieves spending data from the electronic payment system and generates monthly reports.

[2205] Step 2:

[2206] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[2207] Step 3:

[2208] The terminal notifies the user of periodic asset management reminders.

[2209] PayPay integration

[2210] Step 1:

[2211] A user makes everyday payments through an electronic payment system.

[2212] Step 2:

[2213] The server periodically collects user spending data through the API of the electronic payment system.

[2214] Step 3:

[2215] The server analyzes the collected spending data to detect abnormal or excessive spending.

[2216] Step 4:

[2217] The device will notify the user of their spending status and savings suggestions via LINE.

[2218] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[2219] Example 1

[2220] 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."

[2221] Responding to the diverse needs of users during life events requires the collection and analysis of individualized information. However, current systems struggle to comprehensively collect, analyze, propose, manage expenses, and provide financial advice. Furthermore, the lack of a means to provide users with timely reminders and advice can hinder the smooth progression of life events.

[2222] 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.

[2223] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data with a natural language processing engine and making suggestions to the user, means for providing the suggestions to the user, means for aggregating user expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the aggregated expenditure information, and means for notifying the user of the suggestions and advice via a messaging app. This enables users to receive appropriate support for each life event in a centralized manner, starting with registering their basic information, and also enables smooth management of the progress of events through timely notifications.

[2224] "User" refers to an individual who uses this system to register basic information, input information related to life events, receive advice, etc.

[2225] "Basic information" refers to basic personal data such as the user's age, occupation, and family structure.

[2226] "Database" refers to a storage device for storing and managing basic user information, event data, expenditure information, etc.

[2227] "Event Data" refers to data entered into the system by a user regarding information about a life event and its progress.

[2228] A "natural language processing engine" refers to software that analyzes text data collected from users, understands its meaning, and generates appropriate suggestions.

[2229] "Suggestion" refers to specific guidelines for action or advice for the user that are generated based on the analysis results of the natural language processing engine.

[2230] "Electronic payment system" refers to a system that electronically processes financial transactions made by users and provides expenditure data.

[2231] "Expenditure information" refers to data regarding a user's economic activity obtained from an electronic payment system.

[2232] "Financial advice" refers to specific advice for the user to efficiently manage assets and save money based on the analysis of expenditure information.

[2233] "Messaging app" refers to a communication application that allows a user to interact with a system, enter information, or receive suggestions.

[2234] MODE FOR CARRYING OUT THE INVENTION

[2235] This invention is a system that provides comprehensive support for users regarding life events (e.g., exams, employment, marriage, childbirth, childcare, retirement, nursing care, asset formation). The system acquires basic information about the user, generates suggestions based on that information, and notifies the user at appropriate times. It also works in conjunction with an electronic payment system to manage the user's spending information and provide financial advice.

[2236] Hardware and software used

[2237] 1. Hardware

[2238] User device: Mobile devices such as smartphones and tablets

[2239] Server: A virtual server on the cloud (e.g., AWS or Google Cloud Platform)

[2240] Database Server: Cloud data store (e.g., Amazon RDS or Google Cloud SQL)

[2241] 2. Software

[2242] Messaging app: LINE

[2243] Database Management System (DBMS): MySQL, PostgreSQL

[2244] Natural language processing engine: Google Cloud Natural Language API, IBM Watson

[2245] Payment system: PayPay

[2246] A description of what the program does

[2247] The server receives basic information and event data sent by the user and stores it in a database. The server analyzes the necessary information for each life event, generates appropriate suggestions, and notifies the user via a messaging app. It also works with an electronic payment system to manage and compile the user's spending information and provide financial advice. Meanwhile, the user's device allows the user to access the system through messaging apps such as LINE to enter basic information, send event-related data, and receive suggestions. The database stores and manages the user's basic information, event data, spending information, etc.

[2248] Specific processing examples

[2249] Exam support

[2250] User: The candidate enters basic information (e.g., age, desired school, exam date) on LINE and adds the assist app.

[2251] Server: Calculates the number of days until the exam date and generates a daily study plan.

[2252] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[2253] Example prompt:

[2254] Create a daily study plan for your students and share it with them via LINE. Please take into account the number of days until the exam.

[2255] Marriage Support

[2256] User: An engaged couple enters wedding preparation information (e.g., wedding date, preparation status) on LINE.

[2257] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[2258] Device: Receive reminders for meetings and tour dates via LINE.

[2259] Example prompt:

[2260] Keep engaged couples on track with a list of wedding planning tasks and schedules. Receive reminders for meetings and viewing dates.

[2261] Asset formation support

[2262] User: Makes payments using PayPay on a daily basis.

[2263] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[2264] Device: Report results and saving advice are sent to the user via LINE.

