System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to enter information into an input form using a smart device; means for transmitting information collected from the input form to a server; means for the server to analyze the collected information and generate a list of required preparations using a generative model; and means for displaying the generated list of preparations on the user's smart device.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] This system aims to solve the problem that smart device users have difficulty in understanding in advance the documents and preparations required for certain procedures, such as changing the name or plan. This problem leads to users realizing after visiting the store that they are missing an item, which results in double effort, and having to return to the store. Furthermore, even when searching for information online, users often cannot find the appropriate information. This creates the challenge of being unable to proceed with the procedure efficiently. [Means for solving the problem]

[0005] The present invention provides a means for a user to input information into an input form using a smart device and send the information collected from the input form to a server. The server further includes a means for analyzing the collected information and generating a list of necessary preparations using a generative model. The generated list of preparations is displayed on the user's smart device, allowing the user to understand what is needed in advance and make preparations. The present invention provides a highly accurate preparation list by utilizing a generative model that employs natural language processing technology. The input form also includes multiple input fields for information such as name, age, and type of change, allowing the user to easily enter information. This allows the user to efficiently make the necessary preparations.

[0006] "User" refers to an individual who uses the system to enter their information and obtain a list of necessary supplies.

[0007] "Smart devices" refers to electronic devices such as mobile phones, tablets, and computers that can connect to the Internet.

[0008] An "input form" refers to an interface with multiple input fields on a web page for a user to enter specific information.

[0009] "Information" means data provided by the user through the input form, specifically including personal data such as name, age, type of change, etc.

[0010] "Server" refers to a computer system for receiving, analyzing, and processing information sent by users.

[0011] "Collected Information" refers to all data entered by the user into the input form and sent to the server.

[0012] "Generative model" refers to an algorithm or program that uses natural language processing technology to generate a list of necessary preparations based on input information.

[0013] "Preparation List" refers to a list of documents and other preparations required by a User to carry out a specific procedure.

[0014] "Means for displaying" refers to the general mechanism for displaying the preparation list generated by the server on the user's smart device.

[0015] "Natural language processing technology" refers to the technology used by computers to understand, generate, and analyze human language.

[0016] "Input Field" means a separate area in an input form where a user enters information. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] System Overview

[0039] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. Users input information into an input form using a smart device, and a list of necessary items is generated and displayed based on that information. Each processing step and specific examples are described in detail below.

[0040] System configuration

[0041] This system mainly consists of the following elements:

[0042] 1. Terminal (user's smart device):

[0043] Displays a form for users to enter information.

[0044] The entered information is sent to the server.

[0045] 2. Server:

[0046] Receive information sent by users.

[0047] The information is analyzed and a generative model is used to generate a list of necessary preparations.

[0048] The generated preparation list is sent back to the user's smart device.

[0049] 3. Generative Model:

[0050] An algorithm that uses natural language processing technology to generate the optimal preparation list based on the information entered by the user.

[0051] Program processing details

[0052] 1. Submitting the input form and entering information

[0053] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[0054] User: Enter the required information into the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[0055] 2. Sending input data

[0056] On the device: When the submit button on the form is clicked, the user's input data is converted to JSON format and sent to the server as a POST request.

[0057] 3. Data reception and analysis by the server

[0058] Server: Parses the received JSON data and obtains the user's input information. This information is passed to the generative model to generate a list of necessary preparations.

[0059] 4. Running the Generative Model

[0060] Generative model: Using natural language processing technology, the system generates an optimal list of items to prepare based on information provided by the user. For example, it includes specific information such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0061] 5. Return and display of preparation list

[0062] Server: Returns the generated preparation list to the user's smart device.

[0063] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[0064] Specific examples

[0065] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0066] 2. The device converts the input information into JSON format and sends it to the server.

[0067] 3. The server analyzes the received data and uses a generative model to generate a list of documents required for the name change: driver's license, resident registration card, seal certificate, etc.

[0068] 4. The server returns the generated list of preparations to the user's terminal.

[0069] 5. The device will display the returned list on the screen, making it easier for users to prepare in advance.

[0070] conclusion

[0071] The present invention provides an effective means for users to know in advance what documents and preparations are required when carrying out a specific procedure, thereby enabling users to make efficient preparations and smoothly proceed with the procedure.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[0075] Step 2:

[0076] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[0077] Step 3:

[0078] Terminal: When the user clicks the submit button on the form, JavaScript (registered trademark) is used to collect the form data and convert it into JSON format. This JSON data is then sent to the server as a POST request.

[0079] Step 4:

[0080] Server: Parse the received POST request and extract the JSON data. From the parsed data, get the user information such as name, age, and type of change.

[0081] Step 5:

[0082] Server: Based on the acquired user information, it passes appropriate prompts to the generative model, which uses natural language processing techniques to generate a list of items to be prepared.

[0083] Step 6:

[0084] Generative model (on the server): The generative model uses natural language processing technology to generate a list of items to prepare based on the input information. For example, it generates content such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0085] Step 7:

[0086] Server: Receives the generated list of preparations, converts it to JSON format, and returns it to the terminal.

[0087] Step 8:

[0088] On the device: Receive the JSON data returned from the server and parse it using JavaScript. Get the list of preparations from the parsed data and display it on the user's device.

[0089] Step 9:

[0090] User: Check the list of items to prepare displayed on the device and prepare the necessary documents and items in advance, which will help the process go smoothly.

[0091] Example 1

[0092] 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."

[0093] When users go through procedures, it is difficult to know in advance what documents and preparations are required, which can cause the procedures to not proceed smoothly. In addition, insufficient preparations often result in duplicate work, making the procedures inefficient. This increases the burden on users.

[0094] 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.

[0095] In this invention, the server includes: means for a user to input information into an input form using a mobile information terminal; means for transmitting information collected from the input form to a processing device; means for the processing device to analyze the collected information and generate a list of necessary preparations using a generative AI model; means for the processing device to display the generated list of preparations on the user's mobile information terminal; and means for the generative AI model to generate the list of preparations using a prompt sentence for the server. This allows the user to efficiently grasp in advance the preparations required when performing a procedure, making it possible to smoothly proceed with the procedure and avoiding duplicate work.

[0096] A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, that a user uses to input and display information.

[0097] An "input form" is an interface through which a user enters information, and includes input fields such as name, age, type of change, etc.

[0098] A "processing device" is a device, such as a server, that receives and analyzes the data sent by the user and generates the required preparation list using a generative AI model.

[0099] A "generative AI model" is an algorithm or artificial intelligence model that uses natural language processing technology to generate an optimal preparation list based on information provided by the user.

[0100] A "prompt" is an instruction input to a generative AI model, and is text that specifically requests a list of necessary preparations based on the user's input information.

[0101] A "preparation list" is a list of documents and other items that a user needs to carry out a specific procedure.

[0102] "Analyzing information" is the process of understanding, categorizing, and converting user-entered data into a usable format.

[0103] "Collected Information" refers to data provided by users through input forms.

[0104] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. This system is primarily composed of a mobile information terminal, a processing device (server), and a generative AI model. Below, we provide a detailed explanation and specific examples of each element.

[0105] System Overview

[0106] A user uses a mobile information terminal (such as a smartphone or tablet) to input information into an input form. The input form contains multiple input fields, such as name, age, and type of change, and the user enters this information. Once the user has completed the input, the terminal converts the input information into JSON format and sends it to a processing device.

[0107] Hardware and software used

[0108] 1. Personal digital assistant: A device used by a user to enter and display information, such as a smartphone or tablet.

[0109] 2. Processing device (server): Responsible for receiving data, analyzing it, processing it using a generative AI model, and sending a response. Specifically, a server-side framework such as Express.js is used.

[0110] 3. Generative AI model: An algorithm that uses natural language processing technology to generate a preparation list. The generative AI model generates the optimal preparation list based on the prompt sentence.

[0111] Specific operation of the system

[0112] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0113] 2. The device converts the input information into JSON format and sends it to the processing device, which then sends the input data to the server.

[0114] 3. The server parses the received data and extracts the user's input, including data such as name, age, and type of change.

[0115] 4. The server uses the generative AI model to create a prompt based on the user's input. An example prompt might look like this:

[0116] "Please list the necessary preparations according to the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[0117] 5. The generative AI model generates an optimal list of items to prepare based on the prompt. Specifically, it generates a list such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0118] 6. The server returns the generated list of preparations to the user's device. The returned list is sent as a JSON response.

[0119] 7. The terminal analyzes the received preparation list and displays it on the screen of the user's smart device. The user can refer to this list and prepare the necessary documents in advance.

[0120] This system allows users to efficiently understand in advance what preparations they need to make when carrying out a procedure, allowing the procedure to proceed smoothly and avoiding duplicate work.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] Step 1:

[0123] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains several input fields such as name, age, and type of change.

[0124] Input: User accesses the browser.

[0125] Output: The input form is displayed in the browser.

[0126] Step 2:

[0127] User: Enter the required information in the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[0128] Input: Name, Age, Change Type information.

[0129] Output: User enters information into a form.

[0130] Step 3:

[0131] On the device: When you click the submit button on the form, JavaScript triggers this event, converting the input data into JSON format, which is then sent to the server as a POST request.

[0132] Input: User presses submit button.

[0133] Output: JSON formatted data is generated and sent to the server.

[0134] Step 4:

[0135] Server: Receives JSON format data sent from the device.

[0136] Input: JSON data from the terminal.

[0137] Output: The received data.

[0138] Step 5:

[0139] Server: Parses the received JSON data and extracts the user's input information, such as name, age, and type of change.

[0140] Input: The received JSON data.

[0141] Output: The extracted user information.

[0142] Step 6:

[0143] Server: Creates a prompt for the generative AI model based on the user's input. Specifically, it would say something like, "Please list the necessary preparations based on the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[0144] Input: Extracted user information.

[0145] Output: The generated prompt statement.

[0146] Step 7:

[0147] Generative AI model: Analyzes the prompt and generates a list of the necessary documents. For example, it generates "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0148] Input: prompt statement.

[0149] Output: The generated preparation list.

[0150] Step 8:

[0151] Server: Receives the generated list of preparations and returns it to the terminal as a response in JSON format.

[0152] Input: The generated preparation list.

[0153] Output: Response in JSON format.

[0154] Step 9:

[0155] Terminal: Analyzes the received JSON format preparation list and displays it on the screen of the user's smart device.

[0156] Input: The JSON response from the server.

[0157] Output: A list of preparations will be displayed on the screen.

[0158] (Application example 1)

[0159] 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."

[0160] In today's diverse procedures, users are required to know in advance what documents and items they need and prepare them efficiently. However, with conventional methods, users often spend a significant amount of time and effort checking what items they need, which causes the process at the store to take longer. To solve this problem and allow users to prepare efficiently, a system that automatically generates and provides a list of items to be prepared is needed.

[0161] 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.

[0162] In this invention, the server includes means for a user to input information into an input form using an information processing terminal, means for transmitting information collected from the input form to a data analysis device, means for the data analysis device to analyze the collected information and generate a list of necessary preparations using natural language processing technology, means for displaying the generated list of preparations on the user's information processing terminal, and means for providing a list of preparations necessary for procedures at a physical store based on the information input by the user. This enables the user to know in advance the documents and preparations they will need and to make efficient preparations.

[0163] An "information processing terminal" is a device that allows a user to input information and communicate with a server.

[0164] "Data analysis device" refers to a device for analyzing collected information and generating a preparation list.

[0165] "Natural language processing technology" refers to the technology that allows computers to understand and generate human language.

[0166] A "preparation list" is a list of documents and items required to carry out a specific procedure.

[0167] A "question answer generation algorithm" is an algorithm for generating the optimal answer to an input question.

[0168] A "field" is an item on an input form where a user enters specific information.

[0169] "Name" means the name of the User.

[0170] "Procedure type" is an item that indicates the type of specific procedure that the user is going to perform.

[0171] This invention provides a system for efficiently preparing documents and items required for a specific procedure. In this system, a user inputs information into a form using an information processing terminal, the data is sent to a server, analyzed, and a generative model is used to generate and display a list of necessary items. Detailed embodiments are described below.

[0172] System Overview

[0173] The system mainly consists of the following elements:

[0174] 1. Information processing terminal: A device through which a user inputs information and communicates with a server. Specific devices include smartphones, tablets, and PCs.

[0175] 2. Data analysis device: A device that analyzes collected information and generates a list of preparations. Specifically, it is a system built by a server.

[0176] 3. Generative AI model: An algorithm that uses natural language processing technology to generate an optimal preparation list.

[0177] Program Description

[0178] Hardware and Software Use

[0179] Information processing devices (e.g. smartphones, tablets, PCs)

[0180] This is a terminal where users input information and send it to the data analysis device. A browser and dedicated applications are installed on this terminal.

[0181] Data analysis equipment (e.g., server)

[0182] The information sent by the user is analyzed and a preparation list is generated using a generative AI model. The server has a backend system built using Node.js and Express.

[0183] Generative AI models (e.g., GPT-3 (registered trademark), TENSORFLOW (registered trademark))

[0184] This is an algorithm that uses natural language processing technology to generate a list of necessary preparations based on information entered by the user.

[0185] Specific examples of processing

[0186] 1. The user uses the information processing terminal to enter information into the input form. For example, the user selects "name change" as the procedure and enters the user's name and other required items.

[0187] 2. The device converts the input information into JSON format and sends it to the server as a POST request.

[0188] 3. The server analyzes the received data and inputs it as a prompt sentence into the generative AI model.

[0189] 4. The generative AI model generates an optimal preparation list based on the input prompt.

[0190] 5. The server returns the prepared item list to the information processing terminal.

[0191] 6. The information processing terminal displays the received preparation list on the screen and provides it to the user.

[0192] Context and prompt example

[0193] Specific prompt examples:

[0194] Name: Yamada Taro, Procedure: Name change

[0195] This invention allows users to efficiently prepare the documents and materials required for the procedure in advance, thereby shortening the time required for the procedure at a physical store. The above is a detailed description of the embodiment of the present invention.

[0196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0197] Step 1:

[0198] The user uses an information processing terminal to input information into the input form. Specifically, the user enters necessary information such as name and procedure details into the input fields. This information becomes the initial input data for the system.

[0199] Input: Name, procedure details, and other information

[0200] Output: Data entered by the user

[0201] Step 2:

[0202] The terminal converts the information entered by the user into JSON format and sends it to the data analysis device. Specifically, the information entered in the input fields is sent to the server as a POST request.

[0203] Input: Data entered by the user

[0204] Output: JSON format data

[0205] Step 3:

[0206] The server parses the received JSON data and extracts the necessary information. Specifically, it uses Node.js and Express to parse the data and extract the necessary fields (name, procedure details, etc.).

[0207] Input: JSON format data

[0208] Output: Analyzed data (name, procedure details, etc.)

[0209] Step 4:

[0210] The server passes the extracted data to the generative AI model as a prompt sentence. Specifically, it generates a prompt sentence and inputs it into the generative AI model (e.g., GPT-3 or TensorFlow).

