System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving personal economic conditions and medical treatment information such as incomes, expenses, medical treatment contents, and medical treatment periods; means for analyzing the personal economic conditions and medical treatment information using a specific natural-language processing model and a generative AI model; means for proposing a subsidy or an insurance plan optimal for a person based on the analysis result; and means for sending the generated document to a predetermined institution and tracking a sending status.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Cancer treatment is often long-term and expensive, causing financial difficulties and anxiety for patients and their families. Furthermore, the process of gathering information and applying for subsidies and insurance is complicated and requires a lot of time and effort. This situation can delay the selection and application process for optimal subsidies and insurance, further increasing the financial burden. Therefore, there is a need for a system that proposes optimal subsidies and insurance plans based on the user's financial situation and treatment, and automates the application process to reduce the burden. [Means for solving the problem]

[0005] The present invention solves the problems by a system including: means for accepting information on an individual's financial situation and treatment, such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for proposing the optimal subsidy or insurance plan for the individual based on the analysis results; means for automatically generating documents required for application according to the proposed subsidy or insurance plan; and means for sending the generated documents to a predetermined institution and tracking the delivery status. Furthermore, the system includes means for a user to select any plan from the presented plans, automatically starting the application procedure based on the selection, and means for tracking the receipt status of documents after the application procedure in real time and notifying the user, thereby enabling efficient subsidy and insurance procedures while reducing the financial burden.

[0006] "Income" is the total amount of income an individual receives over a given period of time.

[0007] "Expenditure" is the amount of money an individual spends on consumption, purchasing services, etc. over a certain period of time.

[0008] "Treatment details" are details of specific medical services, such as medical procedures, drug therapies, and surgical procedures, that an individual receives.

[0009] A "treatment period" is the period during which an individual receives a particular medical procedure or treatment.

[0010] "Personal economic situation" refers collectively to an individual's financial condition, including income, expenses, assets, and liabilities.

[0011] A "natural language processing model" is a type of artificial intelligence designed to understand and manipulate human language.

[0012] A "generative AI model" is a type of artificial intelligence that generates optimal results or predictions from diverse input data.

[0013] "Analysis" is the process of examining input data in detail and extracting its meaning and relevance.

[0014] A "subsidy plan" refers to the form and terms of financial assistance that an individual may receive under certain conditions.

[0015] An "insurance plan" is a financial product that specifies the coverage and benefit conditions provided in exchange for a certain premium.

[0016] An "application process" is the formal procedures and paperwork required to receive a particular grant or insurance plan.

[0017] "Automatic document generation" is the process of automatically creating required documents based on pre-set templates and conditions.

[0018] "Transportation tracking" is the process of monitoring and recording in real time the progress of a document until it reaches its destination.

[0019] "Real-time tracking" is the process of monitoring an event as it occurs and obtaining information immediately. [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] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on the user's financial situation and treatment information, and automates the application process. The specific processing flow of this system is described below.

[0042] System Overview

[0043] The system is primarily comprised of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans to users through a multi-step process. The entire system operates online and utilizes advanced natural language processing and generative AI models.

[0044] Entering user information

[0045] 1. Users

[0046] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, etc. This information is entered through a web browser or application.

[0047] 2. Terminal

[0048] The device collects the information entered by the user and sends it to the server, with the data being sent using a standard format such as JSON.

[0049] Analysis of information and suggestions

[0050] 3. Server

[0051] The server receives the input data and stores it in a database. It then analyzes the collected data using specific natural language processing and generative AI models.

[0052] 4. Server

[0053] Based on the analysis results, the system generates the optimal subsidy and insurance plan for the user's financial situation and treatment information. This proposal is returned to the device from the server in JSON format.

[0054] Check and select a plan

[0055] 5. Terminal

[0056] The device displays the optimal plan received from the server on the user's screen, and a UI is provided that allows the user to select the optimal plan from multiple proposals.

[0057] 6. Users

[0058] The user selects the most suitable plan from those displayed on the screen and clicks the confirmation button.

[0059] Automatic document generation and delivery

[0060] 7. Server

[0061] The server generates the necessary application documents based on the selected plan, a process that is automated using templates.

[0062] 8. Server

[0063] The generated documents are then sent electronically to the appropriate authority (such as an insurance company or government agency) via email or an online application form.

[0064] Delivery status tracking and notification

[0065] 9. Server

[0066] The server tracks the status of submitted documents in real time and records them in a database, providing updates on the status of submission and receipt.

[0067] 10. Terminal

[0068] Users can check the delivery and receipt status in real time through their devices, and timely information is provided to users through the notification function.

[0069] Specific examples

[0070] For example, suppose a user enters information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment. This information is sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and the user selects insurance plan B. The server generates application documents based on insurance plan B and sends them to the insurance company. The server then tracks the submission and acceptance status in real time and notifies the user of the information.

[0071] In this way, the system can process grant and insurance applications quickly and efficiently, reducing the financial burden on users, allowing them to complete complex procedures with minimal effort.

[0072] The processing flow will be explained below.

[0073] Program processing flow

[0074] Entering and submitting user information

[0075] Step 1:

[0076] User:

[0077] Users log in using a web browser or application and enter details such as income, expenses, treatment details, and treatment duration.

[0078] Step 2:

[0079] Device:

[0080] The device converts the input information into JSON format and generates a request to send to the specified API endpoint.

[0081] Receiving and storing information

[0082] Step 3:

[0083] server:

[0084] The server receives the user information sent from the terminal and temporarily stores it in memory or intermediate data storage.

[0085] Analysis of information and proposal of plans

[0086] Step 4:

[0087] server:

[0088] The server passes the stored information to natural language processing models and generative AI models for analysis.

[0089] Step 5:

[0090] server:

[0091] A generative AI model generates a list of optimal subsidies and insurance plans for the user based on the analysis results.

[0092] Step 6:

[0093] server:

[0094] Sends the list of generated plans to the terminal in JSON format.

[0095] View and review your plan

[0096] Step 7:

[0097] Device:

[0098] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[0099] Step 8:

[0100] User:

[0101] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[0102] Step 9:

[0103] Device:

[0104] The device generates and sends an API request to notify the server of the user's plan selection.

[0105] Automatic document generation

[0106] Step 10:

[0107] server:

[0108] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[0109] Step 11:

[0110] server:

[0111] Save the generated document in a database or file storage and generate a preview link for the user.

[0112] Step 12:

[0113] server:

[0114] The generated preview link is sent to the user's device.

[0115] Start the application process

[0116] Step 13:

[0117] User:

[0118] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[0119] Step 14:

[0120] Device:

[0121] The terminal generates and sends an API request to notify the server of the operation to start the application.

[0122] Document delivery and tracking

[0123] Step 15:

[0124] server:

[0125] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[0126] Step 16:

[0127] server:

[0128] Delivery status is tracked in real time and recorded in a database.

[0129] Notification of delivery and receipt status

[0130] Step 17:

[0131] Device:

[0132] Users will be able to see the status of their shipments in real time through an updated dashboard.

[0133] Step 18:

[0134] server:

[0135] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[0136] Step 19:

[0137] Device:

[0138] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[0139] This process flow allows users to complete grant and insurance application procedures efficiently and with minimal effort.

[0140] Example 1

[0141] 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."

[0142] With conventional systems, selecting the most appropriate subsidy or insurance plan based on an individual's financial situation and treatment information, and then completing the application process, required a lot of time and effort. Furthermore, creating and sending the necessary application documents, as well as tracking their status, were often done manually, resulting in inefficient procedures and errors. There is a need to solve these problems and realize more efficient and accurate proposals and application processes for subsidies and insurance plans.

[0143] 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.

[0144] In this invention, the server includes means for accepting data on an individual's financial situation and medical treatment information, means for analyzing the data using a specific machine learning model and generation algorithm, means for proposing optimal subsidies and insurance plans for the individual based on the analysis results, means for automatically generating documents required for application in accordance with the proposed subsidies and insurance plans, means for sending the generated documents to a predetermined institution and tracking the sending status, and means for recording the sending results in a database and notifying the user. This enables the user to quickly and efficiently receive optimal subsidies and insurance plans and automatically complete the application process.

[0145] "Personal financial and medical information" refers to detailed information about an individual's financial situation and medical care, such as income, expenses, treatment, and duration of treatment.

[0146] A "machine learning model" refers to a collection of algorithms that learn patterns and rules from data and make predictions and classifications for new data.

[0147] A "generative algorithm" refers to a computational method for generating output in a particular format from input data.

[0148] "Subsidy or insurance plan" refers to a group of financial assistance or insurance services provided based on an individual's financial situation and treatment information.

[0149] "Documents required for application" refers to official documents required to access subsidies or insurance plans.

[0150] "Prescribed agency" refers to the official organization or body that administers and manages the subsidy or insurance plan.

[0151] "Delivery status" refers to the progress status after the generated document has been sent to the specified institution.

[0152] A "database" refers to an information collection system that stores data in an organized manner and allows it to be accessed and managed as needed.

[0153] "Notifying the user" means that the system provides information and updates to the user.

[0154] "Efficiently" refers to achieving maximum results with minimum time and resources.

[0155] As an embodiment of the present invention, a system is provided that proposes optimal subsidies and insurance plans based on an individual's financial situation and treatment information, and automates application procedures.

[0156] The system, which operates online and is primarily comprised of a server, terminals, and users, utilizes advanced natural language processing and generative AI models to propose the optimal plan to users through a multi-step process and then complete the application process.

[0157] The server performs data analysis using natural language processing models and generative AI models that utilize Python's TensorFlow library and the BERT model, etc. The terminal refers to a device that can connect to the internet, such as a PC or smartphone.

[0158] Entering user information

[0159] Users log in to the system via a web browser or application and enter information such as their income, expenses, treatment details, and treatment period. For example, they enter information such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" and click the "Submit" button.

[0160] The device takes the information entered by the user, converts it to JSON format, and sends it to the server. For example, it is converted as follows:

[0161] json

[0162] {

[0163] "Income": 300000,

[0164] "Expenditure": 200000,

[0165] "Treatment details": "Chemotherapy",

[0166] "Treatment duration": "6 months"

[0167] }

[0168] Analysis of information and suggestions

[0169] The server receives the JSON data sent from the device and stores it in a database, which can be structured as an SQL table like this:

[0170] sql

[0171] CREATE TABLE user information (

[0172] id INT AUTO_INCREMENT PRIMARY KEY,

[0173] Income INT,

[0174] Expenditure INT,

[0175] Treatment details VARCHAR(255),

[0176] Treatment period VARCHAR(255)

[0177] );

[0178] The stored data is analyzed using natural language processing and generative AI models. Based on the analysis results, the optimal subsidy or insurance plan is generated. Examples of prompts for the generative AI model include:

[0179] text

[0180] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[0181] Check and select a plan

[0182] The device displays the proposals received from the server on the user's screen. For example, a UI is provided that allows users to compare multiple plans, such as "Subsidy Plan A" and "Insurance Plan B."

[0183] The user selects the most suitable plan from the plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[0184] Automatic document generation and delivery

[0185] The server automatically generates application documents according to the plan selected by the user. This process is done using a template engine (e.g., Jinja2) to embed user information in templates. The generated documents are then sent electronically to the designated institution. This process can be done, for example, by email using the SMTP protocol or by using the auto-fill function of an online application form.

[0186] Delivery status tracking and notification

[0187] The server tracks the status of submitted documents in real time and records progress information in a database. Users can check the status of submission and receipt via their devices. Status information displayed on the dashboard keeps users up to date with the latest situation. A notification function also provides users with real-time updates.

[0188] The system allows users to quickly and efficiently find the most suitable subsidy or insurance plan and automatically complete the application process.

[0189] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0190] Step 1: Enter your user information

[0191] Users log in to the system through a web browser or application and enter personal information such as income, expenses, treatment details, and treatment period. For example, they enter details such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" into the form and click the "Submit" button.

[0192] Input: Data on income, expenses, treatment details, and treatment duration

[0193] Output: Personal information entered (form data)

[0194] Specifically, for example, data is sent by entering numbers or text into an application input form and pressing the "Send" button.

[0195] Step 2: Collect and send data

[0196] The device takes the information entered by the user and converts it into JSON format, for example, the following data format:

[0197] json

[0198] {

[0199] "Income": 300000,

[0200] "Expenditure": 200000,

[0201] "Treatment details": "Chemotherapy",

[0202] "Treatment duration": "6 months"

[0203] }

[0204] The converted data is sent to the server.

[0205] Input: Personal information entered by the user (form data)

[0206] Output: JSON format data

[0207] Specifically, the terminal analyzes the form data, generates a data object in JSON format, and sends it to the server via an HTTP request.

[0208] Step 3: Receiving and storing data

[0209] The server receives the JSON data sent from the device and stores it in a database, for example using the following SQL table structure:

[0210] sql

[0211] CREATE TABLE user information (

[0212] id INT AUTO_INCREMENT PRIMARY KEY,

[0213] Income INT,

[0214] Expenditure INT,

[0215] Treatment details VARCHAR(255),

[0216] Treatment period VARCHAR(255)

[0217] );

[0218] Input: JSON data sent from the terminal

[0219] Output: Personal information stored in the database

[0220] Specifically, the server receives the HTTP request, parses the JSON data, executes an SQL insert query, and saves it in the database.

[0221] Step 4: Analyze the data

[0222] The server analyzes the stored data using a natural language processing model (e.g., BERT) and a generative AI model (e.g., TensorFlow). An example of a prompt for the generative AI model is as follows:

[0223] text

[0224] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[0225] Input: Personal information retrieved from the database

[0226] Output: Subsidy and insurance plan proposals as analysis results

[0227] Specifically, the server retrieves information from the database, inputs that data into the generative AI model as prompt sentences, and calculates and proposes the optimal plan.

[0228] Step 5: Submit and view your proposal

[0229] The device receives the analysis results (optimal plan proposals) from the server and displays them on the user's screen. For example, it presents multiple options such as "Subsidy Plan A" and "Insurance Plan B."

[0230] Input: Proposal results sent from the server (JSON format)

[0231] Output: Plan proposal displayed on user screen

[0232] Specifically, the device receives JSON data from the server, analyzes the data, and reflects it on the UI.

[0233] Step 6: Choose a plan

[0234] The user selects the most suitable plan from the multiple plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[0235] Input: Multiple plan proposals

[0236] Output: The plan selected by the user

[0237] Specifically, the user clicks a button to select from the presented options.

[0238] Step 7: Auto-generate documents

[0239] The server automatically generates application documents based on the plan selected by the user. This process uses a template engine (e.g., Jinja2) and embeds user information into the template.

[0240] Input: User selected plan, user information

[0241] Output: Generated application documents

[0242] Specifically, the server inputs the user's selection information and personal information into a template engine to generate the necessary documents.

[0243] Step 8: Send your documents

[0244] The server then sends the generated documents to the appropriate authorities electronically, using email via the SMTP protocol and auto-filling of online application forms.

[0245] Input: Generated application documents

[0246] Output: Documents sent to the designated institution

[0247] Specifically, the server sends emails or API requests to deliver documents to the necessary institutions.

[0248] Step 9: Track your shipment

[0249] The server tracks the status of submitted documents in real time and records the information in a database.

[0250] Input: Status information after sending documents

[0251] Output: Delivery status recorded in the database

[0252] Specifically, the server obtains status information from a predetermined organization and stores it in a database.

[0253] Step 10: Notify users

[0254] Users can check the status of their shipments and receipts through their devices. For example, the following status information is displayed on the dashboard:

[0255] html

[0256]

[0257] <h3> Insurance Plan B Application Status< / h3>

[0258] Delivery completed: 2023-04-01

[0259] Waiting for acceptance

[0260]

[0261] Input: Database status information

[0262] Output: Status information displayed on the user's screen

[0263] Specifically, the device retrieves status information from a database and notifies the user in real time.

[0264] (Application example 1)

[0265] 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."

[0266] Existing food delivery services do not offer optimal meal plans or discount plans that take into account the user's financial situation or health information, forcing users to make complex choices. Furthermore, the ordering process is cumbersome and there is a lack of ways to track delivery status in real time. Therefore, it is necessary to improve user convenience and efficiency.

[0267] 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.

[0268] In this invention, the server includes means for accepting personal financial and health information such as income, expenses, health information, and dietary restriction information, means for analyzing the information using a specific natural language processing model and a generative AI model, means for proposing optimal meal plans and discount plans for the individual based on the analysis results, means for automatically generating an order based on the proposed meal plans and discount plans, and means for sending the generated order to a predetermined institution and tracking the delivery status. This allows users to easily select the meal plan or discount plan that is optimal for their financial and health situations, and automates the process from ordering to tracking delivery.

[0269] "Income" is the money or economic benefits that an individual receives over a period of time.

[0270] "Expenses" are the money or financial burden that an individual spends over a certain period of time.

[0271] "Health information" refers to health-related data such as an individual's dietary restrictions, food allergies, and health goals.

[0272] "Dietary restriction information" is information about foods that an individual should avoid for specific reasons (such as allergies, religion, or health goals).

[0273] "Personal economic situation" refers to general data related to an individual's economic activities, such as income and expenditure.

[0274] A "natural language processing model" is an algorithm or method that allows a computer to analyze and understand human language.

[0275] A "generative AI model" is an artificial intelligence model that generates optimal output from input data.

[0276] A "meal plan" is a meal plan proposed taking into account an individual's financial situation and health information.

[0277] A "discount plan" is a method of offering discounts that can be applied to meal orders.

[0278] "Means for automatically generating orders" refers to a system or process that automatically generates order content based on a proposed plan.

[0279] A "prescribed institution" is an organization or business that receives and fulfills orders, such as a restaurant or food delivery service.

[0280] "Shipping Tracking Measures" means systems and methods for monitoring and managing the shipping and delivery progress of an order.

[0281] "User" refers to an individual who uses the System to select and order a meal plan or discount plan.

[0282] As an embodiment of the present invention, we provide a system that proposes optimal meal plans and discount plans based on a user's financial situation and health information, and automates the ordering process. This system is composed of a server, terminals, and users, and proposes meal plans and discount plans and executes the ordering process through a multi-stage process. The specific details of this system are described below.

[0283] Entering user information

[0284] Users log in to the service using their smartphones and enter data such as their income, expenses, dietary restrictions, and health goals. This information is sent from the device to the server in JSON format.

[0285] Analysis of information and suggestions

[0286] The server stores the received data in a database and analyzes it using specific natural language processing and generative AI models. Based on the analysis results, it generates meal plans and discount plans that are optimal for the user's financial situation and health information. These proposals are also returned from the server to the device in JSON format.

[0287] Check and select a plan

[0288] The device displays the optimal plan received from the server on the user's screen, and the user can use the UI to select the appropriate one from multiple proposals. Once a selection is made, the information is sent to the server.

[0289] Automatic order generation and dispatch

[0290] The server automatically generates an order based on the selected plan. This process is automated using templates. The generated order is then electronically sent to the partner restaurant or food delivery service, where it is confirmed.

[0291] Delivery tracking and notifications

[0292] The server tracks the order status in real time and records it in a database. Delivery status updates are immediately sent to the user, who can then view the delivery progress in real time via their device.

[0293] Specific examples

[0294] For example, suppose a user inputs their income of ¥300,000, expenses of ¥200,000, requests a vegetarian meal plan, and a goal of 2,000 calories per day. This information is sent to the server and analyzed by the generative AI model. The optimal meal plan A and discount plan B are suggested, and the user selects meal plan A. The server then generates an order based on the suggestions and sends it to the partner restaurant.

[0295] Prompt Sentence Examples

[0296] An example of a prompt sentence to be input to the generative AI model is as follows:

[0297] Suppose a user has an income of ¥300,000, expenses of ¥200,000, is a vegetarian, and is aiming for 2,000 calories per day. What meal plan would you suggest?

[0298] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0299] Step 1:

[0300] Entering user information

[0301] A user logs into the service using a smartphone and enters data such as their income, expenses, dietary restrictions, and health goals. This data is encoded in JSON format and sent from the device to the server. Examples of input data include income of 300,000 yen, expenses of 200,000 yen, being a vegetarian, and 2,000 calories per day. The device collects this data and prepares it for further processing.

[0302] Step 2:

[0303] Receiving and storing information on the server side

[0304] The server receives the JSON data sent from the device and stores it in a database. At this point, the server checks the data for consistency and cleans it if necessary. The data received includes income, expenses, dietary restrictions, and health goals. The consistency check includes checking for missing fields and data format.