[2265] Example prompt:

[2266] Generate monthly reports based on spending data from the electronic payment system and provide users with money-saving advice. Notify users of the reports and advice via LINE.

[2267] This system provides comprehensive information and support to users by linking a server, user devices, and databases. Users can receive various types of support for a wide range of life events through a single app.

[2268] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2269] System program processing flow

[2270] Step 1: User registration and initial setup

[2271] Input: The user adds the Assist app through the LINE app and enters basic information (age, occupation, family composition, etc.).

[2272] Output: Basic information is sent to the server and stored in a database.

[2273] Specific actions

[2274] User: Adds the Assist app as a friend in the LINE app, and enters his age (30), occupation (engineer), and family composition (wife and two children).

[2275] Terminal: Displays a form for inputting basic information and sends the input information to the server.

[2276] Server: Receives the basic information sent and saves it in the database as "User ID 123".

[2277] Step 2: Collect and analyze event data

[2278] Input: The user interacts with the Assist App using the LINE app on a daily basis and provides event-related information.

[2279] Output: The server analyzes the dialogue history, identifies the user's state and requests, and saves the analysis results.

[2280] Specific actions

[2281] User: Sends a message on LINE saying, "I have an exam this weekend. How should I prepare?"

[2282] Terminal: Record this message and send it to the server.

[2283] Server: Using the Google Cloud Natural Language API, extract keywords such as "exam" and "preparation" and identify that the user is looking to prepare for an exam. Save the analysis results.

[2284] Step 3: Generate and deliver proposals

[2285] Input: The server generates optimal suggestions based on the analysis results and event-related information.

[2286] Output: The proposal is sent to the user terminal and the user is notified.

[2287] Specific actions

[2288] Server: Based on the analysis results, generate suggestions for "study methods during exam preparation."

[2289] Device: Send a notification via LINE saying, "Starting today, use this study book to study for one hour every night in preparation for this weekend's exam."

[2290] Step 4: Collect and analyze spending data

[2291] Input: Users routinely make payments using electronic payment systems.

[2292] Output: At the end of the month, spending data is compiled and analyzed to generate reports and recommendations.

[2293] Specific actions

[2294] User: Makes daily payments using electronic payment systems such as PayPay.

[2295] Server: At the end of the month, spending data is collected using PayPay's API and aggregated and analyzed.

[2296] Server: Based on the aggregated expenditure data, generate "This month's expenditure status and saving advice."

[2297] Step 5: Providing financial advice

[2298] Input: The server creates advice based on the aggregated expenditure data.

[2299] Output: The created advice is sent to the user's terminal and notified to the user.

[2300] Specific actions

[2301] Server: Based on expenditure data, it generates advice such as, "You've spent a lot on eating out this month, so try to save money next month."

[2302] Device: Receive a notification via LINE saying, "This month's spending: Eating out is expensive. To save money, try cooking at home twice a week."

[2303] The above is a specific flow of the processing steps of the system program.

[2304] (Application example 1)

[2305] 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."

[2306] Conventional systems have struggled to provide users with appropriate information and financial advice related to life events. Furthermore, managing events and analyzing expenditure data required manual tasks, placing a significant burden on users. Furthermore, they were unable to analyze dialogue history using natural language processing or make appropriate suggestions in real time using generative AI models. Therefore, a new system is needed that efficiently provides users with the information and advice they need for major life events.

[2307] 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.

[2308] In this invention, the server includes means for acquiring basic information about a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, means for performing natural language processing using a generative AI model, and means for generating suggestions from the user's dialogue history using prompt sentences. This enables comprehensive support for the user's life events and the provision of appropriate suggestions and financial advice in real time.

[2309] The "means for acquiring basic information about the user" is a means for collecting basic information about the user, such as age, occupation, and family structure.

[2310] "Means for storing in a database" refers to means for safely and effectively storing the acquired basic information of users.

[2311] The "means for collecting data related to events" is a means for collecting data related to life events such as taking an exam, getting a job, getting married, etc. through communication with the user.

[2312] The "means for analyzing data and making suggestions to the user" is a means for analyzing collected data and generating suggestions suited to the user's situation.

[2313] The "means for providing to the user" refers to a means for notifying or displaying the generated proposal to the user.

[2314] The "means for analyzing user expenditure information in cooperation with an electronic payment system" refers to means for analyzing user expenditure data obtained from an electronic payment system.

[2315] The "means for providing financial advice" is a means for providing the user with advice on financial management and saving based on the analyzed expenditure information.

[2316] "Means for performing natural language processing using a generative AI model" refers to means for analyzing a user's dialogue history, etc., using a generative AI model.