[0211] Input: Analyzed data (name, procedure details, etc.)

[0212] Output: prompt statement

[0213] Step 5:

[0214] The generative AI model generates an optimal preparation list based on the prompt sentence. Specifically, it uses natural language processing technology to generate the necessary preparation list and returns it to the server.

[0215] Input: prompt statement

[0216] Output: Preparation list

[0217] Step 6:

[0218] The server returns the created preparation list to the information processing terminal. Specifically, it converts the preparation list into JSON format and returns it as an HTTP response.

[0219] Input: List of preparations

[0220] Output: JSON format list of preparations

[0221] Step 7:

[0222] The information processing terminal displays the received preparation list to the user. Specifically, the preparation list is displayed in an application or web browser so that the user can check it.

[0223] Input: JSON format list of preparations

[0224] Output: A list of preparations that is displayed to the user

[0225] 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.

[0226] System Overview

[0227] This invention is a system that allows users to efficiently prepare documents and other items required for specific procedures by identifying them in advance. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more customized support. Each processing step and specific examples are described in detail below.

[0228] System configuration

[0229] This system mainly consists of the following elements:

[0230] 1. Terminal (user's smart device):

[0231] Displays a form for users to enter information.

[0232] The input information and the user's emotional data are sent to the server.

[0233] 2. Server:

[0234] Receive information and emotional data sent by the user.

[0235] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[0236] The generated preparation list is sent back to the user's smart device.

[0237] 3. Generative Model:

[0238] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user.

[0239] 4. Emotion Engine:

[0240] It has the ability to analyze the user's input and emotional patterns to determine the user's emotional state.

[0241] Program processing details

[0242] 1. Submitting the input form and entering information

[0243] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[0244] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[0245] 2. Acquiring Emotion Data

[0246] Emotion engine: Analyzes emotional patterns from user input to determine the user's emotional state. This emotional data is derived based on the user's typing speed, input content, etc.

[0247] 3. Sending input data and emotion data

[0248] On the device: When you click the submit button on the form, the collected information and analyzed emotion data are converted into JSON format and sent to the server as a POST request.

[0249] 4. Data reception and analysis by the server

[0250] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[0251] 5. Execution of the generative model by the server

[0252] Server: Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotion data, the server generates a customized preparation list.

[0253] 6. Return and display of preparation list

[0254] Server: Returns the generated preparation list to the user's smart device.

[0255] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[0256] Specific examples

[0257] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0258] 2. The emotion engine analyzes the input and detects "stress."

[0259] 3. The device converts the collected information and emotion data into JSON format and sends it to the server.

[0260] 4. The server analyzes the received data and uses a generative model to generate a list of items to prepare, such as "suggested relaxation methods based on emotions" and "documents required for name change: driver's license, resident registration, seal certificate, etc."

[0261] 5. The server returns the generated list to the terminal.

[0262] 6. The device will display the returned list on the screen, making it easier for users to prepare in advance, and will also provide advice based on their emotions.

[0263] conclusion

[0264] The present invention provides an effective means for users to know in advance what documents and preparations are required for a specific procedure. Furthermore, it also recognizes the user's emotional state and provides customized support based on that, thereby improving the user experience. This allows users to prepare efficiently and proceed smoothly through the procedure.

[0265] The processing flow will be explained below.

[0266] Step 1:

[0267] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[0268] Step 2:

[0269] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[0270] Step 3:

[0271] Emotion engine (inside the device): Analyzes the input information and the user's behavioral data while inputting (such as input speed, typing intervals, frequency of errors, etc.) to determine the user's emotional state. For example, if the user makes many errors and the tempo is irregular while inputting, it will be determined that the user is feeling "stressed."

[0272] Step 4:

[0273] On the device: When the user clicks the submit button on the form, JavaScript is used to collect the form data and parsed emotion data, convert them into JSON format, and send them to the server.

[0274] Step 5:

[0275] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[0276] Step 6:

[0277] Server: Based on the acquired user information and emotional data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotional data, the server generates a customized preparation list that takes into account the user's emotional state.

[0278] Step 7:

[0279] Generative model (inside the server): Based on the information entered by the user, the generative model generates a list of necessary preparations, along with additional information based on emotions, such as "preferentially guide people who are feeling stressed through simple procedures."

[0280] Step 8:

[0281] Server: Returns the generated preparation list and emotion-based advice to the user's smart device.

[0282] Step 9:

[0283] Terminal: Receives the JSON data returned from the server, parses it using JavaScript, and displays a list of items to prepare and advice based on the emotion in an HTML document. Specifically, it displays advice such as "Try taking a deep breath to relax" along with "Documents required for name change: driver's license, resident registration, seal certificate, etc."

[0284] Step 10:

[0285] Users can check the preparation list and advice displayed on the device, gather the necessary documents and supplies in advance, or act according to their feelings, making the process smooth and efficient.

[0286] Example 2

[0287] 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."

[0288] Previous systems lacked an efficient way for users to understand in advance what documents and preparations were required when carrying out specific procedures. They also failed to provide appropriate support that took into account the user's emotional state, often causing inconvenience and stress. This led to users being inadequately prepared in advance, resulting in problems with procedures not proceeding smoothly.

[0289] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing collected information and generating a list of necessary preparations using a generative model, means for analyzing emotion data, and means for displaying customized advice based on the generated list of preparations and emotion data on the communication device. This allows the user to know in advance what documents and preparations they need and to receive appropriate support according to their emotional state.

[0290] "User" refers to a person who uses this system to enter the information required for a procedure.

[0291] "Communication device" refers to hardware such as a smart device that a user uses to input information.

[0292] "Input screen" refers to an interface for inputting information that is displayed on the display of a communication device.

[0293] "Collected Information" refers to all data provided by the user through the input screens.

[0294] "Server" refers to a computing system for receiving and analyzing collected information.

[0295] "Analysis" refers to the process of processing the collected information and generating a list of necessary preparations and emotional data.

[0296] "Generative Model" refers to an algorithm that uses natural language processing techniques to generate a list of necessary preparations and customized advice based on sentiment data.

[0297] A "preparation list" refers to a list of documents and items required when carrying out a procedure.

[0298] "Emotional data" refers to data on a user's mental state analyzed from the content and method of input.

[0299] "Customized advice" refers to specific assistance information provided individually based on the user's emotional data and input information.

[0300] The present invention is a system that allows users to efficiently prepare by identifying the documents and preparations required for a specific procedure in advance. It is also possible to analyze the user's emotional state in real time and provide customized support based on their emotions. The following describes the detailed processing content of the program of this system.

[0301] System configuration

[0302] The system mainly consists of the following elements:

[0303] 1. Communication Device (User's Smart Device):

[0304] Displays a screen for the user to enter information.

[0305] The input information and emotion data are sent to the server.

[0306] 2. Server:

[0307] Receive information and emotional data sent by the user.

[0308] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[0309] The generated preparation list is returned to the user's communication device.

[0310] 3. Generative Model:

[0311] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user. Large-scale language models such as GPT-3 can be used as this generation model.

[0312] 4. Emotion Engine:

[0313] It has the ability to analyze the user's input content, input speed, and patterns to determine the user's emotional state. This emotion engine uses emotion analysis models and machine learning algorithms.

[0314] Program processing details

[0315] Submitting the form and entering information

[0316] Communication device: When a user accesses the system, an input screen is displayed in the smart device browser using HTML and JavaScript. This screen contains input fields for identification information, age, type of change, etc.

[0317] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, "Identification information: User A," "Age: 30," "Type of change: Name change," etc. Placeholders and explanations are displayed in each field to make it easier for users to enter information.

[0318] Acquiring emotion data

[0319] Emotion engine: Analyzes user input. It uses input speed, patterns, and linguistic features to determine the user's emotional state using a machine learning model. For example, if the input speed is fast and the sentences are fragmented, it can detect stress.

[0320] Sending input data and emotion data

[0321] Communication device: When the submit button on the form is clicked, the collected information and analyzed emotion data are converted into JSON format and sent as a POST request to the server using a RESTful API.

[0322] Data reception and analysis

[0323] Server: Receives the POST request and checks the data integrity. A server-side program using Python or Node.js (e.g., Flask, Express.js) parses the JSON data and extracts the identity, age, type of change, and emotion data.

[0324] Running the generative model

[0325] Server: Based on the extracted user information and emotion data, the server passes prompts to the generative AI model. For example, a prompt such as "User information: User A, age 30, type of change: name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress state obtained from the emotion data" can be used for the generative AI model (such as GPT-3).

[0326] Generate and return a preparation list

[0327] Server: Receives the customized list of preparations as a response from the generative model, converts it into JSON format, and sends it back to the communication device. Specifically, it includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods according to emotions."

[0328] Displaying the preparation list

[0329] Communication device: Receives the list of items to be prepared returned from the server and displays it on the screen using HTML and JavaScript. Based on this information, users can prepare the items required for the procedure in advance.

[0330] The above is a detailed description of the processing procedure of the system of the present invention. By using this system, users can reduce the hassle of procedures and efficiently make the necessary preparations. In addition, by providing emotionally-based, customized support, the user experience can be improved.

[0331] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0332] Step 1:

[0333] Displaying the input screen

[0334] Terminal: When a user accesses the system, an input screen is displayed in the browser of the communication device (smart device) using HTML and JavaScript. This input screen includes input fields for identification information, age, type of change, etc., and is designed to make it easy for the user to input information.

[0335] Input: System access request from user

[0336] Output: Display of input screen

[0337] Step 2:

[0338] Entering information

[0339] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, enter "Identification information: User A," "Age: 30," and "Type of change: Name change." Placeholders and explanations are displayed in each field to make input easier.

[0340] Input: Information entered by the user

[0341] Output: The entered information is retained in the form

[0342] Step 3:

[0343] Acquiring emotion data

[0344] Emotion engine: Analyzes the user's input. The analysis method involves using a machine learning model to analyze input speed, input patterns, and writing style characteristics. For example, if the input speed is fast and the writing style is incomplete, it will determine that the user is feeling stressed.

[0345] Input: Information entered by the user

[0346] Output: Parsed emotion data (e.g., stress)

[0347] Step 4:

[0348] Sending input data and emotion data

[0349] On the device: When the user clicks the submit button on the form, the collected information and parsed sentiment data are converted into JSON format using JavaScript and sent as a POST request to the server via a RESTful API.

[0350] Input: Collected information and analyzed emotion data

[0351] Output: JSON data sent to the server

[0352] Step 5:

[0353] Data reception and analysis

[0354] Server: After receiving the POST request, the server first checks the integrity of the data. After the data integrity is confirmed, a server-side program such as Python or Node.js parses the JSON data and extracts the identity, age, type of change, and emotion data.

[0355] Input: JSON data sent from the terminal

[0356] Output: Extracted user information and sentiment data

[0357] Step 6:

[0358] Running the generative model

[0359] Server: Based on the extracted user information and emotion data, the server creates and passes a prompt to the generative AI model. This prompt includes the information and emotion data provided by the user. For example, the server might pass a prompt such as, "User information: Identification: User A, Age: 30, Type of change: Name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress level obtained from the emotion data."

[0360] Input: Extracted user information and emotion data

[0361] Output: A preparation list and customized advice generated by the generative AI model

[0362] Step 7:

[0363] Generate and return a preparation list

[0364] Server: Converts the list of preparations and customized advice obtained from the generative AI model into JSON format and sends it back to the communication device. Specifically, this includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods based on emotions."

[0365] Input: A list of preparations and customized advice output by the generative AI model

[0366] Output: JSON data sent to the communication device

[0367] Step 8:

[0368] Displaying the preparation list

[0369] Terminal: Receives the data returned from the server and displays a list of preparations and advice on the screen using HTML and JavaScript. By checking this information in advance, users can efficiently make the necessary preparations.

[0370] Input: JSON data returned from the server

[0371] Output: Preparation list and customized advice displayed on the communication device screen

[0372] (Application example 2)

[0373] 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."

[0374] It is difficult for users to know in advance what documents and preparations are required when carrying out a specific procedure, and if there are any inaccuracies, the procedure may not proceed smoothly. In addition, there is a lack of support to reduce the stress and anxiety users feel when carrying out procedures and to help them prepare more efficiently. For this reason, there is a need for a system that allows users to efficiently prepare the necessary items in advance and at the same time receive appropriate advice based on their emotions.

[0375] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input information into an input form using an information terminal, means for transmitting information and emotion data collected from the input form to the server, means for the server to analyze the collected information and emotion data and generate a list of necessary preparations and advice corresponding to the emotion using a generative model, and means for displaying the generated list of necessary preparations and advice corresponding to the emotion on the user's information terminal. This allows the user to efficiently prepare the necessary preparations in advance, making preparations to smoothly proceed with the procedure, and enabling stress and anxiety to be reduced by receiving appropriate advice corresponding to the emotion.

[0376] "User" refers to an individual or organization that uses the system to carry out a specific procedure.

[0377] An "information terminal" is a device such as a smartphone, tablet, or PC that allows users to input information and send and receive data.

[0378] An "input form" is a screen or interface that allows a user to enter specific information, including data fields such as name, age, and type of procedure.

[0379] The "server" is a computer system that analyzes the received information and emotion data and uses a generative model to generate a list of necessary preparations and advice based on the emotion.

[0380] "Collected Information" refers to data provided by users through input forms, including information such as name, age, and type of procedure.

[0381] "Emotional data" is data that represents the user's emotional state and is analyzed based on the speed and content of input.

[0382] A "generative model" is an algorithm that uses natural language processing technology to generate a list of necessary preparations and advice based on emotions based on input information and emotional data.

[0383] A "preparation list" is a list of documents and items that a user needs to carry out a specific procedure.

[0384] An "emotion engine" is software that has the function of analyzing the user's input content and input patterns to determine the user's emotional state.

[0385] "Emotionally-responsive advice" refers to appropriate support and suggestions provided based on the user's emotional state.

[0386] System Overview

[0387] The system that realizes this invention allows users to efficiently prepare the necessary documents and preparations for specific procedures in advance. It also provides more customized support by combining it with an emotion engine that recognizes the user's emotions.

[0388] System configuration

[0389] This system mainly consists of the following elements:

[0390] 1. Information terminal (user terminal):

[0391] Displays a form for users to enter information.

[0392] The input information and emotion data are sent to the server.

[0393] 2. Server:

[0394] Receive information and emotional data sent by the user.

[0395] The collected information and emotional data are analyzed, and a generative model is used to generate a preparation list and emotional advice.

[0396] The generated preparation list and advice according to the emotion are returned to the user's information terminal.

[0397] 3. Generative Model:

[0398] An algorithm that uses natural language processing technology to generate optimal preparation lists and emotional advice based on the information and emotional state entered by the user.

[0399] 4. Emotion Engine:

[0400] It has the ability to analyze the user's input content and input patterns to determine the user's emotional state.