[0305] Step 3:

[0306] Analysis using natural language processing and AI models

[0307] The server inputs the stored data into a natural language processing model and a generative AI model for analysis. Data processing involves standardizing numerical data such as income and expenses, and vectorizing text data such as dietary restrictions and health goals. Based on this, optimal meal plans and discount plans are generated for the user. An example of a prompt input to the generative AI model is, "Please suggest a meal plan for the user whose income is 300,000 yen, expenses are 200,000 yen, and the user is a vegetarian, aiming for 2,000 calories per day."

[0308] Step 4:

[0309] Generate and return a plan

[0310] Based on the analysis results, the server creates optimal meal plans and discount plans and returns them to the device in JSON format, including plan details, price information, calorie information, etc. Specifically, meal plan A (price 3,000 yen, 2,000 calories) and discount plan B (10% discount coupon) are generated.

[0311] Step 5:

[0312] Check and select a plan

[0313] The device displays the plan information received from the server to the user. The user can select the most suitable plan from multiple proposals on the screen. For example, if the user selects meal plan A, that information is sent from the device to the server. The device reflects this information in the UI, which is designed to be easy for the user to use.

[0314] Step 6:

[0315] Automatic order generation and dispatch

[0316] The server automatically generates an order based on the selected plan and electronically transmits it to the partner restaurant or food delivery service. In this process, the order information is formatted based on a template. Specifically, an order based on meal plan A is generated and transmitted to the partner restaurant.

[0317] Step 7:

[0318] Delivery tracking and notifications

[0319] The server tracks the delivery status of the generated order in real time and records it in a database. Status updates are instantly sent to the user, who can view the progress via their device. Delivery information is displayed as a status such as "on delivery" or "received."

[0320] Through this multi-step process, the system suggests a meal plan that suits the user's financial and health situation, and then automatically generates an order and tracks the delivery status.

[0321] 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.

[0322] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on a user's financial situation and treatment information, automates the application process, and recognizes the user's emotions and adjusts the proposals and support content based on those emotions.

[0323] System Overview

[0324] The system is mainly composed of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans for users through a multi-step process. It also uses an emotion engine to recognize users' emotions and optimize the process accordingly.

[0325] Entering and submitting user information

[0326] 1. Users

[0327] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, and also input their emotional state or have it automatically detected through facial recognition and voice analysis.

[0328] 2. Terminal

[0329] The terminal collects the economic information and emotional data entered by the user, converts it into JSON format, and sends it to the server.

[0330] Receiving and storing information

[0331] 3. Server

[0332] The server receives the user information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[0333] Analyzing information and emotions and proposing plans

[0334] 4. Server

[0335] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[0336] 5. Server

[0337] Based on the generated analysis results and sentiment evaluation results, a list of the most suitable subsidy and insurance plans for the user is generated. Based on the results of the sentiment engine, the priority of the proposed plans is adjusted.

[0338] 6. Server

[0339] Sends the list of generated plans to the terminal in JSON format.

[0340] View and review your plan

[0341] 7. Terminal

[0342] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[0343] 8. Users

[0344] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[0345] 9. Terminal

[0346] The device generates and sends an API request to notify the server of the user's plan selection.

[0347] Automatic document generation

[0348] 10. Server

[0349] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[0350] 11. Server

[0351] Save the generated document in a database or file storage and generate a preview link for the user.

[0352] 12. Server

[0353] The generated preview link is sent to the user's device.

[0354] Start the application process

[0355] 13. Users

[0356] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[0357] 14. Terminal

[0358] The terminal generates and sends an API request to notify the server of the operation to start the application.

[0359] Document delivery and tracking

[0360] 15. Server

[0361] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[0362] 16. Server

[0363] Delivery status is tracked in real time and recorded in a database.

[0364] Notification of delivery and receipt status

[0365] 17. Terminal

[0366] Users will be able to see the status of their shipments in real time through an updated dashboard.

[0367] 18. Server

[0368] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[0369] 19. Terminal

[0370] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[0371] Specific examples

[0372] For example, suppose a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user's stress level is high. This information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and special assistance plan C is also added depending on the user's stress level. The user selects insurance plan B, and the server generates application documents based on this and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[0373] In this way, the system can provide optimal assistance quickly and efficiently, taking into account the user's emotional state, while reducing the user's financial burden. This process allows users to complete complex procedures with minimal effort and also provides psychological support.

[0374] The processing flow will be explained below.

[0375] Program processing flow

[0376] Entering user information and emotion data

[0377] Step 1:

[0378] User:

[0379] Users log in via a web browser or application and enter detailed information such as income, expenses, treatment details, and treatment duration. In addition, the user's emotional state can be entered or automatically detected using facial recognition and voice analysis.

[0380] Step 2:

[0381] Device:

[0382] The device converts the input economic information and sentiment data into JSON format and generates a request to send to the specified API endpoint.

[0383] Receiving and storing information

[0384] Step 3:

[0385] server:

[0386] The server receives the user's economic information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[0387] Analyzing information and emotions and generating plans

[0388] Step 4:

[0389] server:

[0390] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[0391] Step 5:

[0392] server:

[0393] Based on the analysis results and sentiment evaluation results, a list of subsidies and insurance plans that are best suited to the user is generated. The results of the sentiment engine are used to adjust the priority of the proposed plans.

[0394] Step 6:

[0395] server:

[0396] The list of generated plans is sent to the terminal in JSON format.

[0397] View and review your plan

[0398] Step 7:

[0399] Device:

[0400] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[0401] Step 8:

[0402] User:

[0403] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[0404] Step 9:

[0405] Device:

[0406] The device generates and sends an API request to notify the server of the user's plan selection.

[0407] Automatic document generation

[0408] Step 10:

[0409] server:

[0410] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[0411] Step 11:

[0412] server:

[0413] Save the generated document in a database or file storage and generate a preview link for the user.

[0414] Step 12:

[0415] server:

[0416] The generated preview link is sent to the user's device.

[0417] Start the application process

[0418] Step 13:

[0419] User:

[0420] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[0421] Step 14:

[0422] Device:

[0423] The terminal generates and sends an API request to notify the server of the operation to start the application.

[0424] Document delivery and tracking

[0425] Step 15:

[0426] server:

[0427] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[0428] Step 16:

[0429] server:

[0430] Delivery status is tracked in real time and recorded in a database.

[0431] Notification of delivery and receipt status

[0432] Step 17:

[0433] Device:

[0434] Users will be able to see the status of their shipments in real time through an updated dashboard.

[0435] Step 18:

[0436] server:

[0437] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[0438] Step 19:

[0439] Device:

[0440] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[0441] Specific examples

[0442] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user also has a high stress level, this information and emotion data will be sent to the server.

[0443] Information and emotion data analysis

[0444] The server performs analysis using a generative AI model and generates the optimal subsidy plan A and insurance plan B. The emotion engine evaluates the stress level as high and also suggests special support plan C.

[0445] Select a plan and generate documents

[0446] The user checks the plans on the terminal and selects insurance plan B. The server automatically generates application documents based on that and sends them to the insurance company.

[0447] Track delivery and receipt status

[0448] The server tracks the delivery status of the generated document in real time and notifies the user of that information. The server also tracks the receipt status and notifies the user.

[0449] In this way, the system can reduce the user's financial burden and provide optimal assistance quickly and efficiently, taking into account their emotional state. This process allows users to complete complex procedures with minimal effort and also receive psychological support.

[0450] Example 2

[0451] 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."

[0452] In modern society, it is extremely complicated for individuals to select and apply for the most suitable subsidy or insurance plan. Furthermore, there is no system that provides optimal recommendations that take into account each individual's emotional state. Therefore, an effective system is needed to reduce the individual's financial burden and psychological stress at the same time.

[0453] 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.

[0454] In this invention, the server includes: means for receiving personal financial situation and treatment information such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for detecting the user's emotional state and evaluating it based on the analysis results; means for proposing optimal subsidies and insurance plans for the individual based on the analysis results and emotional evaluation results; means for automatically generating documents required for application according to the proposed subsidies and insurance plans; and means for sending the generated documents to a predetermined institution and tracking the delivery status. This enables individuals to complete complex procedures with minimal effort and also receive psychological support by receiving optimal suggestions based on their emotional state.

[0455] "Income" refers to the money or assets that an individual receives over a period of time.

[0456] "Expenditure" refers to the money or assets an individual uses for consumption or obligations over a period of time.

[0457] "Treatment content" refers to the medical procedures and treatment methods an individual receives, including details thereof.

[0458] "Treatment period" refers to the period during which a particular medical procedure or treatment method is performed.

[0459] "Personal economic situation" refers to information that comprehensively represents an individual's financial situation, such as income, expenses, assets, and loans.

[0460] "Treatment information" refers to detailed information about medical treatment an individual receives, including the content and duration of treatment.

[0461] A "natural language processing model" refers to an algorithm or program designed to analyze and understand the meaning of natural language text.

[0462] A "generative AI model" refers to an algorithm or program that uses machine learning techniques to analyze data and generate new information or suggestions.

[0463] "Emotional state" refers to an individual's psychological state, including stress level and type of emotion.

[0464] A "grant" is financial support provided by a government or institution for a specific purpose or under specific conditions.

[0465] "Insurance Plan" means a plan that includes a set of services or coverages offered by an insurance company.

[0466] "Application" refers to the official documentation required to apply for a grant or insurance plan.

[0467] "Authorized institutions" refer to official organizations, such as government agencies or insurance companies, that accept applications for grants or insurance.

[0468] "Delivery status" refers to the process and status of application documents from the time they are sent to the designated institution until they are accepted.

[0469] As an embodiment of the present invention, a system comprising a server, a terminal, and a user is provided. A specific implementation method will be described below.

[0470] The system begins with the user entering personal financial and medical information, such as income, expenses, treatment details, and treatment duration. The user enters this information through a dedicated terminal application. The user's emotional state can also be entered manually or automatically detected using a facial recognition camera or voice analysis.

[0471] The terminal collects the economic and sentiment data entered by the user and converts this information into JSON format, which is then sent to the server using the HTTPS protocol.

[0472] The server receives the user information and emotion data sent from the device and temporarily stores it in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[0473] The stored data is passed to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis. This analysis deciphers the user's medical information and financial situation and identifies appropriate subsidies and insurance plans. At the same time, emotion data is passed to an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[0474] The server combines the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user, which is then sent to the device in JSON format.

[0475] The device displays the list of plans received from the server to the user and provides an interface for the user to select. The user selects the most suitable plan from the displayed plans and clicks the confirmation button. The device generates and sends an API request to notify the server of the selection.

[0476] The server automatically generates the documents required for application based on the plan selected by the user. A template engine (e.g., Handlebars.js) is used to generate the documents, embedding the user's required information. The generated documents are saved in a database (e.g., PostgreSQL) or file storage (e.g., Amazon S3).

[0477] After the document is generated, the server sends a preview link to the user. The user checks this preview link and, if there are no problems, clicks the "Start application" button. This operation causes the device to generate an API request to start the application and send it to the server.

[0478] The server routes the documents to the appropriate authority (insurance company, government agency). The delivery status is tracked in real time and recorded in a database. The delivery status and receipt status are checked periodically, and the latest information is updated on the user's dashboard.

[0479] The above processing flow builds a system that provides optimal support based on the user's emotional state while reducing the user's financial burden.

[0480] Specific examples

[0481] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy, and the emotion engine detects a high stress level, the information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A, insurance plan B, and special needs plan C are then proposed. The user selects insurance plan B, and the server generates application documents based on that and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[0482] Prompt Sentence Examples

[0483] My income is 300,000 yen, my expenses are 200,000 yen, I'm undergoing chemotherapy treatment for 6 months, and my stress level is high. Please suggest the best subsidy and insurance plan.

[0484] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0485] Step 1:

[0486] Users log in to the system and enter information such as their income, expenses, treatment details, and treatment duration, as well as their emotional state, which can be entered manually or automatically detected through facial recognition cameras and voice analysis.

[0487] Input: User's income, expenses, treatment details, treatment duration, emotional state

[0488] Output: Collected personal information and emotional data

[0489] Step 2:

[0490] The terminal receives the economic and emotional data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[0491] Input: User's financial information and emotional data

[0492] Output: Data converted to JSON format

[0493] Step 3:

[0494] The server receives the user information and emotion data sent from the device and temporarily stores them in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[0495] Input: User information and emotion data in JSON format

[0496] Output: Data stored in the database

[0497] Step 4:

[0498] The server passes the stored data to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis, and inputs emotional data into an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[0499] Input: User information and emotion data stored in the database

[0500] Output: Analysis results and emotion evaluation results

[0501] Step 5:

[0502] The server integrates the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user. It also adjusts the priority of the plans based on the evaluation results of the emotion engine.

[0503] Input: Analysis results and emotion evaluation results

[0504] Output: List of best subsidies and insurance plans

[0505] Step 6:

[0506] The server sends the list of generated plans to the terminal in JSON format.

[0507] Input: List of best subsidies and insurance plans

[0508] Output: Plan list in JSON format

[0509] Step 7:

[0510] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[0511] Input: Plan list in JSON format

[0512] Output: User selectable Show Plan interface

[0513] Step 8:

[0514] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[0515] Input: Show Plan interface

[0516] Output: User's plan selection

[0517] Step 9:

[0518] The device generates and sends an API request to notify the server of the user's plan selection.

[0519] Input: User's plan selection

[0520] Output: API request

[0521] Step 10:

[0522] The server automatically generates the necessary application documents based on the selected plan. It uses a template engine (e.g., Handlebars.js) to create the application documents by embedding the necessary user information.

[0523] Input: User's plan selection

[0524] Output: Auto-generated application documents

[0525] Step 11:

[0526] The server stores the generated document in a database or file storage and generates a preview link for the user.

[0527] Input: Auto-generated application documents

[0528] Output: Preview link

[0529] Step 12:

[0530] The server sends the generated preview link to the user's terminal.

[0531] Input: Preview link

[0532] Output: Preview link sent to your device

[0533] Step 13:

[0534] The user clicks on the preview link sent to check the documents, and if there are no problems, clicks the "Start application" button.

[0535] Input: Preview link

[0536] Output: Application start operation

[0537] Step 14:

[0538] The terminal generates and sends an API request to notify the server of the operation to start the application.

[0539] Input: Start application operation

[0540] Output: API request

[0541] Step 15:

[0542] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[0543] Input: API request and application documents

[0544] Output: Documents sent

[0545] Step 16:

[0546] The server tracks the document delivery status in real time and records it in a database.

[0547] Input: Documents sent

[0548] Output: Record of document delivery status in database

[0549] Step 17:

[0550] The device provides a dashboard so users can check delivery status in real time.

[0551] Input: Document delivery status data

[0552] Output: Real-time updated dashboard

[0553] Step 18:

[0554] The server periodically checks the acceptance status of the application documents, obtains the latest acceptance status, and records it in the database.

[0555] Input: Application acceptance status

[0556] Output: Record of acceptance status in database

[0557] Step 19:

[0558] The terminal reflects the latest acceptance status provided by the server on the dashboard and provides a notification to the user.

[0559] Input: Acceptance status data

[0560] Output: Updated dashboard and notification to the user

[0561] (Application example 2)

[0562] 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."

[0563] Existing subsidy and insurance plan recommendation systems suggest optimal plans based on the user's financial information, but do not take into account the user's emotional state, resulting in a lack of appropriate support under stressful circumstances. Furthermore, there is a risk that users may send incorrect information during times of high stress, leading to problems with insufficient financial burden reduction and psychological support.

[0564] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for accepting an individual's financial situation and treatment information, such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for proposing the optimal subsidy or insurance plan for the individual based on the analysis results; means for automatically generating documents required for application according to the proposed subsidy or insurance plan; means for sending the generated documents to a specified institution and tracking the delivery status; means for proposing and implementing optimal security measures based on the user's financial situation and emotional state; and means for recognizing the user's emotional state in real time and adjusting the proposed content. This makes it possible to provide appropriate support that takes into account the user's emotional state, while simultaneously implementing security measures such as preventing erroneous transmissions during times of high stress.

[0565] "Income" is the total amount of money, or value that can be converted into money, that an individual receives over a given period of time.

[0566] "Expenditure" is the total amount of money an individual uses for living and business purposes.

[0567] "Treatment content" refers to details such as the specific treatment procedures and methods used at medical institutions, as well as the medicines and equipment used.

[0568] "Treatment period" refers to the entire period required to receive a given treatment.

[0569] "Personal financial situation" refers to a person's financial stability and health based on income, expenses, assets, liabilities, etc.

[0570] A "natural language processing model" is a model that uses algorithms and techniques to enable computers to understand and analyze human language.

[0571] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to automatically generate new information or suggestions from data.

[0572] A "grant" is financial assistance provided by governments or other organizations to individuals or organizations that meet certain criteria.

[0573] "Insurance plan" refers to the types and terms of a contract offered by an insurance company to provide coverage against certain risks.

[0574] "Automatic document generation" is the process of using templates and predefined data to automatically fill in the necessary information and create a document in a predetermined format.

[0575] "Emotional state" refers to an individual's current feelings or mental state.

[0576] "Security measures" is a general term for measures and actions taken to protect individuals and systems from various risks and threats.

[0577] "Real time" refers to the ability to process and display ongoing situations and events instantly, with minimal delay.

[0578] To implement this invention, a system is required that proposes optimal subsidies, insurance plans, and security measures based on the user's financial situation and emotional state, and automates the application process. The system is primarily composed of a server, terminals, and users, and provides optimal support to users through a multi-stage process.

[0579] Hardware and software used

[0580] Hardware

[0581] Smart glasses: Equipped with a face recognition camera, voice recognition microphone, high-performance processor, and Wi-Fi module

[0582] Server: High-performance computer system

[0583] software

[0584] AWS Lambda: Used for serverless computation to process economic and sentiment data of users.

[0585] Amazon S3: For temporary data storage.

[0586] Amazon Rekognition: A facial recognition engine for emotion recognition.

[0587] Google Dialogflow: A natural language processing engine for interacting with users.

[0588] JSON format: Used for sending and receiving data.

[0589] System Operation

[0590] 1. Collection and Input

[0591] Users use the smart glasses to input their income, expenses, treatment details, and treatment duration, and the glasses also use a facial recognition camera and voice recognition microphone to recognize and collect data on the user's emotional state in real time.

[0592] 2. Data transmission

[0593] The collected data is converted into JSON format and sent to a server, which receives the data and temporarily stores it in Amazon S3.

[0594] 3. Data Analysis

[0595] Amazon Rekognition is used to analyze the collected sentiment data, and AWS Lambda then sends the analyzed economic and sentiment information to Google Dialogflow, which analyzes and generates optimal subsidies, insurance plans, and security measures.

[0596] 4. Proposing plans and measures

[0597] Based on the analysis results, the system will propose optimal plans and measures to the user, which will be sent to the user via smart glasses and can be viewed in real time.

[0598] 5. Real-time notification and action

[0599] Once the user selects a proposed plan or measure, the smart glasses transmit the selection to the server, which then automatically generates the appropriate application documents and sends them to the designated authority. The server also implements specific security measures (e.g., suspending transmissions) depending on the user's stress level.

[0600] Specific examples

[0601] For example, if a user enters information such as income of ¥300,000, expenses of ¥200,000, and six months of chemotherapy treatment, and the emotion engine detects high stress levels, the following prompt will be generated:

[0602] "Given your recent emotional state, we recommend temporarily suspending transmissions to avoid sending erroneous information during high stress situations. Would you like to cease transmissions?"

[0603] In this way, the system can quickly and efficiently provide optimal assistance that takes into account the user's emotional state, while reducing the user's financial burden.

[0604] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0605] Step 1:

[0606] The user uses the smart glasses to input their income, expenses, treatment details, and treatment duration. The smart glasses' facial recognition camera and voice recognition microphone detect and collect the user's emotional state in real time. Specifically, the user enters financial information (income, expenses, etc.), treatment information, as well as facial and voice data. This data is necessary for use in subsequent analysis steps.

[0607] Step 2:

[0608] The device (smart glasses) converts the collected economic information and emotion data into JSON format and sends it to the cloud server. This operation formats the raw data and converts it into a format that is easy for the server to receive.

[0609] Step 3:

[0610] The server temporarily stores the user information and emotion data sent from the device in JSON format in Amazon S3, making the data easily accessible for subsequent processing steps.

[0611] Step 4:

[0612] The server analyzes the stored data using AWS Lambda. First, it inputs the facial recognition data into Amazon Rekognition to perform a detailed analysis of the user's emotional state. This outputs the user's stress level and emotional state as numerical data.

[0613] Step 5:

[0614] AWS Lambda analyzes the economic information and sentiment data and sends it to Google Dialogflow, which uses natural language processing to generate optimal subsidies, insurance plans, and security measures. This results in a list of generated subsidy plans, insurance plans, and security measures.