[2317] The "means for generating a suggestion from a user's dialogue history using a prompt sentence" refers to a means for generating an appropriate suggestion for a user based on a dialogue history in response to a specific instruction or question.

[2318] The "means for sending reminders" is a means for sending notifications related to life events or deadlines set by the user.

[2319] The "means for generating periodic expenditure reports" refers to a means for aggregating the user's expenditure status at regular intervals and generating a report.

[2320] This invention is a system that provides comprehensive support for users regarding life events. The main components of the system include a user terminal, a server, and a database. The functions of the invention are realized by the cooperation of these components.

[2321] 1. User Device

[2322] The user terminal uses a device such as a smartphone or smart glasses and performs the following functions:

[2323] Input of basic information and event data: Users enter basic information (age, occupation, family composition, etc.) and event-related data through a dedicated app. For example, they can access the system using a messaging app such as LINE.

[2324] Data transmission: Collected basic information and event data are sent to the server.

[2325] Receiving suggestions and reminders: Receives suggestions and reminders generated from the server and notifies the user.

[2326] 2. Server

[2327] The server receives and processes the data sent from the above user terminals. It fulfills the following roles.

[2328] Data storage: The server securely stores basic user information and event data using a real-time database such as Firebase.

[2329] Data analysis: Perform natural language processing using Google Cloud Natural Language API, etc. Analyze user interaction history and event data to generate appropriate suggestions based on user requests.

[2330] Integration with electronic payment systems: PayPay's API is used to obtain user spending data and analyze it to generate financial advice for users.

[2331] Generative AI model: A generative AI model is used to generate optimal advice and suggestions for the user based on the prompt text.

[2332] 3. Database

[2333] The database (e.g., Firebase Firestore) stores and manages the following data:

[2334] User Basic Information

[2335] Data related to life events

[2336] Expenditure Data

[2337] Specific examples

[2338] Specific examples of exam support

[2339] User: Candidates enter basic information in the LINE app and access the system.

[2340] Server: Calculates the number of days until the exam date and generates a daily study plan. It also uses the Google Cloud Natural Language API to generate exam advice from the conversation history.

[2341] Device: Every day, the user will receive a LINE message informing them of today's study content and progress check reminders.

[2342] Specific examples of asset formation

[2343] User: Makes payments using electronic payment systems on a daily basis.

[2344] Server: Aggregates spending data at the end of the month, generates spending analysis reports, and provides savings advice based on prompts generated by a generative AI model.

[2345] Device: Report results and saving advice are notified to the user via smartphone or smart glasses.

[2346] Prompt Sentence Examples

[2347] 1. "Provide money-saving advice. User spending categories are food, transportation, entertainment, and health."

[2348] 2. "Please create a study plan taking into account the number of days until the exam. You are currently 30% complete."

[2349] This enables the system to comprehensively support users in a wide range of life events, and also to provide appropriate proposals and financial advice in real time, reducing the burden on users.

[2350] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2351] Step 1:

[2352] User enters basic information

[2353] A user uses a smartphone app to enter their basic information (age, occupation, family composition, etc.). The entered information is temporarily saved on the device and then sent to the server. The input data is sent to the server in JSON format.

[2354] Step 2:

[2355] Saving basic information to a database

[2356] The server saves the basic information data sent from the user's device in the Firebase real-time database. Specifically, the data is stored in the database using the user ID as a key, making it available for later processing.

[2357] Step 3:

[2358] Event data collection

[2359] Users regularly use messaging apps such as LINE to input data related to life events, such as exam schedules or wedding dates. This input data is temporarily stored on the device and then sent to the server.

[2360] Step 4:

[2361] Event data storage in a database

[2362] The server receives the collected event data and stores it in a Firebase database, along with metadata such as the event type and date, allowing for efficient searching and analysis.

[2363] Step 5:

[2364] Data analysis using natural language processing

[2365] The server uses the Google Cloud Natural Language API to analyze user interaction history and event data. The input data is text data from the conversation. The analysis results returned by the API include keyword extraction, sentiment analysis, and context understanding. These analysis results are used as the basis for generating suggestions.

[2366] Step 6:

[2367] Proposal generation using generative AI models

[2368] The server inputs a prompt sentence (e.g., "Please provide money-saving advice. The user's spending categories are food, transportation, entertainment, and health.") into the generative AI model, which generates appropriate suggestions. The generated suggestions are returned to the server in text format, which is used to determine the content of the notification to the user.

[2369] Step 7:

[2370] Acquiring expenditure data from electronic payment systems

[2371] The server obtains the user's expenditure information using the API of the electronic payment system (e.g., PayPay). The obtained data is divided into each item (e.g., date, category, amount) and analyzed. The expenditure data is sent to the server in JSON format and stored in Firebase.