[0401] Program processing details

[0402] When a user enters information into an input form using an information terminal, emotional data is obtained from the input content and the speed and content of the input. This data is converted into JSON format and sent to the server. The server analyzes the received data and generates prompts appropriate for the generative model. The generative model uses natural language processing technology to generate a list of necessary preparations and advice based on the emotion.

[0403] The hardware and software used are as follows:

[0404] Hardware: Smartphones, tablets, computers

[0405] Software: Python, TextBlob library, JSON library

[0406] Specific examples

[0407] For example, a user accesses the system to change their name and enters the following information: "Name: Yamada Taro," "Age: 30," and "Type of change: Name change." If the emotion engine detects "stress" at this time, the input details and emotional data are collected. Based on the collected information, the server then generates "Documents required for name change: Driver's license, resident registration, and seal certificate" and "Suggested relaxation methods to reduce stress," which are displayed on the user's information terminal.

[0408] Here is an example of a prompt to input to the generative model:

[0409] What documents do users need to complete the name change and what would you suggest to help them relax if they are feeling stressed from the input?

[0410] Example input:

[0411] Name: Yamada Hanako

[0412] Age: 28

[0413] Type of change: Name change

[0414] Emotion: Stress

[0415] Example answer:

[0416] Required documents: Driver's license, resident card, seal certificate

[0417] Emotional advice: Take deep breaths, listen to relaxing music

[0418] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0419] Step 1:

[0420] The user enters information into the form

[0421] A user uses an information device (smartphone, tablet, PC) to enter information such as name, age, type of procedure, etc. into an input form. This form contains multiple fields for the user to fill out.

[0422] (Input) Information such as name, age, type of procedure, etc.

[0423] (Output) A set of input information

[0424] Step 2:

[0425] Acquiring emotion data

[0426] The information terminal analyzes the user's input content and input speed and uses an emotion engine to determine the user's emotional state, extracting emotions such as stress and anxiety from the input content and speed.

[0427] (Input) Patterns of information entered by the user, such as input speed

[0428] (Output) Emotion data (e.g., "stress," "anxiety")

[0429] Step 3:

[0430] Sending input data and emotion data

[0431] The information terminal converts the collected information and emotion data into JSON format and sends it to the server as a POST request.

[0432] (Input) Information entered by the user, emotional data

[0433] (Output) JSON format data

[0434] Step 4:

[0435] Data reception and analysis by the server

[0436] The server parses the POST request received and extracts the JSON data, from which the name, age, procedure type, and emotion data are obtained.

[0437] (Input) JSON format data

[0438] (Output) Analyzed user information and emotion data

[0439] Step 5:

[0440] Running the generative model

[0441] Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model, which uses natural language processing technology to generate a list of necessary preparations and emotion-based advice.

[0442] (Input) User information and emotion data

[0443] (Output) Preparation list and emotional advice

[0444] Step 6:

[0445] Return and display of preparation list and advice

[0446] The server returns the prepared list and advice according to the user's emotion to the user's information terminal. The information terminal displays the returned list and advice on the screen, making it easier for the user to prepare in advance. The server also provides advice according to the user's emotion.

[0447] (Input) Generated preparation list and advice based on emotions

[0448] (Output) A list of preparations and advice based on emotions displayed on the device

[0449] The above are the specific processing steps that explain how the system program works. At each step, the input and output are clearly defined, and data processing and calculations are performed based on them.

[0450] 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.

[0451] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0452] 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.

[0453] [Second embodiment]

[0454] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0455] 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.

[0456] 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).

[0457] 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.

[0458] 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.

[0459] 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).

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0465] 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."

[0466] System Overview

[0467] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. Users input information into an input form using a smart device, and a list of necessary items is generated and displayed based on that information. Each processing step and specific examples are described in detail below.

[0468] System configuration

[0469] This system mainly consists of the following elements:

[0470] 1. Terminal (user's smart device):

[0471] Displays a form for users to enter information.

[0472] The entered information is sent to the server.

[0473] 2. Server:

[0474] Receive information sent by users.

[0475] The information is analyzed and a generative model is used to generate a list of necessary preparations.

[0476] The generated preparation list is sent back to the user's smart device.

[0477] 3. Generative Model:

[0478] An algorithm that uses natural language processing technology to generate the optimal preparation list based on the information entered by the user.

[0479] Program processing details

[0480] 1. Submitting the input form and entering information

[0481] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[0482] User: Enter the required information into the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[0483] 2. Sending input data

[0484] On the device: When the submit button on the form is clicked, the user's input data is converted to JSON format and sent to the server as a POST request.

[0485] 3. Data reception and analysis by the server

[0486] Server: Parses the received JSON data and obtains the user's input information. This information is passed to the generative model to generate a list of necessary preparations.

[0487] 4. Running the Generative Model

[0488] Generative model: Using natural language processing technology, the system generates an optimal list of items to prepare based on information provided by the user. For example, it includes specific information such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0489] 5. Return and display of preparation list

[0490] Server: Returns the generated preparation list to the user's smart device.

[0491] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[0492] Specific examples

[0493] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0494] 2. The device converts the input information into JSON format and sends it to the server.

[0495] 3. The server analyzes the received data and uses a generative model to generate a list of documents required for the name change: driver's license, resident registration card, seal certificate, etc.

[0496] 4. The server returns the generated list of preparations to the user's terminal.

[0497] 5. The device will display the returned list on the screen, making it easier for users to prepare in advance.

[0498] conclusion

[0499] The present invention provides an effective means for users to know in advance what documents and preparations are required when carrying out a specific procedure, thereby enabling users to make efficient preparations and smoothly proceed with the procedure.

[0500] The processing flow will be explained below.

[0501] Step 1:

[0502] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[0503] Step 2:

[0504] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[0505] Step 3:

[0506] On the device: When the user clicks the submit button on the form, JavaScript is used to collect the form data, convert it to JSON format, and send this JSON data to the server as a POST request.

[0507] Step 4:

[0508] Server: Parse the received POST request and extract the JSON data. From the parsed data, get the user information such as name, age, and type of change.

[0509] Step 5:

[0510] Server: Based on the acquired user information, it passes appropriate prompts to the generative model, which uses natural language processing techniques to generate a list of items to be prepared.

[0511] Step 6:

[0512] Generative model (on the server): The generative model uses natural language processing technology to generate a list of items to prepare based on the input information. For example, it generates content such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0513] Step 7:

[0514] Server: Receives the generated list of preparations, converts it to JSON format, and returns it to the terminal.

[0515] Step 8:

[0516] On the device: Receive the JSON data returned from the server and parse it using JavaScript. Get the list of preparations from the parsed data and display it on the user's device.

[0517] Step 9:

[0518] User: Check the list of items to prepare displayed on the device and prepare the necessary documents and items in advance, which will help the process go smoothly.

[0519] Example 1

[0520] 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."

[0521] When users go through procedures, it is difficult to know in advance what documents and preparations are required, which can cause the procedures to not proceed smoothly. In addition, insufficient preparations often result in duplicate work, making the procedures inefficient. This increases the burden on users.

[0522] 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.

[0523] In this invention, the server includes: means for a user to input information into an input form using a mobile information terminal; means for transmitting information collected from the input form to a processing device; means for the processing device to analyze the collected information and generate a list of necessary preparations using a generative AI model; means for the processing device to display the generated list of preparations on the user's mobile information terminal; and means for the generative AI model to generate the list of preparations using a prompt sentence for the server. This allows the user to efficiently grasp in advance the preparations required when performing a procedure, making it possible to smoothly proceed with the procedure and avoiding duplicate work.

[0524] A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, that a user uses to input and display information.

[0525] An "input form" is an interface through which a user enters information, and includes input fields such as name, age, type of change, etc.

[0526] A "processing device" is a device, such as a server, that receives and analyzes the data sent by the user and generates the required preparation list using a generative AI model.

[0527] A "generative AI model" is an algorithm or artificial intelligence model that uses natural language processing technology to generate an optimal preparation list based on information provided by the user.

[0528] A "prompt" is an instruction input to a generative AI model, and is text that specifically requests a list of necessary preparations based on the user's input information.

[0529] A "preparation list" is a list of documents and other items that a user needs to carry out a specific procedure.

[0530] "Analyzing information" is the process of understanding, categorizing, and converting user-entered data into a usable format.

[0531] "Collected Information" refers to data provided by users through input forms.

[0532] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. This system is primarily composed of a mobile information terminal, a processing device (server), and a generative AI model. Below, we provide a detailed explanation and specific examples of each element.

[0533] System Overview

[0534] A user uses a mobile information terminal (such as a smartphone or tablet) to input information into an input form. The input form contains multiple input fields, such as name, age, and type of change, and the user enters this information. Once the user has completed the input, the terminal converts the input information into JSON format and sends it to a processing device.

[0535] Hardware and software used

[0536] 1. Personal digital assistant: A device used by a user to enter and display information, such as a smartphone or tablet.

[0537] 2. Processing device (server): Responsible for receiving data, analyzing it, processing it using a generative AI model, and sending a response. Specifically, a server-side framework such as Express.js is used.

[0538] 3. Generative AI model: An algorithm that uses natural language processing technology to generate a preparation list. The generative AI model generates the optimal preparation list based on the prompt sentence.

[0539] Specific operation of the system

[0540] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0541] 2. The device converts the input information into JSON format and sends it to the processing device, which then sends the input data to the server.

[0542] 3. The server parses the received data and extracts the user's input, including data such as name, age, and type of change.

[0543] 4. The server uses the generative AI model to create a prompt based on the user's input. An example prompt might look like this:

[0544] "Please list the necessary preparations according to the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[0545] 5. The generative AI model generates an optimal list of items to prepare based on the prompt. Specifically, it generates a list such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0546] 6. The server returns the generated list of preparations to the user's device. The returned list is sent as a JSON response.

[0547] 7. The terminal analyzes the received preparation list and displays it on the screen of the user's smart device. The user can refer to this list and prepare the necessary documents in advance.

[0548] This system allows users to efficiently understand in advance what preparations they need to make when carrying out a procedure, allowing the procedure to proceed smoothly and avoiding duplicate work.

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

[0550] Step 1:

[0551] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains several input fields such as name, age, and type of change.

[0552] Input: User accesses the browser.

[0553] Output: The input form is displayed in the browser.

[0554] Step 2:

[0555] User: Enter the required information in the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[0556] Input: Name, Age, Change Type information.

[0557] Output: User enters information into a form.

[0558] Step 3:

[0559] On the device: When you click the submit button on the form, JavaScript triggers this event, converting the input data into JSON format, which is then sent to the server as a POST request.

[0560] Input: User presses submit button.

[0561] Output: JSON formatted data is generated and sent to the server.

[0562] Step 4:

[0563] Server: Receives JSON format data sent from the device.

[0564] Input: JSON data from the terminal.

[0565] Output: The received data.

[0566] Step 5:

[0567] Server: Parses the received JSON data and extracts the user's input information, such as name, age, and type of change.

[0568] Input: The received JSON data.

[0569] Output: The extracted user information.

[0570] Step 6:

[0571] Server: Creates a prompt for the generative AI model based on the user's input. Specifically, it would say something like, "Please list the necessary preparations based on the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[0572] Input: Extracted user information.

[0573] Output: The generated prompt statement.

[0574] Step 7:

[0575] Generative AI model: Analyzes the prompt and generates a list of the necessary documents. For example, it generates "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0576] Input: prompt statement.

[0577] Output: The generated preparation list.

[0578] Step 8:

[0579] Server: Receives the generated list of preparations and returns it to the terminal as a response in JSON format.

[0580] Input: The generated preparation list.

[0581] Output: Response in JSON format.

[0582] Step 9:

[0583] Terminal: Analyzes the received JSON format preparation list and displays it on the screen of the user's smart device.

[0584] Input: The JSON response from the server.

[0585] Output: A list of preparations will be displayed on the screen.

[0586] (Application example 1)

[0587] 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."

[0588] In today's diverse procedures, users are required to know in advance what documents and items they need and prepare them efficiently. However, with conventional methods, users often spend a significant amount of time and effort checking what items they need, which causes the process at the store to take longer. To solve this problem and allow users to prepare efficiently, a system that automatically generates and provides a list of items to be prepared is needed.

[0589] 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.

[0590] In this invention, the server includes means for a user to input information into an input form using an information processing terminal, means for transmitting information collected from the input form to a data analysis device, means for the data analysis device to analyze the collected information and generate a list of necessary preparations using natural language processing technology, means for displaying the generated list of preparations on the user's information processing terminal, and means for providing a list of preparations necessary for procedures at a physical store based on the information input by the user. This enables the user to know in advance the documents and preparations they will need and to make efficient preparations.

[0591] An "information processing terminal" is a device that allows a user to input information and communicate with a server.

[0592] "Data analysis device" refers to a device for analyzing collected information and generating a preparation list.

[0593] "Natural language processing technology" refers to the technology that allows computers to understand and generate human language.

[0594] A "preparation list" is a list of documents and items required to carry out a specific procedure.

[0595] A "question answer generation algorithm" is an algorithm for generating the optimal answer to an input question.

[0596] A "field" is an item on an input form where a user enters specific information.

[0597] "Name" means the name of the User.

[0598] "Procedure type" is an item that indicates the type of specific procedure that the user is going to perform.

[0599] This invention provides a system for efficiently preparing documents and items required for a specific procedure. In this system, a user inputs information into a form using an information processing terminal, the data is sent to a server, analyzed, and a generative model is used to generate and display a list of necessary items. Detailed embodiments are described below.

[0600] System Overview

[0601] The system mainly consists of the following elements:

[0602] 1. Information processing terminal: A device through which a user inputs information and communicates with a server. Specific devices include smartphones, tablets, and PCs.

[0603] 2. Data analysis device: A device that analyzes collected information and generates a list of preparations. Specifically, it is a system built by a server.

[0604] 3. Generative AI model: An algorithm that uses natural language processing technology to generate an optimal preparation list.

[0605] Program Description

[0606] Hardware and Software Use

[0607] Information processing devices (e.g. smartphones, tablets, PCs)

[0608] This is a terminal where users input information and send it to the data analysis device. A browser and dedicated applications are installed on this terminal.

[0609] Data analysis equipment (e.g., server)

[0610] The information sent by the user is analyzed and a preparation list is generated using a generative AI model. The server has a backend system built using Node.js and Express.

[0611] Generative AI models (e.g., GPT-3, TensorFlow)

[0612] This is an algorithm that uses natural language processing technology to generate a list of necessary preparations based on information entered by the user.

[0613] Specific examples of processing

[0614] 1. The user uses the information processing terminal to enter information into the input form. For example, the user selects "name change" as the procedure and enters the user's name and other required items.

[0615] 2. The device converts the input information into JSON format and sends it to the server as a POST request.

[0616] 3. The server analyzes the received data and inputs it as a prompt sentence into the generative AI model.