[0615] Step 6:

[0616] The server uses a generative AI model to generate a list of optimal subsidies and insurance plans for each user based on the analysis and sentiment evaluation results, and adjusts priorities based on sentiment data. The generated results are then converted into JSON format.

[0617] Step 7:

[0618] The server sends the generated plan list in JSON format to the device. The device (smart glasses) visualizes and displays the plan list received from the server to the user. The user can select the most appropriate plan from the multiple plans presented.

[0619] Step 8:

[0620] Based on the plan selected by the user, the device will send an API request back to the server, which will receive the selection and automatically execute the steps to start the application process.

[0621] Step 9:

[0622] The server automatically generates the necessary application documents based on the selected plan. This process uses templates to generate documents with the user's information embedded. The server then sends the automatically generated documents to the designated institution via email or an online application form.

[0623] Step 10:

[0624] The server tracks the delivery status in real time and records the progress in a database, which is then periodically updated on the user's device.

[0625] Step 11:

[0626] Users can check the delivery status in real time using the smart glasses. In addition, the server periodically checks whether the application has been accepted and notifies the device of the latest status.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] [Second embodiment]

[0631] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0632] 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.

[0633] 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).

[0634] 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.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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."

[0643] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on the user's financial situation and treatment information, and automates the application process. The specific processing flow of this system is described below.

[0644] System Overview

[0645] The system is primarily comprised of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans to users through a multi-step process. The entire system operates online and utilizes advanced natural language processing and generative AI models.

[0646] Entering user information

[0647] 1. Users

[0648] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, etc. This information is entered through a web browser or application.

[0649] 2. Terminal

[0650] The device collects the information entered by the user and sends it to the server, with the data being sent using a standard format such as JSON.

[0651] Analysis of information and suggestions

[0652] 3. Server

[0653] The server receives the input data and stores it in a database. It then analyzes the collected data using specific natural language processing and generative AI models.

[0654] 4. Server

[0655] Based on the analysis results, the system generates the optimal subsidy and insurance plan for the user's financial situation and treatment information. This proposal is returned to the device from the server in JSON format.

[0656] Check and select a plan

[0657] 5. Terminal

[0658] The device displays the optimal plan received from the server on the user's screen, and a UI is provided that allows the user to select the optimal plan from multiple proposals.

[0659] 6. Users

[0660] The user selects the most suitable plan from those displayed on the screen and clicks the confirmation button.

[0661] Automatic document generation and delivery

[0662] 7. Server

[0663] The server generates the necessary application documents based on the selected plan, a process that is automated using templates.

[0664] 8. Server

[0665] The generated documents are then sent electronically to the appropriate authority (such as an insurance company or government agency) via email or an online application form.

[0666] Delivery status tracking and notification

[0667] 9. Server

[0668] The server tracks the status of submitted documents in real time and records them in a database, providing updates on the status of submission and receipt.

[0669] 10. Terminal

[0670] Users can check the delivery and receipt status in real time through their devices, and timely information is provided to users through the notification function.

[0671] Specific examples

[0672] For example, suppose a user enters information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment. This information is sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and the user selects insurance plan B. The server generates application documents based on insurance plan B and sends them to the insurance company. The server then tracks the submission and acceptance status in real time and notifies the user of the information.

[0673] In this way, the system can process grant and insurance applications quickly and efficiently, reducing the financial burden on users, allowing them to complete complex procedures with minimal effort.

[0674] The processing flow will be explained below.

[0675] Program processing flow

[0676] Entering and submitting user information

[0677] Step 1:

[0678] User:

[0679] Users log in using a web browser or application and enter details such as income, expenses, treatment details, and treatment duration.

[0680] Step 2:

[0681] Device:

[0682] The device converts the input information into JSON format and generates a request to send to the specified API endpoint.

[0683] Receiving and storing information

[0684] Step 3:

[0685] server:

[0686] The server receives the user information sent from the terminal and temporarily stores it in memory or intermediate data storage.

[0687] Analysis of information and proposal of plans

[0688] Step 4:

[0689] server:

[0690] The server passes the stored information to natural language processing models and generative AI models for analysis.

[0691] Step 5:

[0692] server:

[0693] A generative AI model generates a list of optimal subsidies and insurance plans for the user based on the analysis results.

[0694] Step 6:

[0695] server:

[0696] Sends the list of generated plans to the terminal in JSON format.

[0697] View and review your plan

[0698] Step 7:

[0699] Device:

[0700] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[0701] Step 8:

[0702] User:

[0703] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[0704] Step 9:

[0705] Device:

[0706] The device generates and sends an API request to notify the server of the user's plan selection.

[0707] Automatic document generation

[0708] Step 10:

[0709] server:

[0710] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[0711] Step 11:

[0712] server:

[0713] Save the generated document in a database or file storage and generate a preview link for the user.

[0714] Step 12:

[0715] server:

[0716] The generated preview link is sent to the user's device.

[0717] Start the application process

[0718] Step 13:

[0719] User:

[0720] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[0721] Step 14:

[0722] Device:

[0723] The terminal generates and sends an API request to notify the server of the operation to start the application.

[0724] Document delivery and tracking

[0725] Step 15:

[0726] server:

[0727] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[0728] Step 16:

[0729] server:

[0730] Delivery status is tracked in real time and recorded in a database.

[0731] Notification of delivery and receipt status

[0732] Step 17:

[0733] Device:

[0734] Users will be able to see the status of their shipments in real time through an updated dashboard.

[0735] Step 18:

[0736] server:

[0737] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[0738] Step 19:

[0739] Device:

[0740] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[0741] This process flow allows users to complete grant and insurance application procedures efficiently and with minimal effort.

[0742] Example 1

[0743] 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."

[0744] With conventional systems, selecting the most appropriate subsidy or insurance plan based on an individual's financial situation and treatment information, and then completing the application process, required a lot of time and effort. Furthermore, creating and sending the necessary application documents, as well as tracking their status, were often done manually, resulting in inefficient procedures and errors. There is a need to solve these problems and realize more efficient and accurate proposals and application processes for subsidies and insurance plans.

[0745] 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.

[0746] In this invention, the server includes means for accepting data on an individual's financial situation and medical treatment information, means for analyzing the data using a specific machine learning model and generation algorithm, means for proposing optimal subsidies and insurance plans for the individual based on the analysis results, means for automatically generating documents required for application in accordance with the proposed subsidies and insurance plans, means for sending the generated documents to a predetermined institution and tracking the sending status, and means for recording the sending results in a database and notifying the user. This enables the user to quickly and efficiently receive optimal subsidies and insurance plans and automatically complete the application process.

[0747] "Personal financial and medical information" refers to detailed information about an individual's financial situation and medical care, such as income, expenses, treatment, and duration of treatment.

[0748] A "machine learning model" refers to a collection of algorithms that learn patterns and rules from data and make predictions and classifications for new data.

[0749] A "generative algorithm" refers to a computational method for generating output in a particular format from input data.

[0750] "Subsidy or insurance plan" refers to a group of financial assistance or insurance services provided based on an individual's financial situation and treatment information.

[0751] "Documents required for application" refers to official documents required to access subsidies or insurance plans.

[0752] "Prescribed agency" refers to the official organization or body that administers and manages the subsidy or insurance plan.

[0753] "Delivery status" refers to the progress status after the generated document has been sent to the specified institution.

[0754] A "database" refers to an information collection system that stores data in an organized manner and allows it to be accessed and managed as needed.

[0755] "Notifying the user" means that the system provides information and updates to the user.

[0756] "Efficiently" refers to achieving maximum results with minimum time and resources.

[0757] As an embodiment of the present invention, a system is provided that proposes optimal subsidies and insurance plans based on an individual's financial situation and treatment information, and automates application procedures.

[0758] The system, which operates online and is primarily comprised of a server, terminals, and users, utilizes advanced natural language processing and generative AI models to propose the optimal plan to users through a multi-step process and then complete the application process.

[0759] The server performs data analysis using natural language processing models and generative AI models that utilize Python's TensorFlow library and the BERT model, etc. The terminal refers to a device that can connect to the internet, such as a PC or smartphone.

[0760] Entering user information

[0761] Users log in to the system via a web browser or application and enter information such as their income, expenses, treatment details, and treatment period. For example, they enter information such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" and click the "Submit" button.

[0762] The device takes the information entered by the user, converts it to JSON format, and sends it to the server. For example, it is converted as follows:

[0763] json

[0764] {

[0765] "Income": 300000,

[0766] "Expenditure": 200000,

[0767] "Treatment details": "Chemotherapy",

[0768] "Treatment duration": "6 months"

[0769] }

[0770] Analysis of information and suggestions

[0771] The server receives the JSON data sent from the device and stores it in a database, which can be structured as an SQL table like this:

[0772] sql

[0773] CREATE TABLE user information (

[0774] id INT AUTO_INCREMENT PRIMARY KEY,

[0775] Income INT,

[0776] Expenditure INT,

[0777] Treatment details VARCHAR(255),

[0778] Treatment period VARCHAR(255)

[0779] );

[0780] The stored data is analyzed using natural language processing and generative AI models. Based on the analysis results, the optimal subsidy or insurance plan is generated. Examples of prompts for the generative AI model include:

[0781] text

[0782] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[0783] Check and select a plan

[0784] The device displays the proposals received from the server on the user's screen. For example, a UI is provided that allows users to compare multiple plans, such as "Subsidy Plan A" and "Insurance Plan B."

[0785] The user selects the most suitable plan from the plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[0786] Automatic document generation and delivery

[0787] The server automatically generates application documents according to the plan selected by the user. This process is done using a template engine (e.g., Jinja2) to embed user information in templates. The generated documents are then sent electronically to the designated institution. This process can be done, for example, by email using the SMTP protocol or by using the auto-fill function of an online application form.

[0788] Delivery status tracking and notification

[0789] The server tracks the status of submitted documents in real time and records progress information in a database. Users can check the status of submission and receipt via their devices. Status information displayed on the dashboard keeps users up to date with the latest situation. A notification function also provides users with real-time updates.

[0790] The system allows users to quickly and efficiently find the most suitable subsidy or insurance plan and automatically complete the application process.

[0791] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0792] Step 1: Enter your user information

[0793] Users log in to the system through a web browser or application and enter personal information such as income, expenses, treatment details, and treatment period. For example, they enter details such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" into the form and click the "Submit" button.

[0794] Input: Data on income, expenses, treatment details, and treatment duration

[0795] Output: Personal information entered (form data)

[0796] Specifically, for example, data is sent by entering numbers or text into an application input form and pressing the "Send" button.

[0797] Step 2: Collect and send data

[0798] The device takes the information entered by the user and converts it into JSON format, for example, the following data format:

[0799] json

[0800] {

[0801] "Income": 300000,

[0802] "Expenditure": 200000,

[0803] "Treatment details": "Chemotherapy",

[0804] "Treatment duration": "6 months"

[0805] }

[0806] The converted data is sent to the server.

[0807] Input: Personal information entered by the user (form data)

[0808] Output: JSON format data

[0809] Specifically, the terminal analyzes the form data, generates a data object in JSON format, and sends it to the server via an HTTP request.

[0810] Step 3: Receiving and storing data

[0811] The server receives the JSON data sent from the device and stores it in a database, for example using the following SQL table structure:

[0812] sql

[0813] CREATE TABLE user information (

[0814] id INT AUTO_INCREMENT PRIMARY KEY,

[0815] Income INT,

[0816] Expenditure INT,

[0817] Treatment details VARCHAR(255),

[0818] Treatment period VARCHAR(255)

[0819] );

[0820] Input: JSON data sent from the terminal

[0821] Output: Personal information stored in the database

[0822] Specifically, the server receives the HTTP request, parses the JSON data, executes an SQL insert query, and saves it in the database.

[0823] Step 4: Analyze the data

[0824] The server analyzes the stored data using a natural language processing model (e.g., BERT) and a generative AI model (e.g., TensorFlow). An example of a prompt for the generative AI model is as follows:

[0825] text

[0826] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[0827] Input: Personal information retrieved from the database

[0828] Output: Subsidy and insurance plan proposals as analysis results

[0829] Specifically, the server retrieves information from the database, inputs that data into the generative AI model as prompt sentences, and calculates and proposes the optimal plan.

[0830] Step 5: Submit and view your proposal

[0831] The device receives the analysis results (optimal plan proposals) from the server and displays them on the user's screen. For example, it presents multiple options such as "Subsidy Plan A" and "Insurance Plan B."

[0832] Input: Proposal results sent from the server (JSON format)

[0833] Output: Plan proposal displayed on user screen

[0834] Specifically, the device receives JSON data from the server, analyzes the data, and reflects it on the UI.

[0835] Step 6: Choose a plan

[0836] The user selects the most suitable plan from the multiple plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[0837] Input: Multiple plan proposals

[0838] Output: The plan selected by the user

[0839] Specifically, the user clicks a button to select from the presented options.

[0840] Step 7: Auto-generate documents

[0841] The server automatically generates application documents based on the plan selected by the user. This process uses a template engine (e.g., Jinja2) and embeds user information into the template.

[0842] Input: User selected plan, user information

[0843] Output: Generated application documents

[0844] Specifically, the server inputs the user's selection information and personal information into a template engine to generate the necessary documents.

[0845] Step 8: Send your documents

[0846] The server then sends the generated documents to the appropriate authorities electronically, using email via the SMTP protocol and auto-filling of online application forms.

[0847] Input: Generated application documents

[0848] Output: Documents sent to the designated institution

[0849] Specifically, the server sends emails or API requests to deliver documents to the necessary institutions.

[0850] Step 9: Track your shipment

[0851] The server tracks the status of submitted documents in real time and records the information in a database.

[0852] Input: Status information after sending documents

[0853] Output: Delivery status recorded in the database

[0854] Specifically, the server obtains status information from a predetermined organization and stores it in a database.

[0855] Step 10: Notify users

[0856] Users can check the status of their shipments and receipts through their devices. For example, the following status information is displayed on the dashboard:

[0857] html

[0858]

[0859] <h3> Insurance Plan B Application Status< / h3>

[0860] Delivery completed: 2023-04-01

[0861] Waiting for acceptance

[0862]

[0863] Input: Database status information

[0864] Output: Status information displayed on the user's screen

[0865] Specifically, the device retrieves status information from a database and notifies the user in real time.

[0866] (Application example 1)

[0867] 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."

[0868] Existing food delivery services do not offer optimal meal plans or discount plans that take into account the user's financial situation or health information, forcing users to make complex choices. Furthermore, the ordering process is cumbersome and there is a lack of ways to track delivery status in real time. Therefore, it is necessary to improve user convenience and efficiency.

[0869] 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.

[0870] In this invention, the server includes means for accepting personal financial and health information such as income, expenses, health information, and dietary restriction information, means for analyzing the information using a specific natural language processing model and a generative AI model, means for proposing optimal meal plans and discount plans for the individual based on the analysis results, means for automatically generating an order based on the proposed meal plans and discount plans, and means for sending the generated order to a predetermined institution and tracking the delivery status. This allows users to easily select the meal plan or discount plan that is optimal for their financial and health situations, and automates the process from ordering to tracking delivery.

[0871] "Income" is the money or economic benefits that an individual receives over a period of time.

[0872] "Expenses" are the money or financial burden that an individual spends over a certain period of time.

[0873] "Health information" refers to health-related data such as an individual's dietary restrictions, food allergies, and health goals.

[0874] "Dietary restriction information" is information about foods that an individual should avoid for specific reasons (such as allergies, religion, or health goals).

[0875] "Personal economic situation" refers to general data related to an individual's economic activities, such as income and expenditure.

[0876] A "natural language processing model" is an algorithm or method that allows a computer to analyze and understand human language.

[0877] A "generative AI model" is an artificial intelligence model that generates optimal output from input data.

[0878] A "meal plan" is a meal plan proposed taking into account an individual's financial situation and health information.

[0879] A "discount plan" is a method of offering discounts that can be applied to meal orders.

[0880] "Means for automatically generating orders" refers to a system or process that automatically generates order content based on a proposed plan.

[0881] A "prescribed institution" is an organization or business that receives and fulfills orders, such as a restaurant or food delivery service.

[0882] "Shipping Tracking Measures" means systems and methods for monitoring and managing the shipping and delivery progress of an order.

[0883] "User" refers to an individual who uses the System to select and order a meal plan or discount plan.

[0884] As an embodiment of the present invention, we provide a system that proposes optimal meal plans and discount plans based on a user's financial situation and health information, and automates the ordering process. This system is composed of a server, terminals, and users, and proposes meal plans and discount plans and executes the ordering process through a multi-stage process. The specific details of this system are described below.

[0885] Entering user information

[0886] Users log in to the service using their smartphones and enter data such as their income, expenses, dietary restrictions, and health goals. This information is sent from the device to the server in JSON format.

[0887] Analysis of information and suggestions

[0888] The server stores the received data in a database and analyzes it using specific natural language processing and generative AI models. Based on the analysis results, it generates meal plans and discount plans that are optimal for the user's financial situation and health information. These proposals are also returned from the server to the device in JSON format.

[0889] Check and select a plan

[0890] The device displays the optimal plan received from the server on the user's screen, and the user can use the UI to select the appropriate one from multiple proposals. Once a selection is made, the information is sent to the server.

[0891] Automatic order generation and dispatch

[0892] The server automatically generates an order based on the selected plan. This process is automated using templates. The generated order is then electronically sent to the partner restaurant or food delivery service, where it is confirmed.

[0893] Delivery tracking and notifications

[0894] The server tracks the order status in real time and records it in a database. Delivery status updates are immediately sent to the user, who can then view the delivery progress in real time via their device.

[0895] Specific examples

[0896] For example, suppose a user inputs their income of ¥300,000, expenses of ¥200,000, requests a vegetarian meal plan, and a goal of 2,000 calories per day. This information is sent to the server and analyzed by the generative AI model. The optimal meal plan A and discount plan B are suggested, and the user selects meal plan A. The server then generates an order based on the suggestions and sends it to the partner restaurant.

[0897] Prompt Sentence Examples

[0898] An example of a prompt sentence to be input to the generative AI model is as follows:

[0899] Suppose a user has an income of ¥300,000, expenses of ¥200,000, is a vegetarian, and is aiming for 2,000 calories per day. What meal plan would you suggest?

[0900] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0901] Step 1:

[0902] Entering user information

[0903] A user logs into the service using a smartphone and enters data such as their income, expenses, dietary restrictions, and health goals. This data is encoded in JSON format and sent from the device to the server. Examples of input data include income of 300,000 yen, expenses of 200,000 yen, being a vegetarian, and 2,000 calories per day. The device collects this data and prepares it for further processing.

[0904] Step 2:

[0905] Receiving and storing information on the server side

[0906] The server receives the JSON data sent from the device and stores it in a database. At this point, the server checks the data for consistency and cleans it if necessary. The data received includes income, expenses, dietary restrictions, and health goals. The consistency check includes checking for missing fields and data format.

[0907] Step 3:

[0908] Analysis using natural language processing and AI models

[0909] The server inputs the stored data into a natural language processing model and a generative AI model for analysis. Data processing involves standardizing numerical data such as income and expenses, and vectorizing text data such as dietary restrictions and health goals. Based on this, optimal meal plans and discount plans are generated for the user. An example of a prompt input to the generative AI model is, "Please suggest a meal plan for the user whose income is 300,000 yen, expenses are 200,000 yen, and the user is a vegetarian, aiming for 2,000 calories per day."

[0910] Step 4:

[0911] Generate and return a plan

[0912] Based on the analysis results, the server creates optimal meal plans and discount plans and returns them to the device in JSON format, including plan details, price information, calorie information, etc. Specifically, meal plan A (price 3,000 yen, 2,000 calories) and discount plan B (10% discount coupon) are generated.

[0913] Step 5:

[0914] Check and select a plan

[0915] The device displays the plan information received from the server to the user. The user can select the most suitable plan from multiple proposals on the screen. For example, if the user selects meal plan A, that information is sent from the device to the server. The device reflects this information in the UI, which is designed to be easy for the user to use.

[0916] Step 6:

[0917] Automatic order generation and dispatch

[0918] The server automatically generates an order based on the selected plan and electronically transmits it to the partner restaurant or food delivery service. In this process, the order information is formatted based on a template. Specifically, an order based on meal plan A is generated and transmitted to the partner restaurant.

[0919] Step 7:

[0920] Delivery tracking and notifications

[0921] The server tracks the delivery status of the generated order in real time and records it in a database. Status updates are instantly sent to the user, who can view the progress via their device. Delivery information is displayed as a status such as "on delivery" or "received."