[2372] Step 8:

[2373] Analyzing spending data and generating financial advice

[2374] The server analyzes the acquired spending data and generates monthly and weekly reports. It uses a generative AI model to generate financial advice based on prompts (e.g., "Please analyze my spending at the end of the month."). The generated advice is then sent to the user.

[2375] Step 9:

[2376] Send a reminder

[2377] The device notifies the user of suggestions and reminders received from the server. For example, a reminder such as, "Focus on studying math and English today." Notifications are sent via LINE or the notification function of the smart glasses.

[2378] This enables the system to comprehensively support users in a wide range of life events and provide appropriate proposals and financial advice in real time.

[2379] 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.

[2380] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation) by combining it with an emotion engine that recognizes the user's emotions to make more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. Furthermore, it collects and analyzes data related to events through communication with the user and provides the user with necessary information and advice. It also works with electronic payment systems to manage the user's spending information and provide financial advice. By incorporating an emotion engine, it is possible to adjust suggestions and feedback based on the user's emotional state.

[2381] System Components

[2382] 1. User Device

[2383] A device that allows users to access the system via messaging apps such as LINE.

[2384] Enter basic information, submit data related to your event, receive suggestions, and more.

[2385] 2. Server

[2386] Receives basic information and event data sent by users and stores them in a database.

[2387] Conduct data analysis and generate optimal suggestions for users.

[2388] It works in conjunction with electronic payment systems to manage expenditure information.

[2389] Generates and transmits financial advice to users.

[2390] It has an emotion engine that recognizes the user's emotions and adjusts suggestions accordingly.

[2391] 3. Database

[2392] Stores and manages user basic information, event data, expenditure information, emotional data, etc.

[2393] 4. Emotion Engine

[2394] Recognizes and analyzes emotions from user input, voice data, and dialogue content.

[2395] Specific processing content and operation of the program

[2396] 1. User registration and initial settings

[2397] User: Add the Assist app via LINE and enter basic information (age, occupation, family composition, etc.).

[2398] Terminal: Displays a form for inputting basic information to the user and sends the submitted data to the server.

[2399] Server: Saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[2400] 2. Event data collection and analysis

[2401] User: Uses the LINE app on a daily basis to interact with the assist app.

[2402] Terminal: Collects the user's interaction history and periodically sends it to the server.

[2403] Server: Analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[2404] Server: Generates suggestions for users based on the analysis results.

[2405] 3. Operation of the Emotion Engine

[2406] Server: Collects and analyzes emotion data from user input and dialogue.

[2407] Emotion engine: Sends the results of emotion analysis to the server.

[2408] Server: Based on the sentiment analysis results, the server adjusts the suggestions and provides them to the user.

[2409] 4. Providing concrete support

[2410] Exam

[2411] Server: Analyzes the user's exam schedule and past study progress, and generates a daily study plan.

[2412] Emotion engine: If the user loses motivation, it will suggest encouraging messages or a break.

[2413] Device: Send study plans and reminders to users.

[2414] find work

[2415] Server: Based on the user's work history data, collects and analyzes suitable job information and makes suggestions.

[2416] Emotion Engine: Provides relaxation and stress management advice based on the user's stress level.

[2417] Terminal: Notifies the user of interview dates and interview tips.

[2418] marriage

[2419] Server: Manages the progress of wedding preparations and suggests necessary tasks and schedules.

[2420] Emotion engine: Flexible adjustment of advice and suggestions based on the user's emotional state.

[2421] Device: Send a reminder to visit wedding venues.

[2422] Childbirth and childcare

[2423] Server: Collects information related to medical institutions and childcare, and provides appropriate information and advice to users.

[2424] Emotion engine: Detects anxiety and stress about child-rearing and sends appropriate support messages.

[2425] Device: Sends users reminders of childcare schedules and important dates.

[2426] Retirement and nursing care

[2427] Server: Monitors the user's health condition and suggests necessary medical and nursing care services.

[2428] Emotion Engine: Monitors the user's emotional state and provides emotional support when needed.

[2429] Device: Send reminders for regular health checks.

[2430] Asset formation

[2431] Server: Receives spending data from the electronic payment system and generates monthly reports.

[2432] Server: Provides advice on saving and asset management based on the analysis of spending data.

[2433] Emotion Engine: If the user's emotional state indicates financial stress, it will provide appropriate advice and offer payment instalments.

[2434] Device: Send asset management reminders to users periodically.

[2435] Specific examples

[2436] 1. Specific examples of exam support

[2437] User: The candidate enters basic information on LINE and adds the assist app.

[2438] Server: Calculates the number of days until the exam date and generates a daily study plan.

[2439] Emotion Engine: Detects when users are losing motivation and suggests encouraging messages or breaks.