[0617] 4. The generative AI model generates an optimal preparation list based on the input prompt.

[0618] 5. The server returns the prepared item list to the information processing terminal.

[0619] 6. The information processing terminal displays the received preparation list on the screen and provides it to the user.

[0620] Context and prompt example

[0621] Specific prompt examples:

[0622] Name: Yamada Taro, Procedure: Name change

[0623] This invention allows users to efficiently prepare the documents and materials required for the procedure in advance, thereby shortening the time required for the procedure at a physical store. The above is a detailed description of the embodiment of the present invention.

[0624] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0625] Step 1:

[0626] The user uses an information processing terminal to input information into the input form. Specifically, the user enters necessary information such as name and procedure details into the input fields. This information becomes the initial input data for the system.

[0627] Input: Name, procedure details, and other information

[0628] Output: Data entered by the user

[0629] Step 2:

[0630] The terminal converts the information entered by the user into JSON format and sends it to the data analysis device. Specifically, the information entered in the input fields is sent to the server as a POST request.

[0631] Input: Data entered by the user

[0632] Output: JSON format data

[0633] Step 3:

[0634] The server parses the received JSON data and extracts the necessary information. Specifically, it uses Node.js and Express to parse the data and extract the necessary fields (name, procedure details, etc.).

[0635] Input: JSON format data

[0636] Output: Analyzed data (name, procedure details, etc.)

[0637] Step 4:

[0638] The server passes the extracted data to the generative AI model as a prompt sentence. Specifically, it generates a prompt sentence and inputs it into the generative AI model (e.g., GPT-3 or TensorFlow).

[0639] Input: Analyzed data (name, procedure details, etc.)

[0640] Output: prompt statement

[0641] Step 5:

[0642] The generative AI model generates an optimal preparation list based on the prompt sentence. Specifically, it uses natural language processing technology to generate the necessary preparation list and returns it to the server.

[0643] Input: prompt statement

[0644] Output: Preparation list

[0645] Step 6:

[0646] The server returns the created preparation list to the information processing terminal. Specifically, it converts the preparation list into JSON format and returns it as an HTTP response.

[0647] Input: List of preparations

[0648] Output: JSON format list of preparations

[0649] Step 7:

[0650] The information processing terminal displays the received preparation list to the user. Specifically, the preparation list is displayed in an application or web browser so that the user can check it.

[0651] Input: JSON format list of preparations

[0652] Output: A list of preparations that is displayed to the user

[0653] 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.

[0654] System Overview

[0655] This invention is a system that allows users to efficiently prepare documents and other items required for specific procedures by identifying them in advance. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more customized support. Each processing step and specific examples are described in detail below.

[0656] System configuration

[0657] This system mainly consists of the following elements:

[0658] 1. Terminal (user's smart device):

[0659] Displays a form for users to enter information.

[0660] The input information and the user's emotional data are sent to the server.

[0661] 2. Server:

[0662] Receive information and emotional data sent by the user.

[0663] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[0664] The generated preparation list is sent back to the user's smart device.

[0665] 3. Generative Model:

[0666] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user.

[0667] 4. Emotion Engine:

[0668] It has the ability to analyze the user's input and emotional patterns to determine the user's emotional state.

[0669] Program processing details

[0670] 1. Submitting the input form and entering information

[0671] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[0672] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[0673] 2. Acquiring Emotion Data

[0674] Emotion engine: Analyzes emotional patterns from user input to determine the user's emotional state. This emotional data is derived based on the user's typing speed, input content, etc.

[0675] 3. Sending input data and emotion data

[0676] On the device: When you click the submit button on the form, the collected information and analyzed emotion data are converted into JSON format and sent to the server as a POST request.

[0677] 4. Data reception and analysis by the server

[0678] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[0679] 5. Execution of the generative model by the server

[0680] Server: Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotion data, the server generates a customized preparation list.

[0681] 6. Return and display of preparation list

[0682] Server: Returns the generated preparation list to the user's smart device.

[0683] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[0684] Specific examples

[0685] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0686] 2. The emotion engine analyzes the input and detects "stress."

[0687] 3. The device converts the collected information and emotion data into JSON format and sends it to the server.

[0688] 4. The server analyzes the received data and uses a generative model to generate a list of items to prepare, such as "suggested relaxation methods based on emotions" and "documents required for name change: driver's license, resident registration, seal certificate, etc."

[0689] 5. The server returns the generated list to the terminal.

[0690] 6. The device will display the returned list on the screen, making it easier for users to prepare in advance, and will also provide advice based on their emotions.

[0691] conclusion

[0692] The present invention provides an effective means for users to know in advance what documents and preparations are required for a specific procedure. Furthermore, it also recognizes the user's emotional state and provides customized support based on that, thereby improving the user experience. This allows users to prepare efficiently and proceed smoothly through the procedure.

[0693] The processing flow will be explained below.

[0694] Step 1:

[0695] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[0696] Step 2:

[0697] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[0698] Step 3:

[0699] Emotion engine (inside the device): Analyzes the input information and the user's behavioral data while inputting (such as input speed, typing intervals, frequency of errors, etc.) to determine the user's emotional state. For example, if the user makes many errors and the tempo is irregular while inputting, it will be determined that the user is feeling "stressed."

[0700] Step 4:

[0701] On the device: When the user clicks the submit button on the form, JavaScript is used to collect the form data and parsed emotion data, convert them into JSON format, and send them to the server.

[0702] Step 5:

[0703] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[0704] Step 6:

[0705] Server: Based on the acquired user information and emotional data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotional data, the server generates a customized preparation list that takes into account the user's emotional state.

[0706] Step 7:

[0707] Generative model (inside the server): Based on the information entered by the user, the generative model generates a list of necessary preparations, along with additional information based on emotions, such as "preferentially guide people who are feeling stressed through simple procedures."

[0708] Step 8:

[0709] Server: Returns the generated preparation list and emotion-based advice to the user's smart device.

[0710] Step 9:

[0711] Terminal: Receives the JSON data returned from the server, parses it using JavaScript, and displays a list of items to prepare and advice based on the emotion in an HTML document. Specifically, it displays advice such as "Try taking a deep breath to relax" along with "Documents required for name change: driver's license, resident registration, seal certificate, etc."

[0712] Step 10:

[0713] Users can check the preparation list and advice displayed on the device, gather the necessary documents and supplies in advance, or act according to their feelings, making the process smooth and efficient.

[0714] Example 2

[0715] 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."

[0716] Previous systems lacked an efficient way for users to understand in advance what documents and preparations were required when carrying out specific procedures. They also failed to provide appropriate support that took into account the user's emotional state, often causing inconvenience and stress. This led to users being inadequately prepared in advance, resulting in problems with procedures not proceeding smoothly.

[0717] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing collected information and generating a list of necessary preparations using a generative model, means for analyzing emotion data, and means for displaying customized advice based on the generated list of preparations and emotion data on the communication device. This allows the user to know in advance what documents and preparations they need and to receive appropriate support according to their emotional state.

[0718] "User" refers to a person who uses this system to enter the information required for a procedure.

[0719] "Communication device" refers to hardware such as a smart device that a user uses to input information.

[0720] "Input screen" refers to an interface for inputting information that is displayed on the display of a communication device.

[0721] "Collected Information" refers to all data provided by the user through the input screens.

[0722] "Server" refers to a computing system for receiving and analyzing collected information.

[0723] "Analysis" refers to the process of processing the collected information and generating a list of necessary preparations and emotional data.

[0724] "Generative Model" refers to an algorithm that uses natural language processing techniques to generate a list of necessary preparations and customized advice based on sentiment data.

[0725] A "preparation list" refers to a list of documents and items required when carrying out a procedure.

[0726] "Emotional data" refers to data on a user's mental state analyzed from the content and method of input.

[0727] "Customized advice" refers to specific assistance information provided individually based on the user's emotional data and input information.

[0728] The present invention is a system that allows users to efficiently prepare by identifying the documents and preparations required for a specific procedure in advance. It is also possible to analyze the user's emotional state in real time and provide customized support based on their emotions. The following describes the detailed processing content of the program of this system.

[0729] System configuration

[0730] The system mainly consists of the following elements:

[0731] 1. Communication Device (User's Smart Device):

[0732] Displays a screen for the user to enter information.

[0733] The input information and emotion data are sent to the server.

[0734] 2. Server:

[0735] Receive information and emotional data sent by the user.

[0736] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[0737] The generated preparation list is returned to the user's communication device.

[0738] 3. Generative Model:

[0739] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user. Large-scale language models such as GPT-3 can be used as this generation model.

[0740] 4. Emotion Engine:

[0741] It has the ability to analyze the user's input content, input speed, and patterns to determine the user's emotional state. This emotion engine uses emotion analysis models and machine learning algorithms.

[0742] Program processing details

[0743] Submitting the form and entering information

[0744] Communication device: When a user accesses the system, an input screen is displayed in the smart device browser using HTML and JavaScript. This screen contains input fields for identification information, age, type of change, etc.

[0745] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, "Identification information: User A," "Age: 30," "Type of change: Name change," etc. Placeholders and explanations are displayed in each field to make it easier for users to enter information.

[0746] Acquiring emotion data

[0747] Emotion engine: Analyzes user input. It uses input speed, patterns, and linguistic features to determine the user's emotional state using a machine learning model. For example, if the input speed is fast and the sentences are fragmented, it can detect stress.

[0748] Sending input data and emotion data

[0749] Communication device: When the submit button on the form is clicked, the collected information and analyzed emotion data are converted into JSON format and sent as a POST request to the server using a RESTful API.

[0750] Data reception and analysis

[0751] Server: Receives the POST request and checks the data integrity. A server-side program using Python or Node.js (e.g., Flask, Express.js) parses the JSON data and extracts the identity, age, type of change, and emotion data.

[0752] Running the generative model

[0753] Server: Based on the extracted user information and emotion data, the server passes prompts to the generative AI model. For example, a prompt such as "User information: User A, age 30, type of change: name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress state obtained from the emotion data" can be used for the generative AI model (such as GPT-3).

[0754] Generate and return a preparation list

[0755] Server: Receives the customized list of preparations as a response from the generative model, converts it into JSON format, and sends it back to the communication device. Specifically, it includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods according to emotions."

[0756] Displaying the preparation list

[0757] Communication device: Receives the list of items to be prepared returned from the server and displays it on the screen using HTML and JavaScript. Based on this information, users can prepare the items required for the procedure in advance.

[0758] The above is a detailed description of the processing procedure of the system of the present invention. By using this system, users can reduce the hassle of procedures and efficiently make the necessary preparations. In addition, by providing emotionally-based, customized support, the user experience can be improved.

[0759] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0760] Step 1:

[0761] Displaying the input screen

[0762] Terminal: When a user accesses the system, an input screen is displayed in the browser of the communication device (smart device) using HTML and JavaScript. This input screen includes input fields for identification information, age, type of change, etc., and is designed to make it easy for the user to input information.

[0763] Input: System access request from user

[0764] Output: Display of input screen

[0765] Step 2:

[0766] Entering information

[0767] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, enter "Identification information: User A," "Age: 30," and "Type of change: Name change." Placeholders and explanations are displayed in each field to make input easier.

[0768] Input: Information entered by the user

[0769] Output: The entered information is retained in the form

[0770] Step 3:

[0771] Acquiring emotion data

[0772] Emotion engine: Analyzes the user's input. The analysis method involves using a machine learning model to analyze input speed, input patterns, and writing style characteristics. For example, if the input speed is fast and the writing style is incomplete, it will determine that the user is feeling stressed.

[0773] Input: Information entered by the user

[0774] Output: Parsed emotion data (e.g., stress)

[0775] Step 4:

[0776] Sending input data and emotion data

[0777] On the device: When the user clicks the submit button on the form, the collected information and parsed sentiment data are converted into JSON format using JavaScript and sent as a POST request to the server via a RESTful API.

[0778] Input: Collected information and analyzed emotion data

[0779] Output: JSON data sent to the server

[0780] Step 5:

[0781] Data reception and analysis

[0782] Server: After receiving the POST request, the server first checks the integrity of the data. After the data integrity is confirmed, a server-side program such as Python or Node.js parses the JSON data and extracts the identity, age, type of change, and emotion data.

[0783] Input: JSON data sent from the terminal

[0784] Output: Extracted user information and sentiment data

[0785] Step 6:

[0786] Running the generative model

[0787] Server: Based on the extracted user information and emotion data, the server creates and passes a prompt to the generative AI model. This prompt includes the information and emotion data provided by the user. For example, the server might pass a prompt such as, "User information: Identification: User A, Age: 30, Type of change: Name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress level obtained from the emotion data."

[0788] Input: Extracted user information and emotion data

[0789] Output: A preparation list and customized advice generated by the generative AI model

[0790] Step 7:

[0791] Generate and return a preparation list

[0792] Server: Converts the list of preparations and customized advice obtained from the generative AI model into JSON format and sends it back to the communication device. Specifically, this includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods based on emotions."

[0793] Input: A list of preparations and customized advice output by the generative AI model

[0794] Output: JSON data sent to the communication device

[0795] Step 8:

[0796] Displaying the preparation list

[0797] Terminal: Receives the data returned from the server and displays a list of preparations and advice on the screen using HTML and JavaScript. By checking this information in advance, users can efficiently make the necessary preparations.

[0798] Input: JSON data returned from the server

[0799] Output: Preparation list and customized advice displayed on the communication device screen

[0800] (Application example 2)

[0801] 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."

[0802] It is difficult for users to know in advance what documents and preparations are required when carrying out a specific procedure, and if there are any inaccuracies, the procedure may not proceed smoothly. In addition, there is a lack of support to reduce the stress and anxiety users feel when carrying out procedures and to help them prepare more efficiently. For this reason, there is a need for a system that allows users to efficiently prepare the necessary items in advance and at the same time receive appropriate advice based on their emotions.

[0803] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input information into an input form using an information terminal, means for transmitting information and emotion data collected from the input form to the server, means for the server to analyze the collected information and emotion data and generate a list of necessary preparations and advice corresponding to the emotion using a generative model, and means for displaying the generated list of necessary preparations and advice corresponding to the emotion on the user's information terminal. This allows the user to efficiently prepare the necessary preparations in advance, making preparations to smoothly proceed with the procedure, and enabling stress and anxiety to be reduced by receiving appropriate advice corresponding to the emotion.

[0804] "User" refers to an individual or organization that uses the system to carry out a specific procedure.

[0805] An "information terminal" is a device such as a smartphone, tablet, or PC that allows users to input information and send and receive data.

[0806] An "input form" is a screen or interface that allows a user to enter specific information, including data fields such as name, age, and type of procedure.

[0807] The "server" is a computer system that analyzes the received information and emotion data and uses a generative model to generate a list of necessary preparations and advice based on the emotion.

[0808] "Collected Information" refers to data provided by users through input forms, including information such as name, age, and type of procedure.