[0922] Through this multi-step process, the system suggests a meal plan that suits the user's financial and health situation, and then automatically generates an order and tracks the delivery status.

[0923] 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.

[0924] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on a user's financial situation and treatment information, automates the application process, and recognizes the user's emotions and adjusts the proposals and support content based on those emotions.

[0925] System Overview

[0926] The system is mainly composed of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans for users through a multi-step process. It also uses an emotion engine to recognize users' emotions and optimize the process accordingly.

[0927] Entering and submitting user information

[0928] 1. Users

[0929] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, and also input their emotional state or have it automatically detected through facial recognition and voice analysis.

[0930] 2. Terminal

[0931] The terminal collects the economic information and emotional data entered by the user, converts it into JSON format, and sends it to the server.

[0932] Receiving and storing information

[0933] 3. Server

[0934] The server receives the user information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[0935] Analyzing information and emotions and proposing plans

[0936] 4. Server

[0937] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[0938] 5. Server

[0939] Based on the generated analysis results and sentiment evaluation results, a list of the most suitable subsidy and insurance plans for the user is generated. Based on the results of the sentiment engine, the priority of the proposed plans is adjusted.

[0940] 6. Server

[0941] Sends the list of generated plans to the terminal in JSON format.

[0942] View and review your plan

[0943] 7. Terminal

[0944] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[0945] 8. Users

[0946] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[0947] 9. Terminal

[0948] The device generates and sends an API request to notify the server of the user's plan selection.

[0949] Automatic document generation

[0950] 10. Server

[0951] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[0952] 11. Server

[0953] Save the generated document in a database or file storage and generate a preview link for the user.

[0954] 12. Server

[0955] The generated preview link is sent to the user's device.

[0956] Start the application process

[0957] 13. Users

[0958] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[0959] 14. Terminal

[0960] The terminal generates and sends an API request to notify the server of the operation to start the application.

[0961] Document delivery and tracking

[0962] 15. Server

[0963] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[0964] 16. Server

[0965] Delivery status is tracked in real time and recorded in a database.

[0966] Notification of delivery and receipt status

[0967] 17. Terminal

[0968] Users will be able to see the status of their shipments in real time through an updated dashboard.

[0969] 18. Server

[0970] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[0971] 19. Terminal

[0972] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[0973] Specific examples

[0974] For example, suppose a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user's stress level is high. This information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and special assistance plan C is also added depending on the user's stress level. The user selects insurance plan B, and the server generates application documents based on this and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[0975] In this way, the system can provide optimal assistance quickly and efficiently, taking into account the user's emotional state, while reducing the user's financial burden. This process allows users to complete complex procedures with minimal effort and also provides psychological support.

[0976] The processing flow will be explained below.

[0977] Program processing flow

[0978] Entering user information and emotion data

[0979] Step 1:

[0980] User:

[0981] Users log in via a web browser or application and enter detailed information such as income, expenses, treatment details, and treatment duration. In addition, the user's emotional state can be entered or automatically detected using facial recognition and voice analysis.

[0982] Step 2:

[0983] Device:

[0984] The device converts the input economic information and sentiment data into JSON format and generates a request to send to the specified API endpoint.

[0985] Receiving and storing information

[0986] Step 3:

[0987] server:

[0988] The server receives the user's economic information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[0989] Analyzing information and emotions and generating plans

[0990] Step 4:

[0991] server:

[0992] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[0993] Step 5:

[0994] server:

[0995] Based on the analysis results and sentiment evaluation results, a list of subsidies and insurance plans that are best suited to the user is generated. The results of the sentiment engine are used to adjust the priority of the proposed plans.

[0996] Step 6:

[0997] server:

[0998] The list of generated plans is sent to the terminal in JSON format.

[0999] View and review your plan

[1000] Step 7:

[1001] Device:

[1002] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[1003] Step 8:

[1004] User:

[1005] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[1006] Step 9:

[1007] Device:

[1008] The device generates and sends an API request to notify the server of the user's plan selection.

[1009] Automatic document generation

[1010] Step 10:

[1011] server:

[1012] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[1013] Step 11:

[1014] server:

[1015] Save the generated document in a database or file storage and generate a preview link for the user.

[1016] Step 12:

[1017] server:

[1018] The generated preview link is sent to the user's device.

[1019] Start the application process

[1020] Step 13:

[1021] User:

[1022] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[1023] Step 14:

[1024] Device:

[1025] The terminal generates and sends an API request to notify the server of the operation to start the application.

[1026] Document delivery and tracking

[1027] Step 15:

[1028] server:

[1029] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[1030] Step 16:

[1031] server:

[1032] Delivery status is tracked in real time and recorded in a database.

[1033] Notification of delivery and receipt status

[1034] Step 17:

[1035] Device:

[1036] Users will be able to see the status of their shipments in real time through an updated dashboard.

[1037] Step 18:

[1038] server:

[1039] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[1040] Step 19:

[1041] Device:

[1042] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[1043] Specific examples

[1044] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user also has a high stress level, this information and emotion data will be sent to the server.

[1045] Information and emotion data analysis

[1046] The server performs analysis using a generative AI model and generates the optimal subsidy plan A and insurance plan B. The emotion engine evaluates the stress level as high and also suggests special support plan C.

[1047] Select a plan and generate documents

[1048] The user checks the plans on the terminal and selects insurance plan B. The server automatically generates application documents based on that and sends them to the insurance company.

[1049] Track delivery and receipt status

[1050] The server tracks the delivery status of the generated document in real time and notifies the user of that information. The server also tracks the receipt status and notifies the user.

[1051] In this way, the system can reduce the user's financial burden and provide optimal assistance quickly and efficiently, taking into account their emotional state. This process allows users to complete complex procedures with minimal effort and also receive psychological support.

[1052] Example 2

[1053] 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."

[1054] In modern society, it is extremely complicated for individuals to select and apply for the most suitable subsidy or insurance plan. Furthermore, there is no system that provides optimal recommendations that take into account each individual's emotional state. Therefore, an effective system is needed to reduce the individual's financial burden and psychological stress at the same time.

[1055] 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.

[1056] In this invention, the server includes: means for receiving personal financial situation and treatment information such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for detecting the user's emotional state and evaluating it based on the analysis results; means for proposing optimal subsidies and insurance plans for the individual based on the analysis results and emotional evaluation results; means for automatically generating documents required for application according to the proposed subsidies and insurance plans; and means for sending the generated documents to a predetermined institution and tracking the delivery status. This enables individuals to complete complex procedures with minimal effort and also receive psychological support by receiving optimal suggestions based on their emotional state.

[1057] "Income" refers to the money or assets that an individual receives over a period of time.

[1058] "Expenditure" refers to the money or assets an individual uses for consumption or obligations over a period of time.

[1059] "Treatment content" refers to the medical procedures and treatment methods an individual receives, including details thereof.

[1060] "Treatment period" refers to the period during which a particular medical procedure or treatment method is performed.

[1061] "Personal economic situation" refers to information that comprehensively represents an individual's financial situation, such as income, expenses, assets, and loans.

[1062] "Treatment information" refers to detailed information about medical treatment an individual receives, including the content and duration of treatment.

[1063] A "natural language processing model" refers to an algorithm or program designed to analyze and understand the meaning of natural language text.

[1064] A "generative AI model" refers to an algorithm or program that uses machine learning techniques to analyze data and generate new information or suggestions.

[1065] "Emotional state" refers to an individual's psychological state, including stress level and type of emotion.

[1066] A "grant" is financial support provided by a government or institution for a specific purpose or under specific conditions.

[1067] "Insurance Plan" means a plan that includes a set of services or coverages offered by an insurance company.

[1068] "Application" refers to the official documentation required to apply for a grant or insurance plan.

[1069] "Authorized institutions" refer to official organizations, such as government agencies or insurance companies, that accept applications for grants or insurance.

[1070] "Delivery status" refers to the process and status of application documents from the time they are sent to the designated institution until they are accepted.

[1071] As an embodiment of the present invention, a system comprising a server, a terminal, and a user is provided. A specific implementation method will be described below.

[1072] The system begins with the user entering personal financial and medical information, such as income, expenses, treatment details, and treatment duration. The user enters this information through a dedicated terminal application. The user's emotional state can also be entered manually or automatically detected using a facial recognition camera or voice analysis.

[1073] The terminal collects the economic and sentiment data entered by the user and converts this information into JSON format, which is then sent to the server using the HTTPS protocol.

[1074] The server receives the user information and emotion data sent from the device and temporarily stores it in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[1075] The stored data is passed to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis. This analysis deciphers the user's medical information and financial situation and identifies appropriate subsidies and insurance plans. At the same time, emotion data is passed to an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[1076] The server combines the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user, which is then sent to the device in JSON format.

[1077] The device displays the list of plans received from the server to the user and provides an interface for the user to select. The user selects the most suitable plan from the displayed plans and clicks the confirmation button. The device generates and sends an API request to notify the server of the selection.

[1078] The server automatically generates the documents required for application based on the plan selected by the user. A template engine (e.g., Handlebars.js) is used to generate the documents, embedding the user's required information. The generated documents are saved in a database (e.g., PostgreSQL) or file storage (e.g., Amazon S3).

[1079] After the document is generated, the server sends a preview link to the user. The user checks this preview link and, if there are no problems, clicks the "Start application" button. This operation causes the device to generate an API request to start the application and send it to the server.

[1080] The server routes the documents to the appropriate authority (insurance company, government agency). The delivery status is tracked in real time and recorded in a database. The delivery status and receipt status are checked periodically, and the latest information is updated on the user's dashboard.

[1081] The above processing flow builds a system that provides optimal support based on the user's emotional state while reducing the user's financial burden.

[1082] Specific examples

[1083] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy, and the emotion engine detects a high stress level, the information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A, insurance plan B, and special needs plan C are then proposed. The user selects insurance plan B, and the server generates application documents based on that and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[1084] Prompt Sentence Examples

[1085] My income is 300,000 yen, my expenses are 200,000 yen, I'm undergoing chemotherapy treatment for 6 months, and my stress level is high. Please suggest the best subsidy and insurance plan.

[1086] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1087] Step 1:

[1088] Users log in to the system and enter information such as their income, expenses, treatment details, and treatment duration, as well as their emotional state, which can be entered manually or automatically detected through facial recognition cameras and voice analysis.

[1089] Input: User's income, expenses, treatment details, treatment duration, emotional state

[1090] Output: Collected personal information and emotional data

[1091] Step 2:

[1092] The terminal receives the economic and emotional data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[1093] Input: User's financial information and emotional data

[1094] Output: Data converted to JSON format

[1095] Step 3:

[1096] The server receives the user information and emotion data sent from the device and temporarily stores them in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[1097] Input: User information and emotion data in JSON format

[1098] Output: Data stored in the database

[1099] Step 4:

[1100] The server passes the stored data to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis, and inputs emotional data into an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[1101] Input: User information and emotion data stored in the database

[1102] Output: Analysis results and emotion evaluation results

[1103] Step 5:

[1104] The server integrates the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user. It also adjusts the priority of the plans based on the evaluation results of the emotion engine.

[1105] Input: Analysis results and emotion evaluation results

[1106] Output: List of best subsidies and insurance plans

[1107] Step 6:

[1108] The server sends the list of generated plans to the terminal in JSON format.

[1109] Input: List of best subsidies and insurance plans

[1110] Output: Plan list in JSON format

[1111] Step 7:

[1112] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[1113] Input: Plan list in JSON format

[1114] Output: User selectable Show Plan interface

[1115] Step 8:

[1116] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[1117] Input: Show Plan interface

[1118] Output: User's plan selection

[1119] Step 9:

[1120] The device generates and sends an API request to notify the server of the user's plan selection.

[1121] Input: User's plan selection

[1122] Output: API request

[1123] Step 10:

[1124] The server automatically generates the necessary application documents based on the selected plan. It uses a template engine (e.g., Handlebars.js) to create the application documents by embedding the necessary user information.

[1125] Input: User's plan selection

[1126] Output: Auto-generated application documents

[1127] Step 11:

[1128] The server stores the generated document in a database or file storage and generates a preview link for the user.

[1129] Input: Auto-generated application documents

[1130] Output: Preview link

[1131] Step 12:

[1132] The server sends the generated preview link to the user's terminal.

[1133] Input: Preview link

[1134] Output: Preview link sent to your device

[1135] Step 13:

[1136] The user clicks on the preview link sent to check the documents, and if there are no problems, clicks the "Start application" button.

[1137] Input: Preview link

[1138] Output: Application start operation

[1139] Step 14:

[1140] The terminal generates and sends an API request to notify the server of the operation to start the application.

[1141] Input: Start application operation

[1142] Output: API request

[1143] Step 15:

[1144] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[1145] Input: API request and application documents

[1146] Output: Documents sent

[1147] Step 16:

[1148] The server tracks the document delivery status in real time and records it in a database.

[1149] Input: Documents sent

[1150] Output: Record of document delivery status in database

[1151] Step 17:

[1152] The device provides a dashboard so users can check delivery status in real time.

[1153] Input: Document delivery status data

[1154] Output: Real-time updated dashboard

[1155] Step 18:

[1156] The server periodically checks the acceptance status of the application documents, obtains the latest acceptance status, and records it in the database.

[1157] Input: Application acceptance status

[1158] Output: Record of acceptance status in database

[1159] Step 19:

[1160] The terminal reflects the latest acceptance status provided by the server on the dashboard and provides a notification to the user.

[1161] Input: Acceptance status data

[1162] Output: Updated dashboard and notification to the user

[1163] (Application example 2)

[1164] 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."

[1165] Existing subsidy and insurance plan recommendation systems suggest optimal plans based on the user's financial information, but do not take into account the user's emotional state, resulting in a lack of appropriate support under stressful circumstances. Furthermore, there is a risk that users may send incorrect information during times of high stress, leading to problems with insufficient financial burden reduction and psychological support.

[1166] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for accepting an individual's financial situation and treatment information, such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for proposing the optimal subsidy or insurance plan for the individual based on the analysis results; means for automatically generating documents required for application according to the proposed subsidy or insurance plan; means for sending the generated documents to a specified institution and tracking the delivery status; means for proposing and implementing optimal security measures based on the user's financial situation and emotional state; and means for recognizing the user's emotional state in real time and adjusting the proposed content. This makes it possible to provide appropriate support that takes into account the user's emotional state, while simultaneously implementing security measures such as preventing erroneous transmissions during times of high stress.

[1167] "Income" is the total amount of money, or value that can be converted into money, that an individual receives over a given period of time.

[1168] "Expenditure" is the total amount of money an individual uses for living and business purposes.

[1169] "Treatment content" refers to details such as the specific treatment procedures and methods used at medical institutions, as well as the medicines and equipment used.

[1170] "Treatment period" refers to the entire period required to receive a given treatment.

[1171] "Personal financial situation" refers to a person's financial stability and health based on income, expenses, assets, liabilities, etc.

[1172] A "natural language processing model" is a model that uses algorithms and techniques to enable computers to understand and analyze human language.

[1173] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to automatically generate new information or suggestions from data.

[1174] A "grant" is financial assistance provided by governments or other organizations to individuals or organizations that meet certain criteria.

[1175] "Insurance plan" refers to the types and terms of a contract offered by an insurance company to provide coverage against certain risks.

[1176] "Automatic document generation" is the process of using templates and predefined data to automatically fill in the necessary information and create a document in a predetermined format.

[1177] "Emotional state" refers to an individual's current feelings or mental state.

[1178] "Security measures" is a general term for measures and actions taken to protect individuals and systems from various risks and threats.

[1179] "Real time" refers to the ability to process and display ongoing situations and events instantly, with minimal delay.

[1180] To implement this invention, a system is required that proposes optimal subsidies, insurance plans, and security measures based on the user's financial situation and emotional state, and automates the application process. The system is primarily composed of a server, terminals, and users, and provides optimal support to users through a multi-stage process.

[1181] Hardware and software used

[1182] Hardware

[1183] Smart glasses: Equipped with a face recognition camera, voice recognition microphone, high-performance processor, and Wi-Fi module

[1184] Server: High-performance computer system

[1185] software

[1186] AWS Lambda: Used for serverless computation to process economic and sentiment data of users.

[1187] Amazon S3: For temporary data storage.

[1188] Amazon Rekognition: A facial recognition engine for emotion recognition.

[1189] Google Dialogflow: A natural language processing engine for interacting with users.

[1190] JSON format: Used for sending and receiving data.

[1191] System Operation

[1192] 1. Collection and Input

[1193] Users use the smart glasses to input their income, expenses, treatment details, and treatment duration, and the glasses also use a facial recognition camera and voice recognition microphone to recognize and collect data on the user's emotional state in real time.

[1194] 2. Data transmission

[1195] The collected data is converted into JSON format and sent to a server, which receives the data and temporarily stores it in Amazon S3.

[1196] 3. Data Analysis

[1197] Amazon Rekognition is used to analyze the collected sentiment data, and AWS Lambda then sends the analyzed economic and sentiment information to Google Dialogflow, which analyzes and generates optimal subsidies, insurance plans, and security measures.

[1198] 4. Proposing plans and measures

[1199] Based on the analysis results, the system will propose optimal plans and measures to the user, which will be sent to the user via smart glasses and can be viewed in real time.

[1200] 5. Real-time notification and action

[1201] Once the user selects a proposed plan or measure, the smart glasses transmit the selection to the server, which then automatically generates the appropriate application documents and sends them to the designated authority. The server also implements specific security measures (e.g., suspending transmissions) depending on the user's stress level.

[1202] Specific examples

[1203] For example, if a user enters information such as income of ¥300,000, expenses of ¥200,000, and six months of chemotherapy treatment, and the emotion engine detects high stress levels, the following prompt will be generated:

[1204] "Given your recent emotional state, we recommend temporarily suspending transmissions to avoid sending erroneous information during high stress situations. Would you like to cease transmissions?"

[1205] In this way, the system can quickly and efficiently provide optimal assistance that takes into account the user's emotional state, while reducing the user's financial burden.

[1206] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1207] Step 1:

[1208] The user uses the smart glasses to input their income, expenses, treatment details, and treatment duration. The smart glasses' facial recognition camera and voice recognition microphone detect and collect the user's emotional state in real time. Specifically, the user enters financial information (income, expenses, etc.), treatment information, as well as facial and voice data. This data is necessary for use in subsequent analysis steps.

[1209] Step 2:

[1210] The device (smart glasses) converts the collected economic information and emotion data into JSON format and sends it to the cloud server. This operation formats the raw data and converts it into a format that is easy for the server to receive.

[1211] Step 3:

[1212] The server temporarily stores the user information and emotion data sent from the device in JSON format in Amazon S3, making the data easily accessible for subsequent processing steps.

[1213] Step 4:

[1214] The server analyzes the stored data using AWS Lambda. First, it inputs the facial recognition data into Amazon Rekognition to perform a detailed analysis of the user's emotional state. This outputs the user's stress level and emotional state as numerical data.

[1215] Step 5:

[1216] AWS Lambda analyzes the economic information and sentiment data and sends it to Google Dialogflow, which uses natural language processing to generate optimal subsidies, insurance plans, and security measures. This results in a list of generated subsidy plans, insurance plans, and security measures.

[1217] Step 6:

[1218] The server uses a generative AI model to generate a list of optimal subsidies and insurance plans for each user based on the analysis and sentiment evaluation results, and adjusts priorities based on sentiment data. The generated results are then converted into JSON format.

[1219] Step 7:

[1220] The server sends the generated plan list in JSON format to the device. The device (smart glasses) visualizes and displays the plan list received from the server to the user. The user can select the most appropriate plan from the multiple plans presented.

[1221] Step 8:

[1222] Based on the plan selected by the user, the device will send an API request back to the server, which will receive the selection and automatically execute the steps to start the application process.

[1223] Step 9:

[1224] The server automatically generates the necessary application documents based on the selected plan. This process uses templates to generate documents with the user's information embedded. The server then sends the automatically generated documents to the designated institution via email or an online application form.

[1225] Step 10:

[1226] The server tracks the delivery status in real time and records the progress in a database, which is then periodically updated on the user's device.

[1227] Step 11:

[1228] Users can check the delivery status in real time using the smart glasses. In addition, the server periodically checks whether the application has been accepted and notifies the device of the latest status.

[1229] 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.

[1230] 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.

[1231] 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.

[1232] [Third embodiment]

[1233] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1234] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1235] 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).

[1236] 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.

[1237] 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.

[1238] 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).

[1239] 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.

[1240] 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.

[1241] 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.

[1242] 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.

[1243] 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.