[2440] Device: Every morning, the user will receive a LINE message informing them of today's study content and a progress check reminder.

[2441] 2. Specific examples of marriage support

[2442] User: An engaged couple enters wedding preparation information on LINE.

[2443] Server: Lists possible wedding dates and necessary procedures, and manages progress.

[2444] Emotion Engine: Detects when the user is feeling stressed and provides advice on how to relax.

[2445] Device: Receive reminders for meetings and tour dates via LINE.

[2446] 3. Specific examples of asset formation

[2447] User: Makes payments using electronic payment systems on a daily basis.

[2448] Server: Aggregates spending data at the end of the month and generates a spending analysis report.

[2449] Emotion Engine: Detects when users are experiencing financial stress and provides appropriate advice and payment instalments.

[2450] Device: Report results and saving advice are sent to the user via LINE.

[2451] This system connects a server, user devices, a database, and an emotion engine to provide users with comprehensive information and support. Through a single app, users can receive support for a wide range of life events, as well as suggestions and advice tailored to their emotional state.

[2452] The processing flow will be explained below.

[2453] Specific processing steps

[2454] User registration and initial settings

[2455] Step 1:

[2456] The user adds the Assist app via LINE and opens the registration page.

[2457] Step 2:

[2458] The terminal displays a form for the user to input basic information (age, occupation, family composition, etc.).

[2459] Step 3:

[2460] The user enters basic information and presses the submit button.

[2461] Step 4:

[2462] The terminal sends the entered basic information to the server.

[2463] Step 5:

[2464] The server stores the received basic information in a database and sends a registration completion message to the user via LINE.

[2465] Event data collection and analysis

[2466] Step 1:

[2467] The user uses LINE on a daily basis to chat with the assist app.

[2468] Step 2:

[2469] The terminal appropriately collects the user's chat history and transmits it to the server.

[2470] Step 3:

[2471] The server analyzes the chat history collected using natural language processing (NLP) to predict the user's current status and future events.

[2472] Step 4:

[2473] The server prepares to provide the user with necessary information and advice based on the predicted event.

[2474] Emotion Engine Operation

[2475] Step 1:

[2476] The user types or sends a voice message via LINE.

[2477] Step 2:

[2478] The device sends user input and voice messages to the emotion engine.

[2479] Step 3:

[2480] An emotion engine analyzes the input data and identifies the user's emotional state.

[2481] Step 4:

[2482] The emotion engine transmits the identified emotion data to a server.

[2483] Step 5:

[2484] The server adjusts the suggestions and advice based on the emotional data.

[2485] Providing concrete support

[2486] Exam

[2487] Step 1:

[2488] The server analyzes the user's exam schedule and past study progress data to determine what to study today.

[2489] Step 2:

[2490] The emotion engine checks the user's motivation and suggests encouraging messages or breaks as needed.

[2491] Step 3:

[2492] The server generates study progress checks and reminders and sends them as LINE messages.

[2493] Step 4:

[2494] The device will remind the user about study apps and reference books.

[2495] find work

[2496] Step 1:

[2497] The server collects the user's work history data and retrieves job information via scraping or API.

[2498] Step 2:

[2499] The server compiles a list of job information suitable for the user and sends it via LINE.

[2500] Step 3:

[2501] The emotion engine identifies the user's stress level and provides relaxation and stress management advice.

[2502] Step 4:

[2503] The device sends the user interview schedule reminders and content related to interview preparation.

[2504] marriage

[2505] Step 1:

[2506] The server provides a wedding preparation progress management tool via LINE and organizes the necessary tasks.

[2507] Step 2:

[2508] The server collects information on wedding venues and marriage agencies and sends suggestions to the user.

[2509] Step 3:

[2510] The emotion engine checks the user's emotional state and flexibly adjusts advice and suggestions.

[2511] Step 4:

[2512] The device will send you a reminder to schedule a tour.

[2513] Childbirth and childcare

[2514] Step 1:

[2515] The server collects information about medical institutions and childcare items and provides it to users via LINE.

[2516] Step 2:

[2517] The emotion engine detects the user's anxiety and stress about child-rearing and sends support messages.

[2518] Step 3:

[2519] The device will remind you of childcare schedules and vaccination dates.

[2520] Step 4:

[2521] The server analyzes the user's questions and concerns and provides appropriate advice.

[2522] Retirement and nursing care

[2523] Step 1:

[2524] The server monitors the user's health status and periodically sends health check questionnaires.

[2525] Step 2:

[2526] An emotion engine checks the user's emotional state and provides emotional support as needed.

[2527] Step 3:

[2528] Based on the data collected by the server, nursing care services and medical institutions are suggested.

[2529] Step 4:

[2530] The device sends the user health checklists and reminders for regular checkups.