[0809] "Emotional data" is data that represents the user's emotional state and is analyzed based on the speed and content of input.

[0810] A "generative model" is an algorithm that uses natural language processing technology to generate a list of necessary preparations and advice based on emotions based on input information and emotional data.

[0811] A "preparation list" is a list of documents and items that a user needs to carry out a specific procedure.

[0812] An "emotion engine" is software that has the function of analyzing the user's input content and input patterns to determine the user's emotional state.

[0813] "Emotionally-responsive advice" refers to appropriate support and suggestions provided based on the user's emotional state.

[0814] System Overview

[0815] The system that realizes this invention allows users to efficiently prepare the necessary documents and preparations for specific procedures in advance. It also provides more customized support by combining it with an emotion engine that recognizes the user's emotions.

[0816] System configuration

[0817] This system mainly consists of the following elements:

[0818] 1. Information terminal (user terminal):

[0819] Displays a form for users to enter information.

[0820] The input information and emotion data are sent to the server.

[0821] 2. Server:

[0822] Receive information and emotional data sent by the user.

[0823] The collected information and emotional data are analyzed, and a generative model is used to generate a preparation list and emotional advice.

[0824] The generated preparation list and advice according to the emotion are returned to the user's information terminal.

[0825] 3. Generative Model:

[0826] An algorithm that uses natural language processing technology to generate optimal preparation lists and emotional advice based on the information and emotional state entered by the user.

[0827] 4. Emotion Engine:

[0828] It has the ability to analyze the user's input content and input patterns to determine the user's emotional state.

[0829] Program processing details

[0830] When a user enters information into an input form using an information terminal, emotional data is obtained from the input content and the speed and content of the input. This data is converted into JSON format and sent to the server. The server analyzes the received data and generates prompts appropriate for the generative model. The generative model uses natural language processing technology to generate a list of necessary preparations and advice based on the emotion.

[0831] The hardware and software used are as follows:

[0832] Hardware: Smartphones, tablets, computers

[0833] Software: Python, TextBlob library, JSON library

[0834] Specific examples

[0835] For example, a user accesses the system to change their name and enters the following information: "Name: Yamada Taro," "Age: 30," and "Type of change: Name change." If the emotion engine detects "stress" at this time, the input details and emotional data are collected. Based on the collected information, the server then generates "Documents required for name change: Driver's license, resident registration, and seal certificate" and "Suggested relaxation methods to reduce stress," which are displayed on the user's information terminal.

[0836] Here is an example of a prompt to input to the generative model:

[0837] What documents do users need to complete the name change and what would you suggest to help them relax if they are feeling stressed from the input?

[0838] Example input:

[0839] Name: Yamada Hanako

[0840] Age: 28

[0841] Type of change: Name change

[0842] Emotion: Stress

[0843] Example answer:

[0844] Required documents: Driver's license, resident card, seal certificate

[0845] Emotional advice: Take deep breaths, listen to relaxing music

[0846] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0847] Step 1:

[0848] The user enters information into the form

[0849] A user uses an information device (smartphone, tablet, PC) to enter information such as name, age, type of procedure, etc. into an input form. This form contains multiple fields for the user to fill out.

[0850] (Input) Information such as name, age, type of procedure, etc.

[0851] (Output) A set of input information

[0852] Step 2:

[0853] Acquiring emotion data

[0854] The information terminal analyzes the user's input content and input speed and uses an emotion engine to determine the user's emotional state, extracting emotions such as stress and anxiety from the input content and speed.

[0855] (Input) Patterns of information entered by the user, such as input speed

[0856] (Output) Emotion data (e.g., "stress," "anxiety")

[0857] Step 3:

[0858] Sending input data and emotion data

[0859] The information terminal converts the collected information and emotion data into JSON format and sends it to the server as a POST request.

[0860] (Input) Information entered by the user, emotional data

[0861] (Output) JSON format data

[0862] Step 4:

[0863] Data reception and analysis by the server

[0864] The server parses the POST request received and extracts the JSON data, from which the name, age, procedure type, and emotion data are obtained.

[0865] (Input) JSON format data

[0866] (Output) Analyzed user information and emotion data

[0867] Step 5:

[0868] Running the generative model

[0869] Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model, which uses natural language processing technology to generate a list of necessary preparations and emotion-based advice.

[0870] (Input) User information and emotion data

[0871] (Output) Preparation list and emotional advice

[0872] Step 6:

[0873] Return and display of preparation list and advice

[0874] The server returns the prepared list and advice according to the user's emotion to the user's information terminal. The information terminal displays the returned list and advice on the screen, making it easier for the user to prepare in advance. The server also provides advice according to the user's emotion.

[0875] (Input) Generated preparation list and advice based on emotions

[0876] (Output) A list of preparations and advice based on emotions displayed on the device

[0877] The above are the specific processing steps that explain how the system program works. At each step, the input and output are clearly defined, and data processing and calculations are performed based on them.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] [Third embodiment]

[0882] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0883] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0884] 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).

[0885] 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.

[0886] 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.

[0887] 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).

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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."

[0894] System Overview

[0895] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. Users input information into an input form using a smart device, and a list of necessary items is generated and displayed based on that information. Each processing step and specific examples are described in detail below.

[0896] System configuration

[0897] This system mainly consists of the following elements:

[0898] 1. Terminal (user's smart device):

[0899] Displays a form for users to enter information.

[0900] The entered information is sent to the server.

[0901] 2. Server:

[0902] Receive information sent by users.

[0903] The information is analyzed and a generative model is used to generate a list of necessary preparations.

[0904] The generated preparation list is sent back to the user's smart device.

[0905] 3. Generative Model:

[0906] An algorithm that uses natural language processing technology to generate the optimal preparation list based on the information entered by the user.

[0907] Program processing details

[0908] 1. Submitting the input form and entering information

[0909] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[0910] User: Enter the required information into the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[0911] 2. Sending input data

[0912] On the device: When the submit button on the form is clicked, the user's input data is converted to JSON format and sent to the server as a POST request.

[0913] 3. Data reception and analysis by the server

[0914] Server: Parses the received JSON data and obtains the user's input information. This information is passed to the generative model to generate a list of necessary preparations.

[0915] 4. Running the Generative Model

[0916] Generative model: Using natural language processing technology, the system generates an optimal list of items to prepare based on information provided by the user. For example, it includes specific information such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0917] 5. Return and display of preparation list

[0918] Server: Returns the generated preparation list to the user's smart device.

[0919] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[0920] Specific examples

[0921] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0922] 2. The device converts the input information into JSON format and sends it to the server.

[0923] 3. The server analyzes the received data and uses a generative model to generate a list of documents required for the name change: driver's license, resident registration card, seal certificate, etc.

[0924] 4. The server returns the generated list of preparations to the user's terminal.

[0925] 5. The device will display the returned list on the screen, making it easier for users to prepare in advance.

[0926] conclusion

[0927] The present invention provides an effective means for users to know in advance what documents and preparations are required when carrying out a specific procedure, thereby enabling users to make efficient preparations and smoothly proceed with the procedure.

[0928] The processing flow will be explained below.

[0929] Step 1:

[0930] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[0931] Step 2:

[0932] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[0933] Step 3:

[0934] On the device: When the user clicks the submit button on the form, JavaScript is used to collect the form data, convert it to JSON format, and send this JSON data to the server as a POST request.

[0935] Step 4:

[0936] Server: Parse the received POST request and extract the JSON data. From the parsed data, get the user information such as name, age, and type of change.

[0937] Step 5:

[0938] Server: Based on the acquired user information, it passes appropriate prompts to the generative model, which uses natural language processing techniques to generate a list of items to be prepared.

[0939] Step 6:

[0940] Generative model (on the server): The generative model uses natural language processing technology to generate a list of items to prepare based on the input information. For example, it generates content such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0941] Step 7:

[0942] Server: Receives the generated list of preparations, converts it to JSON format, and returns it to the terminal.

[0943] Step 8:

[0944] On the device: Receive the JSON data returned from the server and parse it using JavaScript. Get the list of preparations from the parsed data and display it on the user's device.

[0945] Step 9:

[0946] User: Check the list of items to prepare displayed on the device and prepare the necessary documents and items in advance, which will help the process go smoothly.

[0947] Example 1

[0948] 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."

[0949] When users go through procedures, it is difficult to know in advance what documents and preparations are required, which can cause the procedures to not proceed smoothly. In addition, insufficient preparations often result in duplicate work, making the procedures inefficient. This increases the burden on users.

[0950] 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.

[0951] In this invention, the server includes: means for a user to input information into an input form using a mobile information terminal; means for transmitting information collected from the input form to a processing device; means for the processing device to analyze the collected information and generate a list of necessary preparations using a generative AI model; means for the processing device to display the generated list of preparations on the user's mobile information terminal; and means for the generative AI model to generate the list of preparations using a prompt sentence for the server. This allows the user to efficiently grasp in advance the preparations required when performing a procedure, making it possible to smoothly proceed with the procedure and avoiding duplicate work.

[0952] A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, that a user uses to input and display information.

[0953] An "input form" is an interface through which a user enters information, and includes input fields such as name, age, type of change, etc.

[0954] A "processing device" is a device, such as a server, that receives and analyzes the data sent by the user and generates the required preparation list using a generative AI model.

[0955] A "generative AI model" is an algorithm or artificial intelligence model that uses natural language processing technology to generate an optimal preparation list based on information provided by the user.

[0956] A "prompt" is an instruction input to a generative AI model, and is text that specifically requests a list of necessary preparations based on the user's input information.

[0957] A "preparation list" is a list of documents and other items that a user needs to carry out a specific procedure.

[0958] "Analyzing information" is the process of understanding, categorizing, and converting user-entered data into a usable format.

[0959] "Collected Information" refers to data provided by users through input forms.

[0960] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. This system is primarily composed of a mobile information terminal, a processing device (server), and a generative AI model. Below, we provide a detailed explanation and specific examples of each element.

[0961] System Overview

[0962] A user uses a mobile information terminal (such as a smartphone or tablet) to input information into an input form. The input form contains multiple input fields, such as name, age, and type of change, and the user enters this information. Once the user has completed the input, the terminal converts the input information into JSON format and sends it to a processing device.

[0963] Hardware and software used

[0964] 1. Personal digital assistant: A device used by a user to enter and display information, such as a smartphone or tablet.

[0965] 2. Processing device (server): Responsible for receiving data, analyzing it, processing it using a generative AI model, and sending a response. Specifically, a server-side framework such as Express.js is used.

[0966] 3. Generative AI model: An algorithm that uses natural language processing technology to generate a preparation list. The generative AI model generates the optimal preparation list based on the prompt sentence.

[0967] Specific operation of the system

[0968] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[0969] 2. The device converts the input information into JSON format and sends it to the processing device, which then sends the input data to the server.

[0970] 3. The server parses the received data and extracts the user's input, including data such as name, age, and type of change.

[0971] 4. The server uses the generative AI model to create a prompt based on the user's input. An example prompt might look like this:

[0972] "Please list the necessary preparations according to the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[0973] 5. The generative AI model generates an optimal list of items to prepare based on the prompt. Specifically, it generates a list such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[0974] 6. The server returns the generated list of preparations to the user's device. The returned list is sent as a JSON response.

[0975] 7. The terminal analyzes the received preparation list and displays it on the screen of the user's smart device. The user can refer to this list and prepare the necessary documents in advance.

[0976] This system allows users to efficiently understand in advance what preparations they need to make when carrying out a procedure, allowing the procedure to proceed smoothly and avoiding duplicate work.

[0977] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0978] Step 1:

[0979] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains several input fields such as name, age, and type of change.

[0980] Input: User accesses the browser.

[0981] Output: The input form is displayed in the browser.

[0982] Step 2:

[0983] User: Enter the required information in the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[0984] Input: Name, Age, Change Type information.

[0985] Output: User enters information into a form.

[0986] Step 3:

[0987] On the device: When you click the submit button on the form, JavaScript triggers this event, converting the input data into JSON format, which is then sent to the server as a POST request.

[0988] Input: User presses submit button.

[0989] Output: JSON formatted data is generated and sent to the server.

[0990] Step 4:

[0991] Server: Receives JSON format data sent from the device.

[0992] Input: JSON data from the terminal.

[0993] Output: The received data.

[0994] Step 5:

[0995] Server: Parses the received JSON data and extracts the user's input information, such as name, age, and type of change.

[0996] Input: The received JSON data.

[0997] Output: The extracted user information.

[0998] Step 6:

[0999] Server: Creates a prompt for the generative AI model based on the user's input. Specifically, it would say something like, "Please list the necessary preparations based on the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[1000] Input: Extracted user information.

[1001] Output: The generated prompt statement.

[1002] Step 7:

[1003] Generative AI model: Analyzes the prompt and generates a list of the necessary documents. For example, it generates "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[1004] Input: prompt statement.

[1005] Output: The generated preparation list.

[1006] Step 8:

[1007] Server: Receives the generated list of preparations and returns it to the terminal as a response in JSON format.

[1008] Input: The generated preparation list.

[1009] Output: Response in JSON format.

[1010] Step 9:

[1011] Terminal: Analyzes the received JSON format preparation list and displays it on the screen of the user's smart device.

[1012] Input: The JSON response from the server.

[1013] Output: A list of preparations will be displayed on the screen.

[1014] (Application example 1)

[1015] 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."

[1016] In today's diverse procedures, users are required to know in advance what documents and items they need and prepare them efficiently. However, with conventional methods, users often spend a significant amount of time and effort checking what items they need, which causes the process at the store to take longer. To solve this problem and allow users to prepare efficiently, a system that automatically generates and provides a list of items to be prepared is needed.

[1017] 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.

[1018] In this invention, the server includes means for a user to input information into an input form using an information processing terminal, means for transmitting information collected from the input form to a data analysis device, means for the data analysis device to analyze the collected information and generate a list of necessary preparations using natural language processing technology, means for displaying the generated list of preparations on the user's information processing terminal, and means for providing a list of preparations necessary for procedures at a physical store based on the information input by the user. This enables the user to know in advance the documents and preparations they will need and to make efficient preparations.

[1019] An "information processing terminal" is a device that allows a user to input information and communicate with a server.

[1020] "Data analysis device" refers to a device for analyzing collected information and generating a preparation list.

[1021] "Natural language processing technology" refers to the technology that allows computers to understand and generate human language.

[1022] A "preparation list" is a list of documents and items required to carry out a specific procedure.

[1023] A "question answer generation algorithm" is an algorithm for generating the optimal answer to an input question.

[1024] A "field" is an item on an input form where a user enters specific information.

[1025] "Name" means the name of the User.

[1026] "Procedure type" is an item that indicates the type of specific procedure that the user is going to perform.

[1027] This invention provides a system for efficiently preparing documents and items required for a specific procedure. In this system, a user inputs information into a form using an information processing terminal, the data is sent to a server, analyzed, and a generative model is used to generate and display a list of necessary items. Detailed embodiments are described below.