[1244] 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."

[1245] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on the user's financial situation and treatment information, and automates the application process. The specific processing flow of this system is described below.

[1246] System Overview

[1247] The system is primarily comprised of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans to users through a multi-step process. The entire system operates online and utilizes advanced natural language processing and generative AI models.

[1248] Entering user information

[1249] 1. Users

[1250] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, etc. This information is entered through a web browser or application.

[1251] 2. Terminal

[1252] The device collects the information entered by the user and sends it to the server, with the data being sent using a standard format such as JSON.

[1253] Analysis of information and suggestions

[1254] 3. Server

[1255] The server receives the input data and stores it in a database. It then analyzes the collected data using specific natural language processing and generative AI models.

[1256] 4. Server

[1257] Based on the analysis results, the system generates the optimal subsidy and insurance plan for the user's financial situation and treatment information. This proposal is returned to the device from the server in JSON format.

[1258] Check and select a plan

[1259] 5. Terminal

[1260] The device displays the optimal plan received from the server on the user's screen, and a UI is provided that allows the user to select the optimal plan from multiple proposals.

[1261] 6. Users

[1262] The user selects the most suitable plan from those displayed on the screen and clicks the confirmation button.

[1263] Automatic document generation and delivery

[1264] 7. Server

[1265] The server generates the necessary application documents based on the selected plan, a process that is automated using templates.

[1266] 8. Server

[1267] The generated documents are then sent electronically to the appropriate authority (such as an insurance company or government agency) via email or an online application form.

[1268] Delivery status tracking and notification

[1269] 9. Server

[1270] The server tracks the status of submitted documents in real time and records them in a database, providing updates on the status of submission and receipt.

[1271] 10. Terminal

[1272] Users can check the delivery and receipt status in real time through their devices, and timely information is provided to users through the notification function.

[1273] Specific examples

[1274] For example, suppose a user enters information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment. This information is sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and the user selects insurance plan B. The server generates application documents based on insurance plan B and sends them to the insurance company. The server then tracks the submission and acceptance status in real time and notifies the user of the information.

[1275] In this way, the system can process grant and insurance applications quickly and efficiently, reducing the financial burden on users, allowing them to complete complex procedures with minimal effort.

[1276] The processing flow will be explained below.

[1277] Program processing flow

[1278] Entering and submitting user information

[1279] Step 1:

[1280] User:

[1281] Users log in using a web browser or application and enter details such as income, expenses, treatment details, and treatment duration.

[1282] Step 2:

[1283] Device:

[1284] The device converts the input information into JSON format and generates a request to send to the specified API endpoint.

[1285] Receiving and storing information

[1286] Step 3:

[1287] server:

[1288] The server receives the user information sent from the terminal and temporarily stores it in memory or intermediate data storage.

[1289] Analysis of information and proposal of plans

[1290] Step 4:

[1291] server:

[1292] The server passes the stored information to natural language processing models and generative AI models for analysis.

[1293] Step 5:

[1294] server:

[1295] A generative AI model generates a list of optimal subsidies and insurance plans for the user based on the analysis results.

[1296] Step 6:

[1297] server:

[1298] Sends the list of generated plans to the terminal in JSON format.

[1299] View and review your plan

[1300] Step 7:

[1301] Device:

[1302] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[1303] Step 8:

[1304] User:

[1305] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[1306] Step 9:

[1307] Device:

[1308] The device generates and sends an API request to notify the server of the user's plan selection.

[1309] Automatic document generation

[1310] Step 10:

[1311] server:

[1312] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[1313] Step 11:

[1314] server:

[1315] Save the generated document in a database or file storage and generate a preview link for the user.

[1316] Step 12:

[1317] server:

[1318] The generated preview link is sent to the user's device.

[1319] Start the application process

[1320] Step 13:

[1321] User:

[1322] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[1323] Step 14:

[1324] Device:

[1325] The terminal generates and sends an API request to notify the server of the operation to start the application.

[1326] Document delivery and tracking

[1327] Step 15:

[1328] server:

[1329] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[1330] Step 16:

[1331] server:

[1332] Delivery status is tracked in real time and recorded in a database.

[1333] Notification of delivery and receipt status

[1334] Step 17:

[1335] Device:

[1336] Users will be able to see the status of their shipments in real time through an updated dashboard.

[1337] Step 18:

[1338] server:

[1339] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[1340] Step 19:

[1341] Device:

[1342] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[1343] This process flow allows users to complete grant and insurance application procedures efficiently and with minimal effort.

[1344] Example 1

[1345] 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."

[1346] With conventional systems, selecting the most appropriate subsidy or insurance plan based on an individual's financial situation and treatment information, and then completing the application process, required a lot of time and effort. Furthermore, creating and sending the necessary application documents, as well as tracking their status, were often done manually, resulting in inefficient procedures and errors. There is a need to solve these problems and realize more efficient and accurate proposals and application processes for subsidies and insurance plans.

[1347] 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.

[1348] In this invention, the server includes means for accepting data on an individual's financial situation and medical treatment information, means for analyzing the data using a specific machine learning model and generation algorithm, means for proposing optimal subsidies and insurance plans for the individual based on the analysis results, means for automatically generating documents required for application in accordance with the proposed subsidies and insurance plans, means for sending the generated documents to a predetermined institution and tracking the sending status, and means for recording the sending results in a database and notifying the user. This enables the user to quickly and efficiently receive optimal subsidies and insurance plans and automatically complete the application process.

[1349] "Personal financial and medical information" refers to detailed information about an individual's financial situation and medical care, such as income, expenses, treatment, and duration of treatment.

[1350] A "machine learning model" refers to a collection of algorithms that learn patterns and rules from data and make predictions and classifications for new data.

[1351] A "generative algorithm" refers to a computational method for generating output in a particular format from input data.

[1352] "Subsidy or insurance plan" refers to a group of financial assistance or insurance services provided based on an individual's financial situation and treatment information.

[1353] "Documents required for application" refers to official documents required to access subsidies or insurance plans.

[1354] "Prescribed agency" refers to the official organization or body that administers and manages the subsidy or insurance plan.

[1355] "Delivery status" refers to the progress status after the generated document has been sent to the specified institution.

[1356] A "database" refers to an information collection system that stores data in an organized manner and allows it to be accessed and managed as needed.

[1357] "Notifying the user" means that the system provides information and updates to the user.

[1358] "Efficiently" refers to achieving maximum results with minimum time and resources.

[1359] As an embodiment of the present invention, a system is provided that proposes optimal subsidies and insurance plans based on an individual's financial situation and treatment information, and automates application procedures.

[1360] The system, which operates online and is primarily comprised of a server, terminals, and users, utilizes advanced natural language processing and generative AI models to propose the optimal plan to users through a multi-step process and then complete the application process.

[1361] The server performs data analysis using natural language processing models and generative AI models that utilize Python's TensorFlow library and the BERT model, etc. The terminal refers to a device that can connect to the internet, such as a PC or smartphone.

[1362] Entering user information

[1363] Users log in to the system via a web browser or application and enter information such as their income, expenses, treatment details, and treatment period. For example, they enter information such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" and click the "Submit" button.

[1364] The device takes the information entered by the user, converts it to JSON format, and sends it to the server. For example, it is converted as follows:

[1365] json

[1366] {

[1367] "Income": 300000,

[1368] "Expenditure": 200000,

[1369] "Treatment details": "Chemotherapy",

[1370] "Treatment duration": "6 months"

[1371] }

[1372] Analysis of information and suggestions

[1373] The server receives the JSON data sent from the device and stores it in a database, which can be structured as an SQL table like this:

[1374] sql

[1375] CREATE TABLE user information (

[1376] id INT AUTO_INCREMENT PRIMARY KEY,

[1377] Income INT,

[1378] Expenditure INT,

[1379] Treatment details VARCHAR(255),

[1380] Treatment period VARCHAR(255)

[1381] );

[1382] The stored data is analyzed using natural language processing and generative AI models. Based on the analysis results, the optimal subsidy or insurance plan is generated. Examples of prompts for the generative AI model include:

[1383] text

[1384] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[1385] Check and select a plan

[1386] The device displays the proposals received from the server on the user's screen. For example, a UI is provided that allows users to compare multiple plans, such as "Subsidy Plan A" and "Insurance Plan B."

[1387] The user selects the most suitable plan from the plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[1388] Automatic document generation and delivery

[1389] The server automatically generates application documents according to the plan selected by the user. This process is done using a template engine (e.g., Jinja2) to embed user information in templates. The generated documents are then sent electronically to the designated institution. This process can be done, for example, by email using the SMTP protocol or by using the auto-fill function of an online application form.

[1390] Delivery status tracking and notification

[1391] The server tracks the status of submitted documents in real time and records progress information in a database. Users can check the status of submission and receipt via their devices. Status information displayed on the dashboard keeps users up to date with the latest situation. A notification function also provides users with real-time updates.

[1392] The system allows users to quickly and efficiently find the most suitable subsidy or insurance plan and automatically complete the application process.

[1393] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1394] Step 1: Enter your user information

[1395] Users log in to the system through a web browser or application and enter personal information such as income, expenses, treatment details, and treatment period. For example, they enter details such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" into the form and click the "Submit" button.

[1396] Input: Data on income, expenses, treatment details, and treatment duration

[1397] Output: Personal information entered (form data)

[1398] Specifically, for example, data is sent by entering numbers or text into an application input form and pressing the "Send" button.

[1399] Step 2: Collect and send data

[1400] The device takes the information entered by the user and converts it into JSON format, for example, the following data format:

[1401] json

[1402] {

[1403] "Income": 300000,

[1404] "Expenditure": 200000,

[1405] "Treatment details": "Chemotherapy",

[1406] "Treatment duration": "6 months"

[1407] }

[1408] The converted data is sent to the server.

[1409] Input: Personal information entered by the user (form data)

[1410] Output: JSON format data

[1411] Specifically, the terminal analyzes the form data, generates a data object in JSON format, and sends it to the server via an HTTP request.

[1412] Step 3: Receiving and storing data

[1413] The server receives the JSON data sent from the device and stores it in a database, for example using the following SQL table structure:

[1414] sql

[1415] CREATE TABLE user information (

[1416] id INT AUTO_INCREMENT PRIMARY KEY,

[1417] Income INT,

[1418] Expenditure INT,

[1419] Treatment details VARCHAR(255),

[1420] Treatment period VARCHAR(255)

[1421] );

[1422] Input: JSON data sent from the terminal

[1423] Output: Personal information stored in the database

[1424] Specifically, the server receives the HTTP request, parses the JSON data, executes an SQL insert query, and saves it in the database.

[1425] Step 4: Analyze the data

[1426] The server analyzes the stored data using a natural language processing model (e.g., BERT) and a generative AI model (e.g., TensorFlow). An example of a prompt for the generative AI model is as follows:

[1427] text

[1428] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[1429] Input: Personal information retrieved from the database

[1430] Output: Subsidy and insurance plan proposals as analysis results

[1431] Specifically, the server retrieves information from the database, inputs that data into the generative AI model as prompt sentences, and calculates and proposes the optimal plan.

[1432] Step 5: Submit and view your proposal

[1433] The device receives the analysis results (optimal plan proposals) from the server and displays them on the user's screen. For example, it presents multiple options such as "Subsidy Plan A" and "Insurance Plan B."

[1434] Input: Proposal results sent from the server (JSON format)

[1435] Output: Plan proposal displayed on user screen

[1436] Specifically, the device receives JSON data from the server, analyzes the data, and reflects it on the UI.

[1437] Step 6: Choose a plan

[1438] The user selects the most suitable plan from the multiple plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[1439] Input: Multiple plan proposals

[1440] Output: The plan selected by the user

[1441] Specifically, the user clicks a button to select from the presented options.

[1442] Step 7: Auto-generate documents

[1443] The server automatically generates application documents based on the plan selected by the user. This process uses a template engine (e.g., Jinja2) and embeds user information into the template.

[1444] Input: User selected plan, user information

[1445] Output: Generated application documents

[1446] Specifically, the server inputs the user's selection information and personal information into a template engine to generate the necessary documents.

[1447] Step 8: Send your documents

[1448] The server then sends the generated documents to the appropriate authorities electronically, using email via the SMTP protocol and auto-filling of online application forms.

[1449] Input: Generated application documents

[1450] Output: Documents sent to the designated institution

[1451] Specifically, the server sends emails or API requests to deliver documents to the necessary institutions.

[1452] Step 9: Track your shipment

[1453] The server tracks the status of submitted documents in real time and records the information in a database.

[1454] Input: Status information after sending documents

[1455] Output: Delivery status recorded in the database

[1456] Specifically, the server obtains status information from a predetermined organization and stores it in a database.

[1457] Step 10: Notify users

[1458] Users can check the status of their shipments and receipts through their devices. For example, the following status information is displayed on the dashboard:

[1459] html

[1460]

[1461] <h3> Insurance Plan B Application Status< / h3>

[1462] Delivery completed: 2023-04-01

[1463] Waiting for acceptance

[1464]

[1465] Input: Database status information

[1466] Output: Status information displayed on the user's screen

[1467] Specifically, the device retrieves status information from a database and notifies the user in real time.

[1468] (Application example 1)

[1469] 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."

[1470] Existing food delivery services do not offer optimal meal plans or discount plans that take into account the user's financial situation or health information, forcing users to make complex choices. Furthermore, the ordering process is cumbersome and there is a lack of ways to track delivery status in real time. Therefore, it is necessary to improve user convenience and efficiency.

[1471] 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.

[1472] In this invention, the server includes means for accepting personal financial and health information such as income, expenses, health information, and dietary restriction information, means for analyzing the information using a specific natural language processing model and a generative AI model, means for proposing optimal meal plans and discount plans for the individual based on the analysis results, means for automatically generating an order based on the proposed meal plans and discount plans, and means for sending the generated order to a predetermined institution and tracking the delivery status. This allows users to easily select the meal plan or discount plan that is optimal for their financial and health situations, and automates the process from ordering to tracking delivery.

[1473] "Income" is the money or economic benefits that an individual receives over a period of time.

[1474] "Expenses" are the money or financial burden that an individual spends over a certain period of time.

[1475] "Health information" refers to health-related data such as an individual's dietary restrictions, food allergies, and health goals.

[1476] "Dietary restriction information" is information about foods that an individual should avoid for specific reasons (such as allergies, religion, or health goals).

[1477] "Personal economic situation" refers to general data related to an individual's economic activities, such as income and expenditure.

[1478] A "natural language processing model" is an algorithm or method that allows a computer to analyze and understand human language.

[1479] A "generative AI model" is an artificial intelligence model that generates optimal output from input data.

[1480] A "meal plan" is a meal plan proposed taking into account an individual's financial situation and health information.

[1481] A "discount plan" is a method of offering discounts that can be applied to meal orders.

[1482] "Means for automatically generating orders" refers to a system or process that automatically generates order content based on a proposed plan.

[1483] A "prescribed institution" is an organization or business that receives and fulfills orders, such as a restaurant or food delivery service.

[1484] "Shipping Tracking Measures" means systems and methods for monitoring and managing the shipping and delivery progress of an order.

[1485] "User" refers to an individual who uses the System to select and order a meal plan or discount plan.

[1486] As an embodiment of the present invention, we provide a system that proposes optimal meal plans and discount plans based on a user's financial situation and health information, and automates the ordering process. This system is composed of a server, terminals, and users, and proposes meal plans and discount plans and executes the ordering process through a multi-stage process. The specific details of this system are described below.

[1487] Entering user information

[1488] Users log in to the service using their smartphones and enter data such as their income, expenses, dietary restrictions, and health goals. This information is sent from the device to the server in JSON format.

[1489] Analysis of information and suggestions

[1490] The server stores the received data in a database and analyzes it using specific natural language processing and generative AI models. Based on the analysis results, it generates meal plans and discount plans that are optimal for the user's financial situation and health information. These proposals are also returned from the server to the device in JSON format.

[1491] Check and select a plan

[1492] The device displays the optimal plan received from the server on the user's screen, and the user can use the UI to select the appropriate one from multiple proposals. Once a selection is made, the information is sent to the server.

[1493] Automatic order generation and dispatch

[1494] The server automatically generates an order based on the selected plan. This process is automated using templates. The generated order is then electronically sent to the partner restaurant or food delivery service, where it is confirmed.

[1495] Delivery tracking and notifications

[1496] The server tracks the order status in real time and records it in a database. Delivery status updates are immediately sent to the user, who can then view the delivery progress in real time via their device.

[1497] Specific examples

[1498] For example, suppose a user inputs their income of ¥300,000, expenses of ¥200,000, requests a vegetarian meal plan, and a goal of 2,000 calories per day. This information is sent to the server and analyzed by the generative AI model. The optimal meal plan A and discount plan B are suggested, and the user selects meal plan A. The server then generates an order based on the suggestions and sends it to the partner restaurant.

[1499] Prompt Sentence Examples

[1500] An example of a prompt sentence to be input to the generative AI model is as follows:

[1501] Suppose a user has an income of ¥300,000, expenses of ¥200,000, is a vegetarian, and is aiming for 2,000 calories per day. What meal plan would you suggest?

[1502] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1503] Step 1:

[1504] Entering user information

[1505] A user logs into the service using a smartphone and enters data such as their income, expenses, dietary restrictions, and health goals. This data is encoded in JSON format and sent from the device to the server. Examples of input data include income of 300,000 yen, expenses of 200,000 yen, being a vegetarian, and 2,000 calories per day. The device collects this data and prepares it for further processing.

[1506] Step 2:

[1507] Receiving and storing information on the server side

[1508] The server receives the JSON data sent from the device and stores it in a database. At this point, the server checks the data for consistency and cleans it if necessary. The data received includes income, expenses, dietary restrictions, and health goals. The consistency check includes checking for missing fields and data format.

[1509] Step 3:

[1510] Analysis using natural language processing and AI models

[1511] The server inputs the stored data into a natural language processing model and a generative AI model for analysis. Data processing involves standardizing numerical data such as income and expenses, and vectorizing text data such as dietary restrictions and health goals. Based on this, optimal meal plans and discount plans are generated for the user. An example of a prompt input to the generative AI model is, "Please suggest a meal plan for the user whose income is 300,000 yen, expenses are 200,000 yen, and the user is a vegetarian, aiming for 2,000 calories per day."

[1512] Step 4:

[1513] Generate and return a plan

[1514] Based on the analysis results, the server creates optimal meal plans and discount plans and returns them to the device in JSON format, including plan details, price information, calorie information, etc. Specifically, meal plan A (price 3,000 yen, 2,000 calories) and discount plan B (10% discount coupon) are generated.

[1515] Step 5:

[1516] Check and select a plan

[1517] The device displays the plan information received from the server to the user. The user can select the most suitable plan from multiple proposals on the screen. For example, if the user selects meal plan A, that information is sent from the device to the server. The device reflects this information in the UI, which is designed to be easy for the user to use.

[1518] Step 6:

[1519] Automatic order generation and dispatch

[1520] The server automatically generates an order based on the selected plan and electronically transmits it to the partner restaurant or food delivery service. In this process, the order information is formatted based on a template. Specifically, an order based on meal plan A is generated and transmitted to the partner restaurant.

[1521] Step 7:

[1522] Delivery tracking and notifications

[1523] The server tracks the delivery status of the generated order in real time and records it in a database. Status updates are instantly sent to the user, who can view the progress via their device. Delivery information is displayed as a status such as "on delivery" or "received."

[1524] Through this multi-step process, the system suggests a meal plan that suits the user's financial and health situation, and then automatically generates an order and tracks the delivery status.

[1525] 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.

[1526] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on a user's financial situation and treatment information, automates the application process, and recognizes the user's emotions and adjusts the proposals and support content based on those emotions.

[1527] System Overview

[1528] The system is mainly composed of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans for users through a multi-step process. It also uses an emotion engine to recognize users' emotions and optimize the process accordingly.

[1529] Entering and submitting user information

[1530] 1. Users

[1531] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, and also input their emotional state or have it automatically detected through facial recognition and voice analysis.

[1532] 2. Terminal

[1533] The terminal collects the economic information and emotional data entered by the user, converts it into JSON format, and sends it to the server.

[1534] Receiving and storing information

[1535] 3. Server

[1536] The server receives the user information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[1537] Analyzing information and emotions and proposing plans

[1538] 4. Server

[1539] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[1540] 5. Server

[1541] Based on the generated analysis results and sentiment evaluation results, a list of the most suitable subsidy and insurance plans for the user is generated. Based on the results of the sentiment engine, the priority of the proposed plans is adjusted.

[1542] 6. Server

[1543] Sends the list of generated plans to the terminal in JSON format.