[2531] Asset formation

[2532] Step 1:

[2533] A server retrieves spending data from the electronic payment system and generates monthly reports.

[2534] Step 2:

[2535] The server analyzes spending data and sends advice on saving tips and asset formation via LINE.

[2536] Step 3:

[2537] The emotion engine identifies the user's financial stress and provides optimal advice and payment installment suggestions.

[2538] Step 4:

[2539] The terminal notifies the user of periodic asset management reminders.

[2540] PayPay integration

[2541] Step 1:

[2542] A user makes everyday payments through an electronic payment system.

[2543] Step 2:

[2544] The server periodically collects user spending data through the API of the electronic payment system.

[2545] Step 3:

[2546] The server analyzes the collected spending data to detect abnormal or excessive spending.

[2547] Step 4:

[2548] The emotion engine checks the user's emotional state and provides appropriate feedback and advice.

[2549] Step 5:

[2550] The device will notify the user of their spending status and savings suggestions via LINE.

[2551] In this way, the system performs specific, step-by-step processes, providing the support the user needs in real time. The specific actions taken at each step work together to assist the user in smoothly dealing with various life events.

[2552] Example 2

[2553] 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."

[2554] Users face challenges in receiving appropriate and timely information and advice for major life events. Furthermore, personalized support tailored to the user's emotional and financial situation is rarely provided for each event. Furthermore, there is a lack of comprehensive management of expenditure information and integrated analysis of data related to life events. To address these challenges, a comprehensive system is needed to support users' overall life events.

[2555] 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.

[2556] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data using natural language processing technology, means for making personalized suggestions to the user based on the analysis results, means for providing the suggestions to the user, means for collecting and analyzing emotional data of the user using emotion analysis technology, means for adjusting the suggestions based on the emotion analysis results, means for analyzing the user's expenditure information in cooperation with an electronic payment system, and means for providing the user with financial advice based on the analyzed expenditure information. This allows the user to receive comprehensive support for each life event through a single system, and provides personalized suggestions and advice tailored to their emotions and financial status.

[2557] "Means for acquiring basic information about the user" refers to a function for collecting basic information such as the user's age, occupation, and family composition.

[2558] "Means for saving acquired basic information in a database" refers to a function for saving basic information collected from users in a dedicated database.

[2559] "Means of collecting event-related data through communication with users" refers to a function for interactively collecting information related to a user's life events through messaging apps, etc.

[2560] "Means for analyzing collected data using natural language processing technology" refers to a function that uses natural language processing technology (e.g., text analysis algorithms) to analyze collected text data.

[2561] "Means of making personalized suggestions to users based on the analysis results" refers to a function that makes optimal suggestions to users based on insights gained from analyzed data.

[2562] The "means for providing suggestions to the user" refers to a function for notifying the user of the generated suggestions.

[2563] "Means of collecting and analyzing user emotional data using emotion analysis technology" refers to a function that uses technology to extract and analyze emotional information from user input and dialogue.

[2564] "Means for adjusting suggestions based on emotion analysis results" refers to a function for appropriately changing the suggestions and advice provided depending on the user's emotional state.

[2565] "Means for analyzing user expenditure information in cooperation with an electronic payment system" refers to a function for collecting and analyzing user expenditure data in cooperation with an electronic payment service.

[2566] "Means for providing financial advice to the user based on the analyzed expenditure information" refers to a function for providing appropriate financial advice to the user based on the analyzed expenditure data.

[2567] This invention is a system that provides comprehensive support for major events in a user's life (exams, employment, marriage, childbirth, childcare, retirement, nursing care, and asset formation). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized suggestions. The system acquires basic information about the user and makes suggestions based on that information. It collects and analyzes data related to events through communication with the user, and provides the user with the information and advice they need. It also works with electronic payment systems to manage the user's spending information and provide financial advice.

[2568] Specific examples of hardware and software used

[2569] User device: Messaging app running on a smartphone or tablet (e.g., LINE)

[2570] Server: Cloud server or local server (e.g. AWS, Google Cloud)

[2571] Database: SQL or NoSQL database (e.g. MySQL, MongoDB)

[2572] Natural language processing technology: text analysis algorithms (e.g., spaCy, NLTK)

[2573] Sentiment engine: Sentiment analysis algorithm (e.g. IBM Watson Tone Analyzer, Azure Text Analytics)

[2574] Specific examples

[2575] 1. User registration and initial settings

[2576] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.).

[2577] The terminal displays a basic information input form to the user and sends the submitted data to the server.

[2578] The server saves the submitted basic information in a database and sends a registration completion message to the user via LINE.

[2579] 2. Event data collection and analysis

[2580] Users interact with the assist app using the LINE app on a daily basis.