[1028] System Overview

[1029] The system mainly consists of the following elements:

[1030] 1. Information processing terminal: A device through which a user inputs information and communicates with a server. Specific devices include smartphones, tablets, and PCs.

[1031] 2. Data analysis device: A device that analyzes collected information and generates a list of preparations. Specifically, it is a system built by a server.

[1032] 3. Generative AI model: An algorithm that uses natural language processing technology to generate an optimal preparation list.

[1033] Program Description

[1034] Hardware and Software Use

[1035] Information processing devices (e.g. smartphones, tablets, PCs)

[1036] This is a terminal where users input information and send it to the data analysis device. A browser and dedicated applications are installed on this terminal.

[1037] Data analysis equipment (e.g., server)

[1038] The information sent by the user is analyzed and a preparation list is generated using a generative AI model. The server has a backend system built using Node.js and Express.

[1039] Generative AI models (e.g., GPT-3, TensorFlow)

[1040] This is an algorithm that uses natural language processing technology to generate a list of necessary preparations based on information entered by the user.

[1041] Specific examples of processing

[1042] 1. The user uses the information processing terminal to enter information into the input form. For example, the user selects "name change" as the procedure and enters the user's name and other required items.

[1043] 2. The device converts the input information into JSON format and sends it to the server as a POST request.

[1044] 3. The server analyzes the received data and inputs it as a prompt sentence into the generative AI model.

[1045] 4. The generative AI model generates an optimal preparation list based on the input prompt.

[1046] 5. The server returns the prepared item list to the information processing terminal.

[1047] 6. The information processing terminal displays the received preparation list on the screen and provides it to the user.

[1048] Context and prompt example

[1049] Specific prompt examples:

[1050] Name: Yamada Taro, Procedure: Name change

[1051] This invention allows users to efficiently prepare the documents and materials required for the procedure in advance, thereby shortening the time required for the procedure at a physical store. The above is a detailed description of the embodiment of the present invention.

[1052] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1053] Step 1:

[1054] The user uses an information processing terminal to input information into the input form. Specifically, the user enters necessary information such as name and procedure details into the input fields. This information becomes the initial input data for the system.

[1055] Input: Name, procedure details, and other information

[1056] Output: Data entered by the user

[1057] Step 2:

[1058] The terminal converts the information entered by the user into JSON format and sends it to the data analysis device. Specifically, the information entered in the input fields is sent to the server as a POST request.

[1059] Input: Data entered by the user

[1060] Output: JSON format data

[1061] Step 3:

[1062] The server parses the received JSON data and extracts the necessary information. Specifically, it uses Node.js and Express to parse the data and extract the necessary fields (name, procedure details, etc.).

[1063] Input: JSON format data

[1064] Output: Analyzed data (name, procedure details, etc.)

[1065] Step 4:

[1066] The server passes the extracted data to the generative AI model as a prompt sentence. Specifically, it generates a prompt sentence and inputs it into the generative AI model (e.g., GPT-3 or TensorFlow).

[1067] Input: Analyzed data (name, procedure details, etc.)

[1068] Output: prompt statement

[1069] Step 5:

[1070] The generative AI model generates an optimal preparation list based on the prompt sentence. Specifically, it uses natural language processing technology to generate the necessary preparation list and returns it to the server.

[1071] Input: prompt statement

[1072] Output: Preparation list

[1073] Step 6:

[1074] The server returns the created preparation list to the information processing terminal. Specifically, it converts the preparation list into JSON format and returns it as an HTTP response.

[1075] Input: List of preparations

[1076] Output: JSON format list of preparations

[1077] Step 7:

[1078] The information processing terminal displays the received preparation list to the user. Specifically, the preparation list is displayed in an application or web browser so that the user can check it.

[1079] Input: JSON format list of preparations

[1080] Output: A list of preparations that is displayed to the user

[1081] 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.

[1082] System Overview

[1083] This invention is a system that allows users to efficiently prepare documents and other items required for specific procedures by identifying them in advance. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more customized support. Each processing step and specific examples are described in detail below.

[1084] System configuration

[1085] This system mainly consists of the following elements:

[1086] 1. Terminal (user's smart device):

[1087] Displays a form for users to enter information.

[1088] The input information and the user's emotional data are sent to the server.

[1089] 2. Server:

[1090] Receive information and emotional data sent by the user.

[1091] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[1092] The generated preparation list is sent back to the user's smart device.

[1093] 3. Generative Model:

[1094] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user.

[1095] 4. Emotion Engine:

[1096] It has the ability to analyze the user's input and emotional patterns to determine the user's emotional state.

[1097] Program processing details

[1098] 1. Submitting the input form and entering information

[1099] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[1100] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[1101] 2. Acquiring Emotion Data

[1102] Emotion engine: Analyzes emotional patterns from user input to determine the user's emotional state. This emotional data is derived based on the user's typing speed, input content, etc.

[1103] 3. Sending input data and emotion data

[1104] On the device: When you click the submit button on the form, the collected information and analyzed emotion data are converted into JSON format and sent to the server as a POST request.

[1105] 4. Data reception and analysis by the server

[1106] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[1107] 5. Execution of the generative model by the server

[1108] Server: Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotion data, the server generates a customized preparation list.

[1109] 6. Return and display of preparation list

[1110] Server: Returns the generated preparation list to the user's smart device.

[1111] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[1112] Specific examples

[1113] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[1114] 2. The emotion engine analyzes the input and detects "stress."

[1115] 3. The device converts the collected information and emotion data into JSON format and sends it to the server.

[1116] 4. The server analyzes the received data and uses a generative model to generate a list of items to prepare, such as "suggested relaxation methods based on emotions" and "documents required for name change: driver's license, resident registration, seal certificate, etc."

[1117] 5. The server returns the generated list to the terminal.

[1118] 6. The device will display the returned list on the screen, making it easier for users to prepare in advance, and will also provide advice based on their emotions.

[1119] conclusion

[1120] The present invention provides an effective means for users to know in advance what documents and preparations are required for a specific procedure. Furthermore, it also recognizes the user's emotional state and provides customized support based on that, thereby improving the user experience. This allows users to prepare efficiently and proceed smoothly through the procedure.

[1121] The processing flow will be explained below.

[1122] Step 1:

[1123] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[1124] Step 2:

[1125] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[1126] Step 3:

[1127] Emotion engine (inside the device): Analyzes the input information and the user's behavioral data while inputting (such as input speed, typing intervals, frequency of errors, etc.) to determine the user's emotional state. For example, if the user makes many errors and the tempo is irregular while inputting, it will be determined that the user is feeling "stressed."

[1128] Step 4:

[1129] On the device: When the user clicks the submit button on the form, JavaScript is used to collect the form data and parsed emotion data, convert them into JSON format, and send them to the server.

[1130] Step 5:

[1131] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[1132] Step 6:

[1133] Server: Based on the acquired user information and emotional data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotional data, the server generates a customized preparation list that takes into account the user's emotional state.

[1134] Step 7:

[1135] Generative model (inside the server): Based on the information entered by the user, the generative model generates a list of necessary preparations, along with additional information based on emotions, such as "preferentially guide people who are feeling stressed through simple procedures."

[1136] Step 8:

[1137] Server: Returns the generated preparation list and emotion-based advice to the user's smart device.

[1138] Step 9:

[1139] Terminal: Receives the JSON data returned from the server, parses it using JavaScript, and displays a list of items to prepare and advice based on the emotion in an HTML document. Specifically, it displays advice such as "Try taking a deep breath to relax" along with "Documents required for name change: driver's license, resident registration, seal certificate, etc."

[1140] Step 10:

[1141] Users can check the preparation list and advice displayed on the device, gather the necessary documents and supplies in advance, or act according to their feelings, making the process smooth and efficient.

[1142] Example 2

[1143] 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."

[1144] Previous systems lacked an efficient way for users to understand in advance what documents and preparations were required when carrying out specific procedures. They also failed to provide appropriate support that took into account the user's emotional state, often causing inconvenience and stress. This led to users being inadequately prepared in advance, resulting in problems with procedures not proceeding smoothly.

[1145] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing collected information and generating a list of necessary preparations using a generative model, means for analyzing emotion data, and means for displaying customized advice based on the generated list of preparations and emotion data on the communication device. This allows the user to know in advance what documents and preparations they need and to receive appropriate support according to their emotional state.

[1146] "User" refers to a person who uses this system to enter the information required for a procedure.

[1147] "Communication device" refers to hardware such as a smart device that a user uses to input information.

[1148] "Input screen" refers to an interface for inputting information that is displayed on the display of a communication device.

[1149] "Collected Information" refers to all data provided by the user through the input screens.

[1150] "Server" refers to a computing system for receiving and analyzing collected information.

[1151] "Analysis" refers to the process of processing the collected information and generating a list of necessary preparations and emotional data.

[1152] "Generative Model" refers to an algorithm that uses natural language processing techniques to generate a list of necessary preparations and customized advice based on sentiment data.

[1153] A "preparation list" refers to a list of documents and items required when carrying out a procedure.

[1154] "Emotional data" refers to data on a user's mental state analyzed from the content and method of input.

[1155] "Customized advice" refers to specific assistance information provided individually based on the user's emotional data and input information.

[1156] The present invention is a system that allows users to efficiently prepare by identifying the documents and preparations required for a specific procedure in advance. It is also possible to analyze the user's emotional state in real time and provide customized support based on their emotions. The following describes the detailed processing content of the program of this system.

[1157] System configuration

[1158] The system mainly consists of the following elements:

[1159] 1. Communication Device (User's Smart Device):

[1160] Displays a screen for the user to enter information.

[1161] The input information and emotion data are sent to the server.

[1162] 2. Server:

[1163] Receive information and emotional data sent by the user.

[1164] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[1165] The generated preparation list is returned to the user's communication device.

[1166] 3. Generative Model:

[1167] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user. Large-scale language models such as GPT-3 can be used as this generation model.

[1168] 4. Emotion Engine:

[1169] It has the ability to analyze the user's input content, input speed, and patterns to determine the user's emotional state. This emotion engine uses emotion analysis models and machine learning algorithms.

[1170] Program processing details

[1171] Submitting the form and entering information

[1172] Communication device: When a user accesses the system, an input screen is displayed in the smart device browser using HTML and JavaScript. This screen contains input fields for identification information, age, type of change, etc.

[1173] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, "Identification information: User A," "Age: 30," "Type of change: Name change," etc. Placeholders and explanations are displayed in each field to make it easier for users to enter information.

[1174] Acquiring emotion data

[1175] Emotion engine: Analyzes user input. It uses input speed, patterns, and linguistic features to determine the user's emotional state using a machine learning model. For example, if the input speed is fast and the sentences are fragmented, it can detect stress.

[1176] Sending input data and emotion data

[1177] Communication device: When the submit button on the form is clicked, the collected information and analyzed emotion data are converted into JSON format and sent as a POST request to the server using a RESTful API.

[1178] Data reception and analysis

[1179] Server: Receives the POST request and checks the data integrity. A server-side program using Python or Node.js (e.g., Flask, Express.js) parses the JSON data and extracts the identity, age, type of change, and emotion data.

[1180] Running the generative model

[1181] Server: Based on the extracted user information and emotion data, the server passes prompts to the generative AI model. For example, a prompt such as "User information: User A, age 30, type of change: name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress state obtained from the emotion data" can be used for the generative AI model (such as GPT-3).

[1182] Generate and return a preparation list

[1183] Server: Receives the customized list of preparations as a response from the generative model, converts it into JSON format, and sends it back to the communication device. Specifically, it includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods according to emotions."

[1184] Displaying the preparation list

[1185] Communication device: Receives the list of items to be prepared returned from the server and displays it on the screen using HTML and JavaScript. Based on this information, users can prepare the items required for the procedure in advance.

[1186] The above is a detailed description of the processing procedure of the system of the present invention. By using this system, users can reduce the hassle of procedures and efficiently make the necessary preparations. In addition, by providing emotionally-based, customized support, the user experience can be improved.

[1187] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1188] Step 1:

[1189] Displaying the input screen

[1190] Terminal: When a user accesses the system, an input screen is displayed in the browser of the communication device (smart device) using HTML and JavaScript. This input screen includes input fields for identification information, age, type of change, etc., and is designed to make it easy for the user to input information.

[1191] Input: System access request from user

[1192] Output: Display of input screen

[1193] Step 2:

[1194] Entering information

[1195] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, enter "Identification information: User A," "Age: 30," and "Type of change: Name change." Placeholders and explanations are displayed in each field to make input easier.

[1196] Input: Information entered by the user

[1197] Output: The entered information is retained in the form

[1198] Step 3:

[1199] Acquiring emotion data

[1200] Emotion engine: Analyzes the user's input. The analysis method involves using a machine learning model to analyze input speed, input patterns, and writing style characteristics. For example, if the input speed is fast and the writing style is incomplete, it will determine that the user is feeling stressed.

[1201] Input: Information entered by the user

[1202] Output: Parsed emotion data (e.g., stress)

[1203] Step 4:

[1204] Sending input data and emotion data

[1205] On the device: When the user clicks the submit button on the form, the collected information and parsed sentiment data are converted into JSON format using JavaScript and sent as a POST request to the server via a RESTful API.

[1206] Input: Collected information and analyzed emotion data

[1207] Output: JSON data sent to the server

[1208] Step 5:

[1209] Data reception and analysis

[1210] Server: After receiving the POST request, the server first checks the integrity of the data. After the data integrity is confirmed, a server-side program such as Python or Node.js parses the JSON data and extracts the identity, age, type of change, and emotion data.

[1211] Input: JSON data sent from the terminal

[1212] Output: Extracted user information and sentiment data

[1213] Step 6:

[1214] Running the generative model

[1215] Server: Based on the extracted user information and emotion data, the server creates and passes a prompt to the generative AI model. This prompt includes the information and emotion data provided by the user. For example, the server might pass a prompt such as, "User information: Identification: User A, Age: 30, Type of change: Name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress level obtained from the emotion data."

[1216] Input: Extracted user information and emotion data

[1217] Output: A preparation list and customized advice generated by the generative AI model

[1218] Step 7:

[1219] Generate and return a preparation list

[1220] Server: Converts the list of preparations and customized advice obtained from the generative AI model into JSON format and sends it back to the communication device. Specifically, this includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods based on emotions."

[1221] Input: A list of preparations and customized advice output by the generative AI model

[1222] Output: JSON data sent to the communication device

[1223] Step 8:

[1224] Displaying the preparation list

[1225] Terminal: Receives the data returned from the server and displays a list of preparations and advice on the screen using HTML and JavaScript. By checking this information in advance, users can efficiently make the necessary preparations.

[1226] Input: JSON data returned from the server

[1227] Output: Preparation list and customized advice displayed on the communication device screen

[1228] (Application example 2)

[1229] 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."