[1544] View and review your plan

[1545] 7. Terminal

[1546] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[1547] 8. Users

[1548] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[1549] 9. Terminal

[1550] The device generates and sends an API request to notify the server of the user's plan selection.

[1551] Automatic document generation

[1552] 10. Server

[1553] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[1554] 11. Server

[1555] Save the generated document in a database or file storage and generate a preview link for the user.

[1556] 12. Server

[1557] The generated preview link is sent to the user's device.

[1558] Start the application process

[1559] 13. Users

[1560] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[1561] 14. Terminal

[1562] The terminal generates and sends an API request to notify the server of the operation to start the application.

[1563] Document delivery and tracking

[1564] 15. Server

[1565] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[1566] 16. Server

[1567] Delivery status is tracked in real time and recorded in a database.

[1568] Notification of delivery and receipt status

[1569] 17. Terminal

[1570] Users will be able to see the status of their shipments in real time through an updated dashboard.

[1571] 18. Server

[1572] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[1573] 19. Terminal

[1574] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[1575] Specific examples

[1576] For example, suppose a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user's stress level is high. This information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and special assistance plan C is also added depending on the user's stress level. The user selects insurance plan B, and the server generates application documents based on this and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[1577] In this way, the system can provide optimal assistance quickly and efficiently, taking into account the user's emotional state, while reducing the user's financial burden. This process allows users to complete complex procedures with minimal effort and also provides psychological support.

[1578] The processing flow will be explained below.

[1579] Program processing flow

[1580] Entering user information and emotion data

[1581] Step 1:

[1582] User:

[1583] Users log in via a web browser or application and enter detailed information such as income, expenses, treatment details, and treatment duration. In addition, the user's emotional state can be entered or automatically detected using facial recognition and voice analysis.

[1584] Step 2:

[1585] Device:

[1586] The device converts the input economic information and sentiment data into JSON format and generates a request to send to the specified API endpoint.

[1587] Receiving and storing information

[1588] Step 3:

[1589] server:

[1590] The server receives the user's economic information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[1591] Analyzing information and emotions and generating plans

[1592] Step 4:

[1593] server:

[1594] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[1595] Step 5:

[1596] server:

[1597] Based on the analysis results and sentiment evaluation results, a list of subsidies and insurance plans that are best suited to the user is generated. The results of the sentiment engine are used to adjust the priority of the proposed plans.

[1598] Step 6:

[1599] server:

[1600] The list of generated plans is sent to the terminal in JSON format.

[1601] View and review your plan

[1602] Step 7:

[1603] Device:

[1604] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[1605] Step 8:

[1606] User:

[1607] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[1608] Step 9:

[1609] Device:

[1610] The device generates and sends an API request to notify the server of the user's plan selection.

[1611] Automatic document generation

[1612] Step 10:

[1613] server:

[1614] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[1615] Step 11:

[1616] server:

[1617] Save the generated document in a database or file storage and generate a preview link for the user.

[1618] Step 12:

[1619] server:

[1620] The generated preview link is sent to the user's device.

[1621] Start the application process

[1622] Step 13:

[1623] User:

[1624] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[1625] Step 14:

[1626] Device:

[1627] The terminal generates and sends an API request to notify the server of the operation to start the application.

[1628] Document delivery and tracking

[1629] Step 15:

[1630] server:

[1631] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[1632] Step 16:

[1633] server:

[1634] Delivery status is tracked in real time and recorded in a database.

[1635] Notification of delivery and receipt status

[1636] Step 17:

[1637] Device:

[1638] Users will be able to see the status of their shipments in real time through an updated dashboard.

[1639] Step 18:

[1640] server:

[1641] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[1642] Step 19:

[1643] Device:

[1644] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[1645] Specific examples

[1646] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user also has a high stress level, this information and emotion data will be sent to the server.

[1647] Information and emotion data analysis

[1648] The server performs analysis using a generative AI model and generates the optimal subsidy plan A and insurance plan B. The emotion engine evaluates the stress level as high and also suggests special support plan C.

[1649] Select a plan and generate documents

[1650] The user checks the plans on the terminal and selects insurance plan B. The server automatically generates application documents based on that and sends them to the insurance company.

[1651] Track delivery and receipt status

[1652] The server tracks the delivery status of the generated document in real time and notifies the user of that information. The server also tracks the receipt status and notifies the user.

[1653] In this way, the system can reduce the user's financial burden and provide optimal assistance quickly and efficiently, taking into account their emotional state. This process allows users to complete complex procedures with minimal effort and also receive psychological support.

[1654] Example 2

[1655] 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."

[1656] In modern society, it is extremely complicated for individuals to select and apply for the most suitable subsidy or insurance plan. Furthermore, there is no system that provides optimal recommendations that take into account each individual's emotional state. Therefore, an effective system is needed to reduce the individual's financial burden and psychological stress at the same time.

[1657] 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.

[1658] In this invention, the server includes: means for receiving personal financial situation and treatment information such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for detecting the user's emotional state and evaluating it based on the analysis results; means for proposing optimal subsidies and insurance plans for the individual based on the analysis results and emotional evaluation results; means for automatically generating documents required for application according to the proposed subsidies and insurance plans; and means for sending the generated documents to a predetermined institution and tracking the delivery status. This enables individuals to complete complex procedures with minimal effort and also receive psychological support by receiving optimal suggestions based on their emotional state.

[1659] "Income" refers to the money or assets that an individual receives over a period of time.

[1660] "Expenditure" refers to the money or assets an individual uses for consumption or obligations over a period of time.

[1661] "Treatment content" refers to the medical procedures and treatment methods an individual receives, including details thereof.

[1662] "Treatment period" refers to the period during which a particular medical procedure or treatment method is performed.

[1663] "Personal economic situation" refers to information that comprehensively represents an individual's financial situation, such as income, expenses, assets, and loans.

[1664] "Treatment information" refers to detailed information about medical treatment an individual receives, including the content and duration of treatment.

[1665] A "natural language processing model" refers to an algorithm or program designed to analyze and understand the meaning of natural language text.

[1666] A "generative AI model" refers to an algorithm or program that uses machine learning techniques to analyze data and generate new information or suggestions.

[1667] "Emotional state" refers to an individual's psychological state, including stress level and type of emotion.

[1668] A "grant" is financial support provided by a government or institution for a specific purpose or under specific conditions.

[1669] "Insurance Plan" means a plan that includes a set of services or coverages offered by an insurance company.

[1670] "Application" refers to the official documentation required to apply for a grant or insurance plan.

[1671] "Authorized institutions" refer to official organizations, such as government agencies or insurance companies, that accept applications for grants or insurance.

[1672] "Delivery status" refers to the process and status of application documents from the time they are sent to the designated institution until they are accepted.

[1673] As an embodiment of the present invention, a system comprising a server, a terminal, and a user is provided. A specific implementation method will be described below.

[1674] The system begins with the user entering personal financial and medical information, such as income, expenses, treatment details, and treatment duration. The user enters this information through a dedicated terminal application. The user's emotional state can also be entered manually or automatically detected using a facial recognition camera or voice analysis.

[1675] The terminal collects the economic and sentiment data entered by the user and converts this information into JSON format, which is then sent to the server using the HTTPS protocol.

[1676] The server receives the user information and emotion data sent from the device and temporarily stores it in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[1677] The stored data is passed to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis. This analysis deciphers the user's medical information and financial situation and identifies appropriate subsidies and insurance plans. At the same time, emotion data is passed to an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[1678] The server combines the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user, which is then sent to the device in JSON format.

[1679] The device displays the list of plans received from the server to the user and provides an interface for the user to select. The user selects the most suitable plan from the displayed plans and clicks the confirmation button. The device generates and sends an API request to notify the server of the selection.

[1680] The server automatically generates the documents required for application based on the plan selected by the user. A template engine (e.g., Handlebars.js) is used to generate the documents, embedding the user's required information. The generated documents are saved in a database (e.g., PostgreSQL) or file storage (e.g., Amazon S3).

[1681] After the document is generated, the server sends a preview link to the user. The user checks this preview link and, if there are no problems, clicks the "Start application" button. This operation causes the device to generate an API request to start the application and send it to the server.

[1682] The server routes the documents to the appropriate authority (insurance company, government agency). The delivery status is tracked in real time and recorded in a database. The delivery status and receipt status are checked periodically, and the latest information is updated on the user's dashboard.

[1683] The above processing flow builds a system that provides optimal support based on the user's emotional state while reducing the user's financial burden.

[1684] Specific examples

[1685] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy, and the emotion engine detects a high stress level, the information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A, insurance plan B, and special needs plan C are then proposed. The user selects insurance plan B, and the server generates application documents based on that and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[1686] Prompt Sentence Examples

[1687] My income is 300,000 yen, my expenses are 200,000 yen, I'm undergoing chemotherapy treatment for 6 months, and my stress level is high. Please suggest the best subsidy and insurance plan.

[1688] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1689] Step 1:

[1690] Users log in to the system and enter information such as their income, expenses, treatment details, and treatment duration, as well as their emotional state, which can be entered manually or automatically detected through facial recognition cameras and voice analysis.

[1691] Input: User's income, expenses, treatment details, treatment duration, emotional state

[1692] Output: Collected personal information and emotional data

[1693] Step 2:

[1694] The terminal receives the economic and emotional data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[1695] Input: User's financial information and emotional data

[1696] Output: Data converted to JSON format

[1697] Step 3:

[1698] The server receives the user information and emotion data sent from the device and temporarily stores them in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[1699] Input: User information and emotion data in JSON format

[1700] Output: Data stored in the database

[1701] Step 4:

[1702] The server passes the stored data to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis, and inputs emotional data into an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[1703] Input: User information and emotion data stored in the database

[1704] Output: Analysis results and emotion evaluation results

[1705] Step 5:

[1706] The server integrates the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user. It also adjusts the priority of the plans based on the evaluation results of the emotion engine.

[1707] Input: Analysis results and emotion evaluation results

[1708] Output: List of best subsidies and insurance plans

[1709] Step 6:

[1710] The server sends the list of generated plans to the terminal in JSON format.

[1711] Input: List of best subsidies and insurance plans

[1712] Output: Plan list in JSON format

[1713] Step 7:

[1714] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[1715] Input: Plan list in JSON format

[1716] Output: User selectable Show Plan interface

[1717] Step 8:

[1718] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[1719] Input: Show Plan interface

[1720] Output: User's plan selection

[1721] Step 9:

[1722] The device generates and sends an API request to notify the server of the user's plan selection.

[1723] Input: User's plan selection

[1724] Output: API request

[1725] Step 10:

[1726] The server automatically generates the necessary application documents based on the selected plan. It uses a template engine (e.g., Handlebars.js) to create the application documents by embedding the necessary user information.

[1727] Input: User's plan selection

[1728] Output: Auto-generated application documents

[1729] Step 11:

[1730] The server stores the generated document in a database or file storage and generates a preview link for the user.

[1731] Input: Auto-generated application documents

[1732] Output: Preview link

[1733] Step 12:

[1734] The server sends the generated preview link to the user's terminal.

[1735] Input: Preview link

[1736] Output: Preview link sent to your device

[1737] Step 13:

[1738] The user clicks on the preview link sent to check the documents, and if there are no problems, clicks the "Start application" button.

[1739] Input: Preview link

[1740] Output: Application start operation

[1741] Step 14:

[1742] The terminal generates and sends an API request to notify the server of the operation to start the application.

[1743] Input: Start application operation

[1744] Output: API request

[1745] Step 15:

[1746] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[1747] Input: API request and application documents

[1748] Output: Documents sent

[1749] Step 16:

[1750] The server tracks the document delivery status in real time and records it in a database.

[1751] Input: Documents sent

[1752] Output: Record of document delivery status in database

[1753] Step 17:

[1754] The device provides a dashboard so users can check delivery status in real time.

[1755] Input: Document delivery status data

[1756] Output: Real-time updated dashboard

[1757] Step 18:

[1758] The server periodically checks the acceptance status of the application documents, obtains the latest acceptance status, and records it in the database.

[1759] Input: Application acceptance status

[1760] Output: Record of acceptance status in database

[1761] Step 19:

[1762] The terminal reflects the latest acceptance status provided by the server on the dashboard and provides a notification to the user.

[1763] Input: Acceptance status data

[1764] Output: Updated dashboard and notification to the user

[1765] (Application example 2)

[1766] 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."

[1767] Existing subsidy and insurance plan recommendation systems suggest optimal plans based on the user's financial information, but do not take into account the user's emotional state, resulting in a lack of appropriate support under stressful circumstances. Furthermore, there is a risk that users may send incorrect information during times of high stress, leading to problems with insufficient financial burden reduction and psychological support.

[1768] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for accepting an individual's financial situation and treatment information, such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for proposing the optimal subsidy or insurance plan for the individual based on the analysis results; means for automatically generating documents required for application according to the proposed subsidy or insurance plan; means for sending the generated documents to a specified institution and tracking the delivery status; means for proposing and implementing optimal security measures based on the user's financial situation and emotional state; and means for recognizing the user's emotional state in real time and adjusting the proposed content. This makes it possible to provide appropriate support that takes into account the user's emotional state, while simultaneously implementing security measures such as preventing erroneous transmissions during times of high stress.

[1769] "Income" is the total amount of money, or value that can be converted into money, that an individual receives over a given period of time.

[1770] "Expenditure" is the total amount of money an individual uses for living and business purposes.

[1771] "Treatment content" refers to details such as the specific treatment procedures and methods used at medical institutions, as well as the medicines and equipment used.

[1772] "Treatment period" refers to the entire period required to receive a given treatment.

[1773] "Personal financial situation" refers to a person's financial stability and health based on income, expenses, assets, liabilities, etc.

[1774] A "natural language processing model" is a model that uses algorithms and techniques to enable computers to understand and analyze human language.

[1775] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to automatically generate new information or suggestions from data.

[1776] A "grant" is financial assistance provided by governments or other organizations to individuals or organizations that meet certain criteria.

[1777] "Insurance plan" refers to the types and terms of a contract offered by an insurance company to provide coverage against certain risks.

[1778] "Automatic document generation" is the process of using templates and predefined data to automatically fill in the necessary information and create a document in a predetermined format.

[1779] "Emotional state" refers to an individual's current feelings or mental state.

[1780] "Security measures" is a general term for measures and actions taken to protect individuals and systems from various risks and threats.

[1781] "Real time" refers to the ability to process and display ongoing situations and events instantly, with minimal delay.

[1782] To implement this invention, a system is required that proposes optimal subsidies, insurance plans, and security measures based on the user's financial situation and emotional state, and automates the application process. The system is primarily composed of a server, terminals, and users, and provides optimal support to users through a multi-stage process.

[1783] Hardware and software used

[1784] Hardware

[1785] Smart glasses: Equipped with a face recognition camera, voice recognition microphone, high-performance processor, and Wi-Fi module

[1786] Server: High-performance computer system

[1787] software

[1788] AWS Lambda: Used for serverless computation to process economic and sentiment data of users.

[1789] Amazon S3: For temporary data storage.

[1790] Amazon Rekognition: A facial recognition engine for emotion recognition.

[1791] Google Dialogflow: A natural language processing engine for interacting with users.

[1792] JSON format: Used for sending and receiving data.

[1793] System Operation

[1794] 1. Collection and Input

[1795] Users use the smart glasses to input their income, expenses, treatment details, and treatment duration, and the glasses also use a facial recognition camera and voice recognition microphone to recognize and collect data on the user's emotional state in real time.

[1796] 2. Data transmission

[1797] The collected data is converted into JSON format and sent to a server, which receives the data and temporarily stores it in Amazon S3.

[1798] 3. Data Analysis

[1799] Amazon Rekognition is used to analyze the collected sentiment data, and AWS Lambda then sends the analyzed economic and sentiment information to Google Dialogflow, which analyzes and generates optimal subsidies, insurance plans, and security measures.

[1800] 4. Proposing plans and measures

[1801] Based on the analysis results, the system will propose optimal plans and measures to the user, which will be sent to the user via smart glasses and can be viewed in real time.

[1802] 5. Real-time notification and action

[1803] Once the user selects a proposed plan or measure, the smart glasses transmit the selection to the server, which then automatically generates the appropriate application documents and sends them to the designated authority. The server also implements specific security measures (e.g., suspending transmissions) depending on the user's stress level.

[1804] Specific examples

[1805] For example, if a user enters information such as income of ¥300,000, expenses of ¥200,000, and six months of chemotherapy treatment, and the emotion engine detects high stress levels, the following prompt will be generated:

[1806] "Given your recent emotional state, we recommend temporarily suspending transmissions to avoid sending erroneous information during high stress situations. Would you like to cease transmissions?"

[1807] In this way, the system can quickly and efficiently provide optimal assistance that takes into account the user's emotional state, while reducing the user's financial burden.

[1808] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1809] Step 1:

[1810] The user uses the smart glasses to input their income, expenses, treatment details, and treatment duration. The smart glasses' facial recognition camera and voice recognition microphone detect and collect the user's emotional state in real time. Specifically, the user enters financial information (income, expenses, etc.), treatment information, as well as facial and voice data. This data is necessary for use in subsequent analysis steps.

[1811] Step 2:

[1812] The device (smart glasses) converts the collected economic information and emotion data into JSON format and sends it to the cloud server. This operation formats the raw data and converts it into a format that is easy for the server to receive.

[1813] Step 3:

[1814] The server temporarily stores the user information and emotion data sent from the device in JSON format in Amazon S3, making the data easily accessible for subsequent processing steps.

[1815] Step 4:

[1816] The server analyzes the stored data using AWS Lambda. First, it inputs the facial recognition data into Amazon Rekognition to perform a detailed analysis of the user's emotional state. This outputs the user's stress level and emotional state as numerical data.

[1817] Step 5:

[1818] AWS Lambda analyzes the economic information and sentiment data and sends it to Google Dialogflow, which uses natural language processing to generate optimal subsidies, insurance plans, and security measures. This results in a list of generated subsidy plans, insurance plans, and security measures.

[1819] Step 6:

[1820] The server uses a generative AI model to generate a list of optimal subsidies and insurance plans for each user based on the analysis and sentiment evaluation results, and adjusts priorities based on sentiment data. The generated results are then converted into JSON format.

[1821] Step 7:

[1822] The server sends the generated plan list in JSON format to the device. The device (smart glasses) visualizes and displays the plan list received from the server to the user. The user can select the most appropriate plan from the multiple plans presented.

[1823] Step 8:

[1824] Based on the plan selected by the user, the device will send an API request back to the server, which will receive the selection and automatically execute the steps to start the application process.

[1825] Step 9:

[1826] The server automatically generates the necessary application documents based on the selected plan. This process uses templates to generate documents with the user's information embedded. The server then sends the automatically generated documents to the designated institution via email or an online application form.

[1827] Step 10:

[1828] The server tracks the delivery status in real time and records the progress in a database, which is then periodically updated on the user's device.

[1829] Step 11:

[1830] Users can check the delivery status in real time using the smart glasses. In addition, the server periodically checks whether the application has been accepted and notifies the device of the latest status.

[1831] 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.

[1832] 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.

[1833] 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.

[1834] [Fourth embodiment]

[1835] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1836] 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.

[1837] 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).

[1838] 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.

[1839] 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.

[1840] 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).

[1841] 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.

[1842] 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.

[1843] 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.

[1844] 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.

[1845] 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.

[1846] 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.

[1847] 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."

[1848] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on the user's financial situation and treatment information, and automates the application process. The specific processing flow of this system is described below.

[1849] System Overview

[1850] The system is primarily comprised of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans to users through a multi-step process. The entire system operates online and utilizes advanced natural language processing and generative AI models.

[1851] Entering user information

[1852] 1. Users

[1853] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, etc. This information is entered through a web browser or application.

[1854] 2. Terminal

[1855] The device collects the information entered by the user and sends it to the server, with the data being sent using a standard format such as JSON.

[1856] Analysis of information and suggestions

[1857] 3. Server

[1858] The server receives the input data and stores it in a database. It then analyzes the collected data using specific natural language processing and generative AI models.

[1859] 4. Server

[1860] Based on the analysis results, the system generates the optimal subsidy and insurance plan for the user's financial situation and treatment information. This proposal is returned to the device from the server in JSON format.

[1861] Check and select a plan

[1862] 5. Terminal

[1863] The device displays the optimal plan received from the server on the user's screen, and a UI is provided that allows the user to select the optimal plan from multiple proposals.

[1864] 6. Users

[1865] The user selects the most suitable plan from those displayed on the screen and clicks the confirmation button.