[2581] The terminal collects the user's interaction history and periodically transmits it to the server.

[2582] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[2583] The server generates suggestions for the user based on the analysis results.

[2584] 3. Operation of the Emotion Engine

[2585] The server collects and analyzes emotional data from user input and dialogue.

[2586] The emotion engine sends the results of the emotion analysis to the server.

[2587] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[2588] Prompt Sentence Examples

[2589] 1. Test-taking support prompts

[2590] "Generate encouraging messages when your motivation to study is low"

[2591] 2. Marriage Support Prompts

[2592] "If you're feeling stressed while planning your wedding, we'll generate advice on how to relax."

[2593] 3. Wealth Building Prompts

[2594] "Generate monthly expenditure analysis reports based on data from the electronic payment system."

[2595] The basic components of this system are a user device, a server, a database, a natural language processing tool, and an emotion engine, all working closely together. Users can receive support for a variety of life events through a single application. Emotion analysis also makes it possible to provide more personalized suggestions in real time. In this way, users can receive comprehensive and personalized assistance.

[2596] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2597] System program processing flow

[2598] Processing Steps:

[2599] Step 1:

[2600] Step 2:

[2601] Step 3:

[2602] ...

[2603] Processing step details

[2604] Step 1:

[2605] The user adds the Assist app via LINE and enters basic information (age, occupation, family composition, etc.)

[2606] Input: User's basic information data

[2607] Action: The user opens the LINE app and taps the "Assist App" button. A basic information input form is displayed. The user enters basic information such as age, occupation, and family composition, and presses the "Send" button.

[2608] Output: Basic information data entered by the user

[2609] Step 2:

[2610] The device displays a form for inputting basic information to the user and sends the submitted data to the server.

[2611] Input: Basic information entered by the user

[2612] Operation: The terminal displays a basic information input form to the user, converts the information entered by the user into a data format to be sent to the server, and sends the data to the server in the form of an HTTP request.

[2613] Output: Basic information sent to the server

[2614] Step 3:

[2615] The server saves the basic information sent to the database and sends a registration completion message to the user via LINE.

[2616] Input: Basic information received by the server

[2617] Operation: The server saves basic information to the database. After saving is complete, it generates a registration completion message and sends it to the user using the LINE API.

[2618] Output: Basic information stored in the database and a successful registration message sent to the user.

[2619] Step 4:

[2620] Users interact with the Assist App using the LINE app on a daily basis.

[2621] Input: User interaction message

[2622] How it works: A user sends a message about a daily event through the LINE app.

[2623] Output: Interactive message from the user

[2624] Step 5:

[2625] The device collects the user's interaction history and periodically sends it to the server.

[2626] Input: User interaction history

[2627] How it works: The device collects conversation history via the LINE API and uploads it to the server on a specified schedule (e.g., at a certain time every day).

[2628] Output: Dialogue history sent to the server

[2629] Step 6:

[2630] The server analyzes the dialogue history using natural language processing technology to identify the user's status and desired information.

[2631] Input: Dialogue history received by the server

[2632] How it works: The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the dialogue history and perform text tokenization, sentiment analysis, and semantic analysis to identify the user's emotional state and information needs.

[2633] Output: Analyzed user status and desired information

[2634] Step 7:

[2635] The server generates suggestions for the user based on the analysis results.

[2636] Input: Analyzed user status and desired information

[2637] How it works: The server uses the generative AI model to generate suggestions based on the analysis results. The suggestions are generated based on the prompt (e.g., "If your motivation to study is declining, generate an encouraging message").

[2638] Output: Generated proposals

[2639] Step 8:

[2640] The server provides suggestions to the user via LINE

[2641] Input: Generated proposals

[2642] How it works: The server uses the LINE API to send the generated suggestions to the user.

[2643] Output: Suggestions sent to the user

[2644] Step 9:

[2645] The server collects and analyzes emotional data from user input and dialogue.

[2646] Input: User input and interaction data

[2647] How it works: The server uses the emotion engine to analyze the user's emotional state from their input and dialogue. It uses an emotion analysis algorithm to analyze the input text and identify the user's emotional state.

[2648] Output: Parsed emotion data

[2649] Step 10:

[2650] The emotion engine sends the results of emotion analysis to the server.

[2651] Input: Parsed emotion data

[2652] How it works: The emotion engine sends the analysis results to the server, which then updates the user's emotional state based on the analysis results.

[2653] Output: Sentiment analysis results sent to the server

[2654] Step 11:

[2655] The server adjusts the suggestions based on the sentiment analysis results and provides them to the user.