[1230] It is difficult for users to know in advance what documents and preparations are required when carrying out a specific procedure, and if there are any inaccuracies, the procedure may not proceed smoothly. In addition, there is a lack of support to reduce the stress and anxiety users feel when carrying out procedures and to help them prepare more efficiently. For this reason, there is a need for a system that allows users to efficiently prepare the necessary items in advance and at the same time receive appropriate advice based on their emotions.

[1231] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input information into an input form using an information terminal, means for transmitting information and emotion data collected from the input form to the server, means for the server to analyze the collected information and emotion data and generate a list of necessary preparations and advice corresponding to the emotion using a generative model, and means for displaying the generated list of necessary preparations and advice corresponding to the emotion on the user's information terminal. This allows the user to efficiently prepare the necessary preparations in advance, making preparations to smoothly proceed with the procedure, and enabling stress and anxiety to be reduced by receiving appropriate advice corresponding to the emotion.

[1232] "User" refers to an individual or organization that uses the system to carry out a specific procedure.

[1233] An "information terminal" is a device such as a smartphone, tablet, or PC that allows users to input information and send and receive data.

[1234] An "input form" is a screen or interface that allows a user to enter specific information, including data fields such as name, age, and type of procedure.

[1235] The "server" is a computer system that analyzes the received information and emotion data and uses a generative model to generate a list of necessary preparations and advice based on the emotion.

[1236] "Collected Information" refers to data provided by users through input forms, including information such as name, age, and type of procedure.

[1237] "Emotional data" is data that represents the user's emotional state and is analyzed based on the speed and content of input.

[1238] A "generative model" is an algorithm that uses natural language processing technology to generate a list of necessary preparations and advice based on emotions based on input information and emotional data.

[1239] A "preparation list" is a list of documents and items that a user needs to carry out a specific procedure.

[1240] An "emotion engine" is software that has the function of analyzing the user's input content and input patterns to determine the user's emotional state.

[1241] "Emotionally-responsive advice" refers to appropriate support and suggestions provided based on the user's emotional state.

[1242] System Overview

[1243] The system that realizes this invention allows users to efficiently prepare the necessary documents and preparations for specific procedures in advance. It also provides more customized support by combining it with an emotion engine that recognizes the user's emotions.

[1244] System configuration

[1245] This system mainly consists of the following elements:

[1246] 1. Information terminal (user terminal):

[1247] Displays a form for users to enter information.

[1248] The input information and emotion data are sent to the server.

[1249] 2. Server:

[1250] Receive information and emotional data sent by the user.

[1251] The collected information and emotional data are analyzed, and a generative model is used to generate a preparation list and emotional advice.

[1252] The generated preparation list and advice according to the emotion are returned to the user's information terminal.

[1253] 3. Generative Model:

[1254] An algorithm that uses natural language processing technology to generate optimal preparation lists and emotional advice based on the information and emotional state entered by the user.

[1255] 4. Emotion Engine:

[1256] It has the ability to analyze the user's input content and input patterns to determine the user's emotional state.

[1257] Program processing details

[1258] When a user enters information into an input form using an information terminal, emotional data is obtained from the input content and the speed and content of the input. This data is converted into JSON format and sent to the server. The server analyzes the received data and generates prompts appropriate for the generative model. The generative model uses natural language processing technology to generate a list of necessary preparations and advice based on the emotion.

[1259] The hardware and software used are as follows:

[1260] Hardware: Smartphones, tablets, computers

[1261] Software: Python, TextBlob library, JSON library

[1262] Specific examples

[1263] For example, a user accesses the system to change their name and enters the following information: "Name: Yamada Taro," "Age: 30," and "Type of change: Name change." If the emotion engine detects "stress" at this time, the input details and emotional data are collected. Based on the collected information, the server then generates "Documents required for name change: Driver's license, resident registration, and seal certificate" and "Suggested relaxation methods to reduce stress," which are displayed on the user's information terminal.

[1264] Here is an example of a prompt to input to the generative model:

[1265] What documents do users need to complete the name change and what would you suggest to help them relax if they are feeling stressed from the input?

[1266] Example input:

[1267] Name: Yamada Hanako

[1268] Age: 28

[1269] Type of change: Name change

[1270] Emotion: Stress

[1271] Example answer:

[1272] Required documents: Driver's license, resident card, seal certificate

[1273] Emotional advice: Take deep breaths, listen to relaxing music

[1274] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1275] Step 1:

[1276] The user enters information into the form

[1277] A user uses an information device (smartphone, tablet, PC) to enter information such as name, age, type of procedure, etc. into an input form. This form contains multiple fields for the user to fill out.

[1278] (Input) Information such as name, age, type of procedure, etc.

[1279] (Output) A set of input information

[1280] Step 2:

[1281] Acquiring emotion data

[1282] The information terminal analyzes the user's input content and input speed and uses an emotion engine to determine the user's emotional state, extracting emotions such as stress and anxiety from the input content and speed.

[1283] (Input) Patterns of information entered by the user, such as input speed

[1284] (Output) Emotion data (e.g., "stress," "anxiety")

[1285] Step 3:

[1286] Sending input data and emotion data

[1287] The information terminal converts the collected information and emotion data into JSON format and sends it to the server as a POST request.

[1288] (Input) Information entered by the user, emotional data

[1289] (Output) JSON format data

[1290] Step 4:

[1291] Data reception and analysis by the server

[1292] The server parses the POST request received and extracts the JSON data, from which the name, age, procedure type, and emotion data are obtained.

[1293] (Input) JSON format data

[1294] (Output) Analyzed user information and emotion data

[1295] Step 5:

[1296] Running the generative model

[1297] Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model, which uses natural language processing technology to generate a list of necessary preparations and emotion-based advice.

[1298] (Input) User information and emotion data

[1299] (Output) Preparation list and emotional advice

[1300] Step 6:

[1301] Return and display of preparation list and advice

[1302] The server returns the prepared list and advice according to the user's emotion to the user's information terminal. The information terminal displays the returned list and advice on the screen, making it easier for the user to prepare in advance. The server also provides advice according to the user's emotion.

[1303] (Input) Generated preparation list and advice based on emotions

[1304] (Output) A list of preparations and advice based on emotions displayed on the device

[1305] The above are the specific processing steps that explain how the system program works. At each step, the input and output are clearly defined, and data processing and calculations are performed based on them.

[1306] 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.

[1307] 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.

[1308] 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.

[1309] [Fourth embodiment]

[1310] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1311] 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.

[1312] 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).

[1313] 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.

[1314] 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.

[1315] 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).

[1316] 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.

[1317] 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.

[1318] 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.

[1319] 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.

[1320] 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.

[1321] 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.

[1322] 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."

[1323] System Overview

[1324] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. Users input information into an input form using a smart device, and a list of necessary items is generated and displayed based on that information. Each processing step and specific examples are described in detail below.

[1325] System configuration

[1326] This system mainly consists of the following elements:

[1327] 1. Terminal (user's smart device):

[1328] Displays a form for users to enter information.

[1329] The entered information is sent to the server.

[1330] 2. Server:

[1331] Receive information sent by users.

[1332] The information is analyzed and a generative model is used to generate a list of necessary preparations.

[1333] The generated preparation list is sent back to the user's smart device.

[1334] 3. Generative Model:

[1335] An algorithm that uses natural language processing technology to generate the optimal preparation list based on the information entered by the user.

[1336] Program processing details

[1337] 1. Submitting the input form and entering information

[1338] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[1339] User: Enter the required information into the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[1340] 2. Sending input data

[1341] On the device: When the submit button on the form is clicked, the user's input data is converted to JSON format and sent to the server as a POST request.

[1342] 3. Data reception and analysis by the server

[1343] Server: Parses the received JSON data and obtains the user's input information. This information is passed to the generative model to generate a list of necessary preparations.

[1344] 4. Running the Generative Model

[1345] Generative model: Using natural language processing technology, the system generates an optimal list of items to prepare based on information provided by the user. For example, it includes specific information such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[1346] 5. Return and display of preparation list

[1347] Server: Returns the generated preparation list to the user's smart device.

[1348] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[1349] Specific examples

[1350] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[1351] 2. The device converts the input information into JSON format and sends it to the server.

[1352] 3. The server analyzes the received data and uses a generative model to generate a list of documents required for the name change: driver's license, resident registration card, seal certificate, etc.

[1353] 4. The server returns the generated list of preparations to the user's terminal.

[1354] 5. The device will display the returned list on the screen, making it easier for users to prepare in advance.

[1355] conclusion

[1356] The present invention provides an effective means for users to know in advance what documents and preparations are required when carrying out a specific procedure, thereby enabling users to make efficient preparations and smoothly proceed with the procedure.

[1357] The processing flow will be explained below.

[1358] Step 1:

[1359] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[1360] Step 2:

[1361] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[1362] Step 3:

[1363] On the device: When the user clicks the submit button on the form, JavaScript is used to collect the form data, convert it to JSON format, and send this JSON data to the server as a POST request.

[1364] Step 4:

[1365] Server: Parse the received POST request and extract the JSON data. From the parsed data, get the user information such as name, age, and type of change.

[1366] Step 5:

[1367] Server: Based on the acquired user information, it passes appropriate prompts to the generative model, which uses natural language processing techniques to generate a list of items to be prepared.

[1368] Step 6:

[1369] Generative model (on the server): The generative model uses natural language processing technology to generate a list of items to prepare based on the input information. For example, it generates content such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[1370] Step 7:

[1371] Server: Receives the generated list of preparations, converts it to JSON format, and returns it to the terminal.

[1372] Step 8:

[1373] On the device: Receive the JSON data returned from the server and parse it using JavaScript. Get the list of preparations from the parsed data and display it on the user's device.

[1374] Step 9:

[1375] User: Check the list of items to prepare displayed on the device and prepare the necessary documents and items in advance, which will help the process go smoothly.

[1376] Example 1

[1377] 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."

[1378] When users go through procedures, it is difficult to know in advance what documents and preparations are required, which can cause the procedures to not proceed smoothly. In addition, insufficient preparations often result in duplicate work, making the procedures inefficient. This increases the burden on users.

[1379] 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.

[1380] In this invention, the server includes: means for a user to input information into an input form using a mobile information terminal; means for transmitting information collected from the input form to a processing device; means for the processing device to analyze the collected information and generate a list of necessary preparations using a generative AI model; means for the processing device to display the generated list of preparations on the user's mobile information terminal; and means for the generative AI model to generate the list of preparations using a prompt sentence for the server. This allows the user to efficiently grasp in advance the preparations required when performing a procedure, making it possible to smoothly proceed with the procedure and avoiding duplicate work.

[1381] A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, that a user uses to input and display information.

[1382] An "input form" is an interface through which a user enters information, and includes input fields such as name, age, type of change, etc.

[1383] A "processing device" is a device, such as a server, that receives and analyzes the data sent by the user and generates the required preparation list using a generative AI model.

[1384] A "generative AI model" is an algorithm or artificial intelligence model that uses natural language processing technology to generate an optimal preparation list based on information provided by the user.

[1385] A "prompt" is an instruction input to a generative AI model, and is text that specifically requests a list of necessary preparations based on the user's input information.

[1386] A "preparation list" is a list of documents and other items that a user needs to carry out a specific procedure.

[1387] "Analyzing information" is the process of understanding, categorizing, and converting user-entered data into a usable format.

[1388] "Collected Information" refers to data provided by users through input forms.

[1389] This invention is a system that allows users to efficiently prepare documents and other items required for a specific procedure by identifying them in advance. This system is primarily composed of a mobile information terminal, a processing device (server), and a generative AI model. Below, we provide a detailed explanation and specific examples of each element.

[1390] System Overview

[1391] A user uses a mobile information terminal (such as a smartphone or tablet) to input information into an input form. The input form contains multiple input fields, such as name, age, and type of change, and the user enters this information. Once the user has completed the input, the terminal converts the input information into JSON format and sends it to a processing device.

[1392] Hardware and software used

[1393] 1. Personal digital assistant: A device used by a user to enter and display information, such as a smartphone or tablet.

[1394] 2. Processing device (server): Responsible for receiving data, analyzing it, processing it using a generative AI model, and sending a response. Specifically, a server-side framework such as Express.js is used.

[1395] 3. Generative AI model: An algorithm that uses natural language processing technology to generate a preparation list. The generative AI model generates the optimal preparation list based on the prompt sentence.

[1396] Specific operation of the system

[1397] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[1398] 2. The device converts the input information into JSON format and sends it to the processing device, which then sends the input data to the server.

[1399] 3. The server parses the received data and extracts the user's input, including data such as name, age, and type of change.

[1400] 4. The server uses the generative AI model to create a prompt based on the user's input. An example prompt might look like this:

[1401] "Please list the necessary preparations according to the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[1402] 5. The generative AI model generates an optimal list of items to prepare based on the prompt. Specifically, it generates a list such as "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[1403] 6. The server returns the generated list of preparations to the user's device. The returned list is sent as a JSON response.

[1404] 7. The terminal analyzes the received preparation list and displays it on the screen of the user's smart device. The user can refer to this list and prepare the necessary documents in advance.

[1405] This system allows users to efficiently understand in advance what preparations they need to make when carrying out a procedure, allowing the procedure to proceed smoothly and avoiding duplicate work.

[1406] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1407] Step 1:

[1408] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains several input fields such as name, age, and type of change.

[1409] Input: User accesses the browser.

[1410] Output: The input form is displayed in the browser.

[1411] Step 2:

[1412] User: Enter the required information in the input form. For example, enter information such as "Name: Yamada Taro", "Age: 30", and "Type of change: Name change".

[1413] Input: Name, Age, Change Type information.

[1414] Output: User enters information into a form.

[1415] Step 3:

[1416] On the device: When you click the submit button on the form, JavaScript triggers this event, converting the input data into JSON format, which is then sent to the server as a POST request.

[1417] Input: User presses submit button.

[1418] Output: JSON formatted data is generated and sent to the server.

[1419] Step 4:

[1420] Server: Receives JSON format data sent from the device.

[1421] Input: JSON data from the terminal.

[1422] Output: The received data.

[1423] Step 5:

[1424] Server: Parses the received JSON data and extracts the user's input information, such as name, age, and type of change.

[1425] Input: The received JSON data.

[1426] Output: The extracted user information.

[1427] Step 6:

[1428] Server: Creates a prompt for the generative AI model based on the user's input. Specifically, it would say something like, "Please list the necessary preparations based on the user's name, age, and type of change. For example, Name: Yamada Taro, Age: 30, Type of change: Name change."

[1429] Input: Extracted user information.

[1430] Output: The generated prompt statement.

[1431] Step 7:

[1432] Generative AI model: Analyzes the prompt and generates a list of the necessary documents. For example, it generates "Documents required for name change: driver's license, resident registration card, seal certificate, etc."

[1433] Input: prompt statement.

[1434] Output: The generated preparation list.

[1435] Step 8:

[1436] Server: Receives the generated list of preparations and returns it to the terminal as a response in JSON format.

[1437] Input: The generated preparation list.