[1866] Automatic document generation and delivery

[1867] 7. Server

[1868] The server generates the necessary application documents based on the selected plan, a process that is automated using templates.

[1869] 8. Server

[1870] The generated documents are then sent electronically to the appropriate authority (such as an insurance company or government agency) via email or an online application form.

[1871] Delivery status tracking and notification

[1872] 9. Server

[1873] The server tracks the status of submitted documents in real time and records them in a database, providing updates on the status of submission and receipt.

[1874] 10. Terminal

[1875] Users can check the delivery and receipt status in real time through their devices, and timely information is provided to users through the notification function.

[1876] Specific examples

[1877] For example, suppose a user enters information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment. This information is sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and the user selects insurance plan B. The server generates application documents based on insurance plan B and sends them to the insurance company. The server then tracks the submission and acceptance status in real time and notifies the user of the information.

[1878] In this way, the system can process grant and insurance applications quickly and efficiently, reducing the financial burden on users, allowing them to complete complex procedures with minimal effort.

[1879] The processing flow will be explained below.

[1880] Program processing flow

[1881] Entering and submitting user information

[1882] Step 1:

[1883] User:

[1884] Users log in using a web browser or application and enter details such as income, expenses, treatment details, and treatment duration.

[1885] Step 2:

[1886] Device:

[1887] The device converts the input information into JSON format and generates a request to send to the specified API endpoint.

[1888] Receiving and storing information

[1889] Step 3:

[1890] server:

[1891] The server receives the user information sent from the terminal and temporarily stores it in memory or intermediate data storage.

[1892] Analysis of information and proposal of plans

[1893] Step 4:

[1894] server:

[1895] The server passes the stored information to natural language processing models and generative AI models for analysis.

[1896] Step 5:

[1897] server:

[1898] A generative AI model generates a list of optimal subsidies and insurance plans for the user based on the analysis results.

[1899] Step 6:

[1900] server:

[1901] Sends the list of generated plans to the terminal in JSON format.

[1902] View and review your plan

[1903] Step 7:

[1904] Device:

[1905] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[1906] Step 8:

[1907] User:

[1908] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[1909] Step 9:

[1910] Device:

[1911] The device generates and sends an API request to notify the server of the user's plan selection.

[1912] Automatic document generation

[1913] Step 10:

[1914] server:

[1915] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[1916] Step 11:

[1917] server:

[1918] Save the generated document in a database or file storage and generate a preview link for the user.

[1919] Step 12:

[1920] server:

[1921] The generated preview link is sent to the user's device.

[1922] Start the application process

[1923] Step 13:

[1924] User:

[1925] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[1926] Step 14:

[1927] Device:

[1928] The terminal generates and sends an API request to notify the server of the operation to start the application.

[1929] Document delivery and tracking

[1930] Step 15:

[1931] server:

[1932] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[1933] Step 16:

[1934] server:

[1935] Delivery status is tracked in real time and recorded in a database.

[1936] Notification of delivery and receipt status

[1937] Step 17:

[1938] Device:

[1939] Users will be able to see the status of their shipments in real time through an updated dashboard.

[1940] Step 18:

[1941] server:

[1942] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[1943] Step 19:

[1944] Device:

[1945] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[1946] This process flow allows users to complete grant and insurance application procedures efficiently and with minimal effort.

[1947] Example 1

[1948] 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."

[1949] With conventional systems, selecting the most appropriate subsidy or insurance plan based on an individual's financial situation and treatment information, and then completing the application process, required a lot of time and effort. Furthermore, creating and sending the necessary application documents, as well as tracking their status, were often done manually, resulting in inefficient procedures and errors. There is a need to solve these problems and realize more efficient and accurate proposals and application processes for subsidies and insurance plans.

[1950] 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.

[1951] In this invention, the server includes means for accepting data on an individual's financial situation and medical treatment information, means for analyzing the data using a specific machine learning model and generation algorithm, means for proposing optimal subsidies and insurance plans for the individual based on the analysis results, means for automatically generating documents required for application in accordance with the proposed subsidies and insurance plans, means for sending the generated documents to a predetermined institution and tracking the sending status, and means for recording the sending results in a database and notifying the user. This enables the user to quickly and efficiently receive optimal subsidies and insurance plans and automatically complete the application process.

[1952] "Personal financial and medical information" refers to detailed information about an individual's financial situation and medical care, such as income, expenses, treatment, and duration of treatment.

[1953] A "machine learning model" refers to a collection of algorithms that learn patterns and rules from data and make predictions and classifications for new data.

[1954] A "generative algorithm" refers to a computational method for generating output in a particular format from input data.

[1955] "Subsidy or insurance plan" refers to a group of financial assistance or insurance services provided based on an individual's financial situation and treatment information.

[1956] "Documents required for application" refers to official documents required to access subsidies or insurance plans.

[1957] "Prescribed agency" refers to the official organization or body that administers and manages the subsidy or insurance plan.

[1958] "Delivery status" refers to the progress status after the generated document has been sent to the specified institution.

[1959] A "database" refers to an information collection system that stores data in an organized manner and allows it to be accessed and managed as needed.

[1960] "Notifying the user" means that the system provides information and updates to the user.

[1961] "Efficiently" refers to achieving maximum results with minimum time and resources.

[1962] As an embodiment of the present invention, a system is provided that proposes optimal subsidies and insurance plans based on an individual's financial situation and treatment information, and automates application procedures.

[1963] The system, which operates online and is primarily comprised of a server, terminals, and users, utilizes advanced natural language processing and generative AI models to propose the optimal plan to users through a multi-step process and then complete the application process.

[1964] The server performs data analysis using natural language processing models and generative AI models that utilize Python's TensorFlow library and the BERT model, etc. The terminal refers to a device that can connect to the internet, such as a PC or smartphone.

[1965] Entering user information

[1966] Users log in to the system via a web browser or application and enter information such as their income, expenses, treatment details, and treatment period. For example, they enter information such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" and click the "Submit" button.

[1967] The device takes the information entered by the user, converts it to JSON format, and sends it to the server. For example, it is converted as follows:

[1968] json

[1969] {

[1970] "Income": 300000,

[1971] "Expenditure": 200000,

[1972] "Treatment details": "Chemotherapy",

[1973] "Treatment duration": "6 months"

[1974] }

[1975] Analysis of information and suggestions

[1976] The server receives the JSON data sent from the device and stores it in a database, which can be structured as an SQL table like this:

[1977] sql

[1978] CREATE TABLE user information (

[1979] id INT AUTO_INCREMENT PRIMARY KEY,

[1980] Income INT,

[1981] Expenditure INT,

[1982] Treatment details VARCHAR(255),

[1983] Treatment period VARCHAR(255)

[1984] );

[1985] The stored data is analyzed using natural language processing and generative AI models. Based on the analysis results, the optimal subsidy or insurance plan is generated. Examples of prompts for the generative AI model include:

[1986] text

[1987] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[1988] Check and select a plan

[1989] The device displays the proposals received from the server on the user's screen. For example, a UI is provided that allows users to compare multiple plans, such as "Subsidy Plan A" and "Insurance Plan B."

[1990] The user selects the most suitable plan from the plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[1991] Automatic document generation and delivery

[1992] The server automatically generates application documents according to the plan selected by the user. This process is done using a template engine (e.g., Jinja2) to embed user information in templates. The generated documents are then sent electronically to the designated institution. This process can be done, for example, by email using the SMTP protocol or by using the auto-fill function of an online application form.

[1993] Delivery status tracking and notification

[1994] The server tracks the status of submitted documents in real time and records progress information in a database. Users can check the status of submission and receipt via their devices. Status information displayed on the dashboard keeps users up to date with the latest situation. A notification function also provides users with real-time updates.

[1995] The system allows users to quickly and efficiently find the most suitable subsidy or insurance plan and automatically complete the application process.

[1996] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1997] Step 1: Enter your user information

[1998] Users log in to the system through a web browser or application and enter personal information such as income, expenses, treatment details, and treatment period. For example, they enter details such as "income 300,000 yen, expenses 200,000 yen, chemotherapy for 6 months" into the form and click the "Submit" button.

[1999] Input: Data on income, expenses, treatment details, and treatment duration

[2000] Output: Personal information entered (form data)

[2001] Specifically, for example, data is sent by entering numbers or text into an application input form and pressing the "Send" button.

[2002] Step 2: Collect and send data

[2003] The device takes the information entered by the user and converts it into JSON format, for example, the following data format:

[2004] json

[2005] {

[2006] "Income": 300000,

[2007] "Expenditure": 200000,

[2008] "Treatment details": "Chemotherapy",

[2009] "Treatment duration": "6 months"

[2010] }

[2011] The converted data is sent to the server.

[2012] Input: Personal information entered by the user (form data)

[2013] Output: JSON format data

[2014] Specifically, the terminal analyzes the form data, generates a data object in JSON format, and sends it to the server via an HTTP request.

[2015] Step 3: Receiving and storing data

[2016] The server receives the JSON data sent from the device and stores it in a database, for example using the following SQL table structure:

[2017] sql

[2018] CREATE TABLE user information (

[2019] id INT AUTO_INCREMENT PRIMARY KEY,

[2020] Income INT,

[2021] Expenditure INT,

[2022] Treatment details VARCHAR(255),

[2023] Treatment period VARCHAR(255)

[2024] );

[2025] Input: JSON data sent from the terminal

[2026] Output: Personal information stored in the database

[2027] Specifically, the server receives the HTTP request, parses the JSON data, executes an SQL insert query, and saves it in the database.

[2028] Step 4: Analyze the data

[2029] The server analyzes the stored data using a natural language processing model (e.g., BERT) and a generative AI model (e.g., TensorFlow). An example of a prompt for the generative AI model is as follows:

[2030] text

[2031] "If a user's income is 300,000 yen, expenses are 200,000 yen, and the chemotherapy treatment period is 6 months, please suggest the optimal subsidy and insurance plan."

[2032] Input: Personal information retrieved from the database

[2033] Output: Subsidy and insurance plan proposals as analysis results

[2034] Specifically, the server retrieves information from the database, inputs that data into the generative AI model as prompt sentences, and calculates and proposes the optimal plan.

[2035] Step 5: Submit and view your proposal

[2036] The device receives the analysis results (optimal plan proposals) from the server and displays them on the user's screen. For example, it presents multiple options such as "Subsidy Plan A" and "Insurance Plan B."

[2037] Input: Proposal results sent from the server (JSON format)

[2038] Output: Plan proposal displayed on user screen

[2039] Specifically, the device receives JSON data from the server, analyzes the data, and reflects it on the UI.

[2040] Step 6: Choose a plan

[2041] The user selects the most suitable plan from the multiple plans displayed on the screen and clicks the "Select" button for "Insurance Plan B," for example.

[2042] Input: Multiple plan proposals

[2043] Output: The plan selected by the user

[2044] Specifically, the user clicks a button to select from the presented options.

[2045] Step 7: Auto-generate documents

[2046] The server automatically generates application documents based on the plan selected by the user. This process uses a template engine (e.g., Jinja2) and embeds user information into the template.

[2047] Input: User selected plan, user information

[2048] Output: Generated application documents

[2049] Specifically, the server inputs the user's selection information and personal information into a template engine to generate the necessary documents.

[2050] Step 8: Send your documents

[2051] The server then sends the generated documents to the appropriate authorities electronically, using email via the SMTP protocol and auto-filling of online application forms.

[2052] Input: Generated application documents

[2053] Output: Documents sent to the designated institution

[2054] Specifically, the server sends emails or API requests to deliver documents to the necessary institutions.

[2055] Step 9: Track your shipment

[2056] The server tracks the status of submitted documents in real time and records the information in a database.

[2057] Input: Status information after sending documents

[2058] Output: Delivery status recorded in the database

[2059] Specifically, the server obtains status information from a predetermined organization and stores it in a database.

[2060] Step 10: Notify users

[2061] Users can check the status of their shipments and receipts through their devices. For example, the following status information is displayed on the dashboard:

[2062] html

[2063]

[2064] <h3> Insurance Plan B Application Status< / h3>

[2065] Delivery completed: 2023-04-01

[2066] Waiting for acceptance

[2067]

[2068] Input: Database status information

[2069] Output: Status information displayed on the user's screen

[2070] Specifically, the device retrieves status information from a database and notifies the user in real time.

[2071] (Application example 1)

[2072] 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."

[2073] Existing food delivery services do not offer optimal meal plans or discount plans that take into account the user's financial situation or health information, forcing users to make complex choices. Furthermore, the ordering process is cumbersome and there is a lack of ways to track delivery status in real time. Therefore, it is necessary to improve user convenience and efficiency.

[2074] 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.

[2075] In this invention, the server includes means for accepting personal financial and health information such as income, expenses, health information, and dietary restriction information, means for analyzing the information using a specific natural language processing model and a generative AI model, means for proposing optimal meal plans and discount plans for the individual based on the analysis results, means for automatically generating an order based on the proposed meal plans and discount plans, and means for sending the generated order to a predetermined institution and tracking the delivery status. This allows users to easily select the meal plan or discount plan that is optimal for their financial and health situations, and automates the process from ordering to tracking delivery.

[2076] "Income" is the money or economic benefits that an individual receives over a period of time.

[2077] "Expenses" are the money or financial burden that an individual spends over a certain period of time.

[2078] "Health information" refers to health-related data such as an individual's dietary restrictions, food allergies, and health goals.

[2079] "Dietary restriction information" is information about foods that an individual should avoid for specific reasons (such as allergies, religion, or health goals).

[2080] "Personal economic situation" refers to general data related to an individual's economic activities, such as income and expenditure.

[2081] A "natural language processing model" is an algorithm or method that allows a computer to analyze and understand human language.

[2082] A "generative AI model" is an artificial intelligence model that generates optimal output from input data.

[2083] A "meal plan" is a meal plan proposed taking into account an individual's financial situation and health information.

[2084] A "discount plan" is a method of offering discounts that can be applied to meal orders.

[2085] "Means for automatically generating orders" refers to a system or process that automatically generates order content based on a proposed plan.

[2086] A "prescribed institution" is an organization or business that receives and fulfills orders, such as a restaurant or food delivery service.

[2087] "Shipping Tracking Measures" means systems and methods for monitoring and managing the shipping and delivery progress of an order.

[2088] "User" refers to an individual who uses the System to select and order a meal plan or discount plan.

[2089] As an embodiment of the present invention, we provide a system that proposes optimal meal plans and discount plans based on a user's financial situation and health information, and automates the ordering process. This system is composed of a server, terminals, and users, and proposes meal plans and discount plans and executes the ordering process through a multi-stage process. The specific details of this system are described below.

[2090] Entering user information

[2091] Users log in to the service using their smartphones and enter data such as their income, expenses, dietary restrictions, and health goals. This information is sent from the device to the server in JSON format.

[2092] Analysis of information and suggestions

[2093] The server stores the received data in a database and analyzes it using specific natural language processing and generative AI models. Based on the analysis results, it generates meal plans and discount plans that are optimal for the user's financial situation and health information. These proposals are also returned from the server to the device in JSON format.

[2094] Check and select a plan

[2095] The device displays the optimal plan received from the server on the user's screen, and the user can use the UI to select the appropriate one from multiple proposals. Once a selection is made, the information is sent to the server.

[2096] Automatic order generation and dispatch

[2097] The server automatically generates an order based on the selected plan. This process is automated using templates. The generated order is then electronically sent to the partner restaurant or food delivery service, where it is confirmed.

[2098] Delivery tracking and notifications

[2099] The server tracks the order status in real time and records it in a database. Delivery status updates are immediately sent to the user, who can then view the delivery progress in real time via their device.

[2100] Specific examples

[2101] For example, suppose a user inputs their income of ¥300,000, expenses of ¥200,000, requests a vegetarian meal plan, and a goal of 2,000 calories per day. This information is sent to the server and analyzed by the generative AI model. The optimal meal plan A and discount plan B are suggested, and the user selects meal plan A. The server then generates an order based on the suggestions and sends it to the partner restaurant.

[2102] Prompt Sentence Examples

[2103] An example of a prompt sentence to be input to the generative AI model is as follows:

[2104] Suppose a user has an income of ¥300,000, expenses of ¥200,000, is a vegetarian, and is aiming for 2,000 calories per day. What meal plan would you suggest?

[2105] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2106] Step 1:

[2107] Entering user information

[2108] A user logs into the service using a smartphone and enters data such as their income, expenses, dietary restrictions, and health goals. This data is encoded in JSON format and sent from the device to the server. Examples of input data include income of 300,000 yen, expenses of 200,000 yen, being a vegetarian, and 2,000 calories per day. The device collects this data and prepares it for further processing.

[2109] Step 2:

[2110] Receiving and storing information on the server side

[2111] The server receives the JSON data sent from the device and stores it in a database. At this point, the server checks the data for consistency and cleans it if necessary. The data received includes income, expenses, dietary restrictions, and health goals. The consistency check includes checking for missing fields and data format.

[2112] Step 3:

[2113] Analysis using natural language processing and AI models

[2114] The server inputs the stored data into a natural language processing model and a generative AI model for analysis. Data processing involves standardizing numerical data such as income and expenses, and vectorizing text data such as dietary restrictions and health goals. Based on this, optimal meal plans and discount plans are generated for the user. An example of a prompt input to the generative AI model is, "Please suggest a meal plan for the user whose income is 300,000 yen, expenses are 200,000 yen, and the user is a vegetarian, aiming for 2,000 calories per day."

[2115] Step 4:

[2116] Generate and return a plan

[2117] Based on the analysis results, the server creates optimal meal plans and discount plans and returns them to the device in JSON format, including plan details, price information, calorie information, etc. Specifically, meal plan A (price 3,000 yen, 2,000 calories) and discount plan B (10% discount coupon) are generated.

[2118] Step 5:

[2119] Check and select a plan

[2120] The device displays the plan information received from the server to the user. The user can select the most suitable plan from multiple proposals on the screen. For example, if the user selects meal plan A, that information is sent from the device to the server. The device reflects this information in the UI, which is designed to be easy for the user to use.

[2121] Step 6:

[2122] Automatic order generation and dispatch

[2123] The server automatically generates an order based on the selected plan and electronically transmits it to the partner restaurant or food delivery service. In this process, the order information is formatted based on a template. Specifically, an order based on meal plan A is generated and transmitted to the partner restaurant.

[2124] Step 7:

[2125] Delivery tracking and notifications

[2126] The server tracks the delivery status of the generated order in real time and records it in a database. Status updates are instantly sent to the user, who can view the progress via their device. Delivery information is displayed as a status such as "on delivery" or "received."

[2127] Through this multi-step process, the system suggests a meal plan that suits the user's financial and health situation, and then automatically generates an order and tracks the delivery status.

[2128] 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.

[2129] As an embodiment of the present invention, we provide a system that proposes optimal subsidies and insurance plans based on a user's financial situation and treatment information, automates the application process, and recognizes the user's emotions and adjusts the proposals and support content based on those emotions.

[2130] System Overview

[2131] The system is mainly composed of a server, terminals, and users, and it proposes and processes applications for subsidies and insurance plans for users through a multi-step process. It also uses an emotion engine to recognize users' emotions and optimize the process accordingly.

[2132] Entering and submitting user information

[2133] 1. Users

[2134] Users log in to the service and provide information such as their income, expenses, treatment details, and treatment duration, and also input their emotional state or have it automatically detected through facial recognition and voice analysis.

[2135] 2. Terminal

[2136] The terminal collects the economic information and emotional data entered by the user, converts it into JSON format, and sends it to the server.

[2137] Receiving and storing information

[2138] 3. Server

[2139] The server receives the user information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[2140] Analyzing information and emotions and proposing plans

[2141] 4. Server

[2142] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[2143] 5. Server

[2144] Based on the generated analysis results and sentiment evaluation results, a list of the most suitable subsidy and insurance plans for the user is generated. Based on the results of the sentiment engine, the priority of the proposed plans is adjusted.

[2145] 6. Server

[2146] Sends the list of generated plans to the terminal in JSON format.

[2147] View and review your plan

[2148] 7. Terminal

[2149] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[2150] 8. Users

[2151] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[2152] 9. Terminal

[2153] The device generates and sends an API request to notify the server of the user's plan selection.

[2154] Automatic document generation

[2155] 10. Server

[2156] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[2157] 11. Server

[2158] Save the generated document in a database or file storage and generate a preview link for the user.

[2159] 12. Server

[2160] The generated preview link is sent to the user's device.

[2161] Start the application process

[2162] 13. Users

[2163] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[2164] 14. Terminal

[2165] The terminal generates and sends an API request to notify the server of the operation to start the application.