[2656] Input: Sentiment analysis results

[2657] How it works: The server adjusts the generated suggestions based on the results of emotion analysis. For example, if the user is feeling stressed, it adds suggestions for relaxation methods. The adjusted suggestions are then sent to the user via LINE.

[2658] Output: Adjusted proposal and send to user

[2659] (Application example 2)

[2660] 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."

[2661] Conventional user support systems make suggestions based on the user's basic information and event data, but they have the problem of not being able to take into account the user's emotional state. As a result, they are unable to provide personalized advice that adapts to the user's emotions, making it difficult to provide effective user support. In particular, because they do not take into account emotional changes related to financial stress or life events, they are unable to provide appropriate support that meets the user's needs.

[2662] 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.

[2663] In this invention, the server includes means for acquiring basic information of a user, means for storing the acquired basic information in a database, means for collecting data related to events through communication with the user, means for analyzing the collected data and making suggestions to the user, means for providing the suggestions to the user, means for analyzing the user's expenditure information in cooperation with an electronic payment system, means for providing financial advice to the user based on the analyzed expenditure information, and means for recognizing the user's emotions and adjusting the suggestions based thereon, thereby enabling the provision of personalized suggestions and financial advice that take the user's emotional state into consideration.

[2664] "Basic user information" refers to basic data about each individual user, such as the user's age, occupation, family structure, and income.

[2665] A "database" is an electronic information system that stores acquired information and data and allows it to be searched and updated as needed.

[2666] "Communication" refers to the means by which information is exchanged between users and systems, including messaging apps and email.

[2667] "Event-related data" is information related to major events in a user's life, such as taking an exam, getting a job, getting married, giving birth, raising children, retirement, caring for elderly relatives, and building assets.

[2668] "Recommendations" refers to specific advice, plans, information, etc. provided to users based on collected and analyzed data.

[2669] An "electronic payment system" is a system that allows users to pay electronically when purchasing goods or using services, and includes credit cards and digital wallets.

[2670] "Expense information" is data relating to the flow of money involved in purchases and payments made by a user.

[2671] "Financial advice" refers to recommendations on the user's household finances, saving methods, investment strategies, etc. based on expenditure and income information.

[2672] Recognizing "emotions" means analyzing and identifying a user's emotional state from their text messages, voice, facial expressions, etc.

[2673] "Emotion analysis" is the process of using data processing techniques to recognize emotions to determine a user's emotional state and sending that information to a server.

[2674] This invention is a system that provides comprehensive support for major events in a user's life, and by combining it with an emotion engine that recognizes the user's emotions, it makes personalized suggestions and advice. Specific embodiments for implementing this invention are described below.

[2675] System Configuration

[2676] The system consists of the following components:

[2677] 1. User Device

[2678] Users access the system using their smartphones.

[2679] Enter basic information, submit data related to your event, and receive suggestions.

[2680] To communicate with the system, messaging apps such as LINE are used.

[2681] 2. Server

[2682] Receives basic information and event data and stores it in a database.

[2683] Data analysis is performed to generate optimal suggestions for users.

[2684] It works in conjunction with electronic payment systems to manage expenditure information.

[2685] It uses an emotion engine to analyze the user's emotional state and tailor suggestions and advice.

[2686] 3. Database

[2687] Stores and manages user basic information, event data, expenditure information, and emotional data.

[2688] 4. Emotion Engine

[2689] It analyzes the user's input and voice data to recognize their emotional state.

[2690] Hardware and software used

[2691] Hardware: Smartphone (iOS, Android)

[2692] software:

[2693] LINE Messaging API (sending messages, notifications)

[2694] AWS Lambda (serverless computing)

[2695] AWS RDS (database)

[2696] Amazon Rekognition (emotion engine)

[2697] NumPy, Pandas (data analysis)

[2698] TensorFlow (sentiment analysis model)

[2699] Program processing overview

[2700] 1. User registration and initial settings

[2701] The user enters basic information using the LINE app and sends it to the server. The server saves the basic information in a database and sends a registration completion message.

[2702] 2. Data collection and analysis

[2703] Users regularly send event-related data and information about their emotional state via the LINE app.

[2704] The server periodically receives this data and analyzes it using natural language processing technology. The analyzed information is then stored in a database.

[2705] 3. Spending data management and financial advice

[2706] ...

Claims

1. A means for obtaining basic information about a user; A means of storing the acquired basic information in a database; means for collecting data relating to the event through communication with the user; means for analyzing the collected data and providing recommendations to the user; a means for providing suggestions to a user; means for analyzing user spending information in conjunction with an electronic payment system; means for providing financial advice to the user based on the analyzed spending information; A system including:

2. further comprising means for providing information related to the user's life events; The system of claim 1 .

3. Further comprising means for monitoring the user's healthcare data and providing health support; The system of claim 1 .

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