[1438] Output: Response in JSON format.

[1439] Step 9:

[1440] Terminal: Analyzes the received JSON format preparation list and displays it on the screen of the user's smart device.

[1441] Input: The JSON response from the server.

[1442] Output: A list of preparations will be displayed on the screen.

[1443] (Application example 1)

[1444] 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."

[1445] In today's diverse procedures, users are required to know in advance what documents and items they need and prepare them efficiently. However, with conventional methods, users often spend a significant amount of time and effort checking what items they need, which causes the process at the store to take longer. To solve this problem and allow users to prepare efficiently, a system that automatically generates and provides a list of items to be prepared is needed.

[1446] 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.

[1447] In this invention, the server includes means for a user to input information into an input form using an information processing terminal, means for transmitting information collected from the input form to a data analysis device, means for the data analysis device to analyze the collected information and generate a list of necessary preparations using natural language processing technology, means for displaying the generated list of preparations on the user's information processing terminal, and means for providing a list of preparations necessary for procedures at a physical store based on the information input by the user. This enables the user to know in advance the documents and preparations they will need and to make efficient preparations.

[1448] An "information processing terminal" is a device that allows a user to input information and communicate with a server.

[1449] "Data analysis device" refers to a device for analyzing collected information and generating a preparation list.

[1450] "Natural language processing technology" refers to the technology that allows computers to understand and generate human language.

[1451] A "preparation list" is a list of documents and items required to carry out a specific procedure.

[1452] A "question answer generation algorithm" is an algorithm for generating the optimal answer to an input question.

[1453] A "field" is an item on an input form where a user enters specific information.

[1454] "Name" means the name of the User.

[1455] "Procedure type" is an item that indicates the type of specific procedure that the user is going to perform.

[1456] This invention provides a system for efficiently preparing documents and items required for a specific procedure. In this system, a user inputs information into a form using an information processing terminal, the data is sent to a server, analyzed, and a generative model is used to generate and display a list of necessary items. Detailed embodiments are described below.

[1457] System Overview

[1458] The system mainly consists of the following elements:

[1459] 1. Information processing terminal: A device through which a user inputs information and communicates with a server. Specific devices include smartphones, tablets, and PCs.

[1460] 2. Data analysis device: A device that analyzes collected information and generates a list of preparations. Specifically, it is a system built by a server.

[1461] 3. Generative AI model: An algorithm that uses natural language processing technology to generate an optimal preparation list.

[1462] Program Description

[1463] Hardware and Software Use

[1464] Information processing devices (e.g. smartphones, tablets, PCs)

[1465] This is a terminal where users input information and send it to the data analysis device. A browser and dedicated applications are installed on this terminal.

[1466] Data analysis equipment (e.g., server)

[1467] The information sent by the user is analyzed and a preparation list is generated using a generative AI model. The server has a backend system built using Node.js and Express.

[1468] Generative AI models (e.g., GPT-3, TensorFlow)

[1469] This is an algorithm that uses natural language processing technology to generate a list of necessary preparations based on information entered by the user.

[1470] Specific examples of processing

[1471] 1. The user uses the information processing terminal to enter information into the input form. For example, the user selects "name change" as the procedure and enters the user's name and other required items.

[1472] 2. The device converts the input information into JSON format and sends it to the server as a POST request.

[1473] 3. The server analyzes the received data and inputs it as a prompt sentence into the generative AI model.

[1474] 4. The generative AI model generates an optimal preparation list based on the input prompt.

[1475] 5. The server returns the prepared item list to the information processing terminal.

[1476] 6. The information processing terminal displays the received preparation list on the screen and provides it to the user.

[1477] Context and prompt example

[1478] Specific prompt examples:

[1479] Name: Yamada Taro, Procedure: Name change

[1480] This invention allows users to efficiently prepare the documents and materials required for the procedure in advance, thereby shortening the time required for the procedure at a physical store. The above is a detailed description of the embodiment of the present invention.

[1481] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1482] Step 1:

[1483] The user uses an information processing terminal to input information into the input form. Specifically, the user enters necessary information such as name and procedure details into the input fields. This information becomes the initial input data for the system.

[1484] Input: Name, procedure details, and other information

[1485] Output: Data entered by the user

[1486] Step 2:

[1487] The terminal converts the information entered by the user into JSON format and sends it to the data analysis device. Specifically, the information entered in the input fields is sent to the server as a POST request.

[1488] Input: Data entered by the user

[1489] Output: JSON format data

[1490] Step 3:

[1491] The server parses the received JSON data and extracts the necessary information. Specifically, it uses Node.js and Express to parse the data and extract the necessary fields (name, procedure details, etc.).

[1492] Input: JSON format data

[1493] Output: Analyzed data (name, procedure details, etc.)

[1494] Step 4:

[1495] The server passes the extracted data to the generative AI model as a prompt sentence. Specifically, it generates a prompt sentence and inputs it into the generative AI model (e.g., GPT-3 or TensorFlow).

[1496] Input: Analyzed data (name, procedure details, etc.)

[1497] Output: prompt statement

[1498] Step 5:

[1499] The generative AI model generates an optimal preparation list based on the prompt sentence. Specifically, it uses natural language processing technology to generate the necessary preparation list and returns it to the server.

[1500] Input: prompt statement

[1501] Output: Preparation list

[1502] Step 6:

[1503] The server returns the created preparation list to the information processing terminal. Specifically, it converts the preparation list into JSON format and returns it as an HTTP response.

[1504] Input: List of preparations

[1505] Output: JSON format list of preparations

[1506] Step 7:

[1507] The information processing terminal displays the received preparation list to the user. Specifically, the preparation list is displayed in an application or web browser so that the user can check it.

[1508] Input: JSON format list of preparations

[1509] Output: A list of preparations that is displayed to the user

[1510] 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.

[1511] System Overview

[1512] This invention is a system that allows users to efficiently prepare documents and other items required for specific procedures by identifying them in advance. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more customized support. Each processing step and specific examples are described in detail below.

[1513] System configuration

[1514] This system mainly consists of the following elements:

[1515] 1. Terminal (user's smart device):

[1516] Displays a form for users to enter information.

[1517] The input information and the user's emotional data are sent to the server.

[1518] 2. Server:

[1519] Receive information and emotional data sent by the user.

[1520] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[1521] The generated preparation list is sent back to the user's smart device.

[1522] 3. Generative Model:

[1523] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user.

[1524] 4. Emotion Engine:

[1525] It has the ability to analyze the user's input and emotional patterns to determine the user's emotional state.

[1526] Program processing details

[1527] 1. Submitting the input form and entering information

[1528] Terminal: When a user accesses the system, an input form is displayed in the browser of the smart device, which contains multiple input fields such as name, age, and type of change.

[1529] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[1530] 2. Acquiring Emotion Data

[1531] Emotion engine: Analyzes emotional patterns from user input to determine the user's emotional state. This emotional data is derived based on the user's typing speed, input content, etc.

[1532] 3. Sending input data and emotion data

[1533] On the device: When you click the submit button on the form, the collected information and analyzed emotion data are converted into JSON format and sent to the server as a POST request.

[1534] 4. Data reception and analysis by the server

[1535] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[1536] 5. Execution of the generative model by the server

[1537] Server: Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotion data, the server generates a customized preparation list.

[1538] 6. Return and display of preparation list

[1539] Server: Returns the generated preparation list to the user's smart device.

[1540] Terminal: The returned preparation list is displayed on the screen, providing reference information for the user to prepare in advance, allowing the user to gather all necessary documents before visiting the store and avoiding duplicate work.

[1541] Specific examples

[1542] 1. The user accesses the system and enters "Name: Yamada Taro," "Age: 30," and "Type of change: Name change" into the input form displayed in the smart device's browser.

[1543] 2. The emotion engine analyzes the input and detects "stress."

[1544] 3. The device converts the collected information and emotion data into JSON format and sends it to the server.

[1545] 4. The server analyzes the received data and uses a generative model to generate a list of items to prepare, such as "suggested relaxation methods based on emotions" and "documents required for name change: driver's license, resident registration, seal certificate, etc."

[1546] 5. The server returns the generated list to the terminal.

[1547] 6. The device will display the returned list on the screen, making it easier for users to prepare in advance, and will also provide advice based on their emotions.

[1548] conclusion

[1549] The present invention provides an effective means for users to know in advance what documents and preparations are required for a specific procedure. Furthermore, it also recognizes the user's emotional state and provides customized support based on that, thereby improving the user experience. This allows users to prepare efficiently and proceed smoothly through the procedure.

[1550] The processing flow will be explained below.

[1551] Step 1:

[1552] Terminal: When a user accesses the system, the browser on the smart device displays an input form, which contains multiple input fields such as name, age, and type of change.

[1553] Step 2:

[1554] User: Enter the required information in the displayed input form, such as name, age, type of change, etc. For example, enter "Name: Yamada Taro", "Age: 30", "Type of change: Name change".

[1555] Step 3:

[1556] Emotion engine (inside the device): Analyzes the input information and the user's behavioral data while inputting (such as input speed, typing intervals, frequency of errors, etc.) to determine the user's emotional state. For example, if the user makes many errors and the tempo is irregular while inputting, it will be determined that the user is feeling "stressed."

[1557] Step 4:

[1558] On the device: When the user clicks the submit button on the form, JavaScript is used to collect the form data and parsed emotion data, convert them into JSON format, and send them to the server.

[1559] Step 5:

[1560] Server: Parses the received POST request and extracts the JSON data. From the parsed data, obtain the name, age, type of change, and emotion data.

[1561] Step 6:

[1562] Server: Based on the acquired user information and emotional data, the server passes appropriate prompts to the generative model to generate a preparation list using natural language processing technology. Based on the emotional data, the server generates a customized preparation list that takes into account the user's emotional state.

[1563] Step 7:

[1564] Generative model (inside the server): Based on the information entered by the user, the generative model generates a list of necessary preparations, along with additional information based on emotions, such as "preferentially guide people who are feeling stressed through simple procedures."

[1565] Step 8:

[1566] Server: Returns the generated preparation list and emotion-based advice to the user's smart device.

[1567] Step 9:

[1568] Terminal: Receives the JSON data returned from the server, parses it using JavaScript, and displays a list of items to prepare and advice based on the emotion in an HTML document. Specifically, it displays advice such as "Try taking a deep breath to relax" along with "Documents required for name change: driver's license, resident registration, seal certificate, etc."

[1569] Step 10:

[1570] Users can check the preparation list and advice displayed on the device, gather the necessary documents and supplies in advance, or act according to their feelings, making the process smooth and efficient.

[1571] Example 2

[1572] 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."

[1573] Previous systems lacked an efficient way for users to understand in advance what documents and preparations were required when carrying out specific procedures. They also failed to provide appropriate support that took into account the user's emotional state, often causing inconvenience and stress. This led to users being inadequately prepared in advance, resulting in problems with procedures not proceeding smoothly.

[1574] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing collected information and generating a list of necessary preparations using a generative model, means for analyzing emotion data, and means for displaying customized advice based on the generated list of preparations and emotion data on the communication device. This allows the user to know in advance what documents and preparations they need and to receive appropriate support according to their emotional state.

[1575] "User" refers to a person who uses this system to enter the information required for a procedure.

[1576] "Communication device" refers to hardware such as a smart device that a user uses to input information.

[1577] "Input screen" refers to an interface for inputting information that is displayed on the display of a communication device.

[1578] "Collected Information" refers to all data provided by the user through the input screens.

[1579] "Server" refers to a computing system for receiving and analyzing collected information.

[1580] "Analysis" refers to the process of processing the collected information and generating a list of necessary preparations and emotional data.

[1581] "Generative Model" refers to an algorithm that uses natural language processing techniques to generate a list of necessary preparations and customized advice based on sentiment data.

[1582] A "preparation list" refers to a list of documents and items required when carrying out a procedure.

[1583] "Emotional data" refers to data on a user's mental state analyzed from the content and method of input.

[1584] "Customized advice" refers to specific assistance information provided individually based on the user's emotional data and input information.

[1585] The present invention is a system that allows users to efficiently prepare by identifying the documents and preparations required for a specific procedure in advance. It is also possible to analyze the user's emotional state in real time and provide customized support based on their emotions. The following describes the detailed processing content of the program of this system.

[1586] System configuration

[1587] The system mainly consists of the following elements:

[1588] 1. Communication Device (User's Smart Device):

[1589] Displays a screen for the user to enter information.

[1590] The input information and emotion data are sent to the server.

[1591] 2. Server:

[1592] Receive information and emotional data sent by the user.

[1593] The collected information and sentiment data are analyzed, and a generative model is used to generate a preparation list.

[1594] The generated preparation list is returned to the user's communication device.

[1595] 3. Generative Model:

[1596] An algorithm that uses natural language processing technology to generate an optimal preparation list based on the information and emotional state entered by the user. Large-scale language models such as GPT-3 can be used as this generation model.

[1597] 4. Emotion Engine:

[1598] It has the ability to analyze the user's input content, input speed, and patterns to determine the user's emotional state. This emotion engine uses emotion analysis models and machine learning algorithms.

[1599] Program processing details

[1600] Submitting the form and entering information

[1601] Communication device: When a user accesses the system, an input screen is displayed in the smart device browser using HTML and JavaScript. This screen contains input fields for identification information, age, type of change, etc.

[1602] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, "Identification information: User A," "Age: 30," "Type of change: Name change," etc. Placeholders and explanations are displayed in each field to make it easier for users to enter information.

[1603] Acquiring emotion data

[1604] Emotion engine: Analyzes user input. It uses input speed, patterns, and linguistic features to determine the user's emotional state using a machine learning model. For example, if the input speed is fast and the sentences are fragmented, it can detect stress.

[1605] Sending input data and emotion data

[1606] Communication device: When the submit button on the form is clicked, the collected information and analyzed emotion data are converted into JSON format and sent as a POST request to the server using a RESTful API.

[1607] Data reception and analysis

[1608] Server: Receives the POST request and checks the data integrity. A server-side program using Python or Node.js (e.g., Flask, Express.js) parses the JSON data and extracts the identity, age, type of change, and emotion data.

[1609] Running the generative model

[1610] Server: Based on the extracted user information and emotion data, the server passes prompts to the generative AI model. For example, a prompt such as "User information: User A, age 30, type of change: name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress state obtained from the emotion data" can be used for the generative AI model (such as GPT-3).

[1611] Generate and return a preparation list

[1612] Server: Receives the customized list of preparations as a response from the generative model, converts it into JSON format, and sends it back to the communication device. Specifically, it includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods according to emotions."

[1613] Displaying the preparation list

[1614] Communication device: Receives the list of items to be prepared returned from the server and displays it on the screen using HTML and JavaScript. Based on this information, users can prepare the items required for the procedure in advance.

[1615] The above is a detailed description of the processing procedure of the system of the present invention. By using this system, users can reduce the hassle of procedures and efficiently make the necessary preparations