[2166] Document delivery and tracking

[2167] 15. Server

[2168] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[2169] 16. Server

[2170] Delivery status is tracked in real time and recorded in a database.

[2171] Notification of delivery and receipt status

[2172] 17. Terminal

[2173] Users will be able to see the status of their shipments in real time through an updated dashboard.

[2174] 18. Server

[2175] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[2176] 19. Terminal

[2177] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[2178] Specific examples

[2179] For example, suppose a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user's stress level is high. This information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A and insurance plan B are proposed, and special assistance plan C is also added depending on the user's stress level. The user selects insurance plan B, and the server generates application documents based on this and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[2180] In this way, the system can provide optimal assistance quickly and efficiently, taking into account the user's emotional state, while reducing the user's financial burden. This process allows users to complete complex procedures with minimal effort and also provides psychological support.

[2181] The processing flow will be explained below.

[2182] Program processing flow

[2183] Entering user information and emotion data

[2184] Step 1:

[2185] User:

[2186] Users log in via a web browser or application and enter detailed information such as income, expenses, treatment details, and treatment duration. In addition, the user's emotional state can be entered or automatically detected using facial recognition and voice analysis.

[2187] Step 2:

[2188] Device:

[2189] The device converts the input economic information and sentiment data into JSON format and generates a request to send to the specified API endpoint.

[2190] Receiving and storing information

[2191] Step 3:

[2192] server:

[2193] The server receives the user's economic information and emotion data sent from the terminal and temporarily stores them in memory or intermediate data storage.

[2194] Analyzing information and emotions and generating plans

[2195] Step 4:

[2196] server:

[2197] The server passes the stored information to natural language processing and generative AI models for analysis, and also inputs emotional data into an emotion engine to evaluate the user's emotional state.

[2198] Step 5:

[2199] server:

[2200] Based on the analysis results and sentiment evaluation results, a list of subsidies and insurance plans that are best suited to the user is generated. The results of the sentiment engine are used to adjust the priority of the proposed plans.

[2201] Step 6:

[2202] server:

[2203] The list of generated plans is sent to the terminal in JSON format.

[2204] View and review your plan

[2205] Step 7:

[2206] Device:

[2207] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select the plan.

[2208] Step 8:

[2209] User:

[2210] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[2211] Step 9:

[2212] Device:

[2213] The device generates and sends an API request to notify the server of the user's plan selection.

[2214] Automatic document generation

[2215] Step 10:

[2216] server:

[2217] The server automatically generates the necessary application documents based on the selected plan, using templates to fill in the necessary information.

[2218] Step 11:

[2219] server:

[2220] Save the generated document in a database or file storage and generate a preview link for the user.

[2221] Step 12:

[2222] server:

[2223] The generated preview link is sent to the user's device.

[2224] Start the application process

[2225] Step 13:

[2226] User:

[2227] Users can click on the preview link sent to check the documents, and if there are no problems, click the "Start application" button.

[2228] Step 14:

[2229] Device:

[2230] The terminal generates and sends an API request to notify the server of the operation to start the application.

[2231] Document delivery and tracking

[2232] Step 15:

[2233] server:

[2234] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[2235] Step 16:

[2236] server:

[2237] Delivery status is tracked in real time and recorded in a database.

[2238] Notification of delivery and receipt status

[2239] Step 17:

[2240] Device:

[2241] Users will be able to see the status of their shipments in real time through an updated dashboard.

[2242] Step 18:

[2243] server:

[2244] The status of application documents will also be checked regularly, and the latest status will be obtained and recorded in the database.

[2245] Step 19:

[2246] Device:

[2247] The latest acceptance status will be reflected on the user's dashboard and notifications will be provided.

[2248] Specific examples

[2249] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy treatment, and the emotion engine detects that the user also has a high stress level, this information and emotion data will be sent to the server.

[2250] Information and emotion data analysis

[2251] The server performs analysis using a generative AI model and generates the optimal subsidy plan A and insurance plan B. The emotion engine evaluates the stress level as high and also suggests special support plan C.

[2252] Select a plan and generate documents

[2253] The user checks the plans on the terminal and selects insurance plan B. The server automatically generates application documents based on that and sends them to the insurance company.

[2254] Track delivery and receipt status

[2255] The server tracks the delivery status of the generated document in real time and notifies the user of that information. The server also tracks the receipt status and notifies the user.

[2256] In this way, the system can reduce the user's financial burden and provide optimal assistance quickly and efficiently, taking into account their emotional state. This process allows users to complete complex procedures with minimal effort and also receive psychological support.

[2257] Example 2

[2258] 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."

[2259] In modern society, it is extremely complicated for individuals to select and apply for the most suitable subsidy or insurance plan. Furthermore, there is no system that provides optimal recommendations that take into account each individual's emotional state. Therefore, an effective system is needed to reduce the individual's financial burden and psychological stress at the same time.

[2260] 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.

[2261] In this invention, the server includes: means for receiving personal financial situation and treatment information such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for detecting the user's emotional state and evaluating it based on the analysis results; means for proposing optimal subsidies and insurance plans for the individual based on the analysis results and emotional evaluation results; means for automatically generating documents required for application according to the proposed subsidies and insurance plans; and means for sending the generated documents to a predetermined institution and tracking the delivery status. This enables individuals to complete complex procedures with minimal effort and also receive psychological support by receiving optimal suggestions based on their emotional state.

[2262] "Income" refers to the money or assets that an individual receives over a period of time.

[2263] "Expenditure" refers to the money or assets an individual uses for consumption or obligations over a period of time.

[2264] "Treatment content" refers to the medical procedures and treatment methods an individual receives, including details thereof.

[2265] "Treatment period" refers to the period during which a particular medical procedure or treatment method is performed.

[2266] "Personal economic situation" refers to information that comprehensively represents an individual's financial situation, such as income, expenses, assets, and loans.

[2267] "Treatment information" refers to detailed information about medical treatment an individual receives, including the content and duration of treatment.

[2268] A "natural language processing model" refers to an algorithm or program designed to analyze and understand the meaning of natural language text.

[2269] A "generative AI model" refers to an algorithm or program that uses machine learning techniques to analyze data and generate new information or suggestions.

[2270] "Emotional state" refers to an individual's psychological state, including stress level and type of emotion.

[2271] A "grant" is financial support provided by a government or institution for a specific purpose or under specific conditions.

[2272] "Insurance Plan" means a plan that includes a set of services or coverages offered by an insurance company.

[2273] "Application" refers to the official documentation required to apply for a grant or insurance plan.

[2274] "Authorized institutions" refer to official organizations, such as government agencies or insurance companies, that accept applications for grants or insurance.

[2275] "Delivery status" refers to the process and status of application documents from the time they are sent to the designated institution until they are accepted.

[2276] As an embodiment of the present invention, a system comprising a server, a terminal, and a user is provided. A specific implementation method will be described below.

[2277] The system begins with the user entering personal financial and medical information, such as income, expenses, treatment details, and treatment duration. The user enters this information through a dedicated terminal application. The user's emotional state can also be entered manually or automatically detected using a facial recognition camera or voice analysis.

[2278] The terminal collects the economic and sentiment data entered by the user and converts this information into JSON format, which is then sent to the server using the HTTPS protocol.

[2279] The server receives the user information and emotion data sent from the device and temporarily stores it in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[2280] The stored data is passed to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis. This analysis deciphers the user's medical information and financial situation and identifies appropriate subsidies and insurance plans. At the same time, emotion data is passed to an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[2281] The server combines the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user, which is then sent to the device in JSON format.

[2282] The device displays the list of plans received from the server to the user and provides an interface for the user to select. The user selects the most suitable plan from the displayed plans and clicks the confirmation button. The device generates and sends an API request to notify the server of the selection.

[2283] The server automatically generates the documents required for application based on the plan selected by the user. A template engine (e.g., Handlebars.js) is used to generate the documents, embedding the user's required information. The generated documents are saved in a database (e.g., PostgreSQL) or file storage (e.g., Amazon S3).

[2284] After the document is generated, the server sends a preview link to the user. The user checks this preview link and, if there are no problems, clicks the "Start application" button. This operation causes the device to generate an API request to start the application and send it to the server.

[2285] The server routes the documents to the appropriate authority (insurance company, government agency). The delivery status is tracked in real time and recorded in a database. The delivery status and receipt status are checked periodically, and the latest information is updated on the user's dashboard.

[2286] The above processing flow builds a system that provides optimal support based on the user's emotional state while reducing the user's financial burden.

[2287] Specific examples

[2288] For example, if a user inputs information such as income of 300,000 yen, expenses of 200,000 yen, and a six-month course of chemotherapy, and the emotion engine detects a high stress level, the information and emotion data are sent to the server and analyzed by the generative AI model. The optimal subsidy plan A, insurance plan B, and special needs plan C are then proposed. The user selects insurance plan B, and the server generates application documents based on that and sends them to the insurance company. The server then tracks the delivery and acceptance status in real time and notifies the user.

[2289] Prompt Sentence Examples

[2290] My income is 300,000 yen, my expenses are 200,000 yen, I'm undergoing chemotherapy treatment for 6 months, and my stress level is high. Please suggest the best subsidy and insurance plan.

[2291] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2292] Step 1:

[2293] Users log in to the system and enter information such as their income, expenses, treatment details, and treatment duration, as well as their emotional state, which can be entered manually or automatically detected through facial recognition cameras and voice analysis.

[2294] Input: User's income, expenses, treatment details, treatment duration, emotional state

[2295] Output: Collected personal information and emotional data

[2296] Step 2:

[2297] The terminal receives the economic and emotional data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[2298] Input: User's financial information and emotional data

[2299] Output: Data converted to JSON format

[2300] Step 3:

[2301] The server receives the user information and emotion data sent from the device and temporarily stores them in memory or in intermediate data storage on a database, such as MongoDB or Redis.

[2302] Input: User information and emotion data in JSON format

[2303] Output: Data stored in the database

[2304] Step 4:

[2305] The server passes the stored data to natural language processing models (e.g., BERT) and generative AI models (e.g., OpenAI's GPT) for data analysis, and inputs emotional data into an emotion engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state.

[2306] Input: User information and emotion data stored in the database

[2307] Output: Analysis results and emotion evaluation results

[2308] Step 5:

[2309] The server integrates the analysis results output by the generative AI model with the evaluation results of the emotion engine to generate a list of optimal subsidies and insurance plans for the user. It also adjusts the priority of the plans based on the evaluation results of the emotion engine.

[2310] Input: Analysis results and emotion evaluation results

[2311] Output: List of best subsidies and insurance plans

[2312] Step 6:

[2313] The server sends the list of generated plans to the terminal in JSON format.

[2314] Input: List of best subsidies and insurance plans

[2315] Output: Plan list in JSON format

[2316] Step 7:

[2317] The terminal displays the list of plans received from the server to the user and provides an interface from which the user can select.

[2318] Input: Plan list in JSON format

[2319] Output: User selectable Show Plan interface

[2320] Step 8:

[2321] The user selects the most suitable plan from the displayed plans and clicks the confirmation button.

[2322] Input: Show Plan interface

[2323] Output: User's plan selection

[2324] Step 9:

[2325] The device generates and sends an API request to notify the server of the user's plan selection.

[2326] Input: User's plan selection

[2327] Output: API request

[2328] Step 10:

[2329] The server automatically generates the necessary application documents based on the selected plan. It uses a template engine (e.g., Handlebars.js) to create the application documents by embedding the necessary user information.

[2330] Input: User's plan selection

[2331] Output: Auto-generated application documents

[2332] Step 11:

[2333] The server stores the generated document in a database or file storage and generates a preview link for the user.

[2334] Input: Auto-generated application documents

[2335] Output: Preview link

[2336] Step 12:

[2337] The server sends the generated preview link to the user's terminal.

[2338] Input: Preview link

[2339] Output: Preview link sent to your device

[2340] Step 13:

[2341] The user clicks on the preview link sent to check the documents, and if there are no problems, clicks the "Start application" button.

[2342] Input: Preview link

[2343] Output: Application start operation

[2344] Step 14:

[2345] The terminal generates and sends an API request to notify the server of the operation to start the application.

[2346] Input: Start application operation

[2347] Output: API request

[2348] Step 15:

[2349] The server sends the documents to the appropriate authority (insurance company, government agency) via email or an online application form.

[2350] Input: API request and application documents

[2351] Output: Documents sent

[2352] Step 16:

[2353] The server tracks the document delivery status in real time and records it in a database.

[2354] Input: Documents sent

[2355] Output: Record of document delivery status in database

[2356] Step 17:

[2357] The device provides a dashboard so users can check delivery status in real time.

[2358] Input: Document delivery status data

[2359] Output: Real-time updated dashboard

[2360] Step 18:

[2361] The server periodically checks the acceptance status of the application documents, obtains the latest acceptance status, and records it in the database.

[2362] Input: Application acceptance status

[2363] Output: Record of acceptance status in database

[2364] Step 19:

[2365] The terminal reflects the latest acceptance status provided by the server on the dashboard and provides a notification to the user.

[2366] Input: Acceptance status data

[2367] Output: Updated dashboard and notification to the user

[2368] (Application example 2)

[2369] 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."

[2370] Existing subsidy and insurance plan recommendation systems suggest optimal plans based on the user's financial information, but do not take into account the user's emotional state, resulting in a lack of appropriate support under stressful circumstances. Furthermore, there is a risk that users may send incorrect information during times of high stress, leading to problems with insufficient financial burden reduction and psychological support.

[2371] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for accepting an individual's financial situation and treatment information, such as income, expenses, treatment content, and treatment period; means for analyzing the information using a specific natural language processing model and a generative AI model; means for proposing the optimal subsidy or insurance plan for the individual based on the analysis results; means for automatically generating documents required for application according to the proposed subsidy or insurance plan; means for sending the generated documents to a specified institution and tracking the delivery status; means for proposing and implementing optimal security measures based on the user's financial situation and emotional state; and means for recognizing the user's emotional state in real time and adjusting the proposed content. This makes it possible to provide appropriate support that takes into account the user's emotional state, while simultaneously implementing security measures such as preventing erroneous transmissions during times of high stress.

[2372] "Income" is the total amount of money, or value that can be converted into money, that an individual receives over a given period of time.

[2373] "Expenditure" is the total amount of money an individual uses for living and business purposes.

[2374] "Treatment content" refers to details such as the specific treatment procedures and methods used at medical institutions, as well as the medicines and equipment used.

[2375] "Treatment period" refers to the entire period required to receive a given treatment.

[2376] "Personal financial situation" refers to a person's financial stability and health based on income, expenses, assets, liabilities, etc.

[2377] A "natural language processing model" is a model that uses algorithms and techniques to enable computers to understand and analyze human language.

[2378] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to automatically generate new information or suggestions from data.

[2379] A "grant" is financial assistance provided by governments or other organizations to individuals or organizations that meet certain criteria.

[2380] "Insurance plan" refers to the types and terms of a contract offered by an insurance company to provide coverage against certain risks.

[2381] "Automatic document generation" is the process of using templates and predefined data to automatically fill in the necessary information and create a document in a predetermined format.

[2382] "Emotional state" refers to an individual's current feelings or mental state.

[2383] "Security measures" is a general term for measures and actions taken to protect individuals and systems from various risks and threats.

[2384] "Real time" refers to the ability to process and display ongoing situations and events instantly, with minimal delay.

[2385] To implement this invention, a system is required that proposes optimal subsidies, insurance plans, and security measures based on the user's financial situation and emotional state, and automates the application process. The system is primarily composed of a server, terminals, and users, and provides optimal support to users through a multi-stage process.

[2386] Hardware and software used

[2387] Hardware

[2388] Smart glasses: Equipped with a face recognition camera, voice recognition microphone, high-performance processor, and Wi-Fi module

[2389] Server: High-performance computer system

[2390] software

[2391] AWS Lambda: Used for serverless computation to process economic and sentiment data of users.

[2392] Amazon S3: For temporary data storage.

[2393] Amazon Rekognition: A facial recognition engine for emotion recognition.

[2394] Google Dialogflow: A natural language processing engine for interacting with users.

[2395] JSON format: Used for sending and receiving data.

[2396] System Operation

[2397] 1. Collection and Input

[2398] Users use the smart glasses to input their income, expenses, treatment details, and treatment duration, and the glasses also use a facial recognition camera and voice recognition microphone to recognize and collect data on the user's emotional state in real time.

[2399] 2. Data transmission

[2400] The collected data is converted into JSON format and sent to a server, which receives the data and temporarily stores it in Amazon S3.

[2401] 3. Data Analysis

[2402] Amazon Rekognition is used to analyze the collected sentiment data, and AWS Lambda then sends the analyzed economic and sentiment information to Google Dialogflow, which analyzes and generates optimal subsidies, insurance plans, and security measures.

[2403] 4. Proposing plans and measures

[2404] Based on the analysis results, the system will propose optimal plans and measures to the user, which will be sent to the user via smart glasses and can be viewed in real time.

[2405] 5. Real-time notification and action

[2406] Once the user selects a proposed plan or measure, the smart glasses transmit the selection to the server, which then automatically generates the appropriate application documents and sends them to the designated authority. The server also implements specific security measures (e.g., suspending transmissions) depending on the user's stress level.

[2407] Specific examples

[2408] For example, if a user enters information such as income of ¥300,000, expenses of ¥200,000, and six months of chemotherapy treatment, and the emotion engine detects high stress levels, the following prompt will be generated:

[2409] "Given your recent emotional state, we recommend temporarily suspending transmissions to avoid sending erroneous information during high stress situations. Would you like to cease transmissions?"

[2410] In this way, the system can quickly and efficiently provide optimal assistance that takes into account the user's emotional state, while reducing the user's financial burden.

[2411] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2412] Step 1:

[2413] The user uses the smart glasses to input their income, expenses, treatment details, and treatment duration. The smart glasses' facial recognition camera and voice recognition microphone detect and collect the user's emotional state in real time. Specifically, the user enters financial information (income, expenses, etc.), treatment information, as well as facial and voice data. This data is necessary for use in subsequent analysis steps.

[2414] Step 2:

[2415] The device (smart glasses) converts the collected economic information and emotion data into JSON format and sends it to the cloud server. This operation formats the raw data and converts it into a format that is easy for the server to receive.

[2416] Step 3:

[2417] The server temporarily stores the user information and emotion data sent from the device in JSON format in Amazon S3, making the data easily accessible for subsequent processing steps.

[2418] Step 4:

[2419] The server analyzes the stored data using AWS Lambda. First, it inputs the facial recognition data into Amazon Rekognition to perform a detailed analysis of the user's emotional state. This outputs the user's stress level and emotional state as numerical data.

[2420] Step 5:

[2421] AWS Lambda analyzes the economic information and sentiment data and sends it to Google Dialogflow, which uses natural language processing to generate optimal subsidies, insurance plans, and security measures. This results in a list of generated subsidy plans, insurance plans, and security measures.

[2422] Step 6:

[2423] The server uses a generative AI model to generate a list of optimal subsidies and insurance plans for each user based on the analysis and sentiment evaluation results, and adjusts priorities based on sentiment data. The generated results are then converted into JSON format.

[2424] Step 7:

[2425] The server sends the generated plan list in JSON format to the device. The device (smart glasses) visualizes and displays the plan list received from the server to the user. The user can select the most appropriate plan from the multiple plans presented.

[2426] Step 8:

[2427] Based on the plan selected by the user, the device will send an API request back to the server, which will receive the selection and automatically execute the steps to start the application process.

[2428] Step 9:

[2429] The server automatically generates the necessary application documents based on the selected plan. This process uses templates to generate documents with the user's information embedded. The server then sends the automatically generated documents to the designated institution via email or an online application form.

[2430] Step 10:

[2431] The server tracks the delivery status in real time and records the progress in a database, which is then periodically updated on the user's device.

[2432] Step 11:

[2433] Users can check the delivery status in real time using the smart glasses. In addition, the server periodically checks whether the application has been accepted and notifies the device of the latest status.

[2434] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2435] 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.

[2436] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2437] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2438] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2439] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2440] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2441] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approa...

Claims

1. A means of accepting personal financial and medical information, such as income, expenses, treatment details, and treatment duration; A means for analyzing using a specific natural language processing model and a generative AI model; A method to propose optimal subsidies and insurance plans for individuals based on the analysis results, and A means to automatically generate application documents according to proposed grants and insurance plans; a means for sending the generated document to a predetermined institution and tracking the status of the delivery; A system including:

2. A means for the user to select any plan from the plans presented and automatically start the application procedure based on the selection; The system of claim 1 , comprising:

3. A means to track the status of documents received after application procedures in real time and notify users; The system of claim 1 , comprising:

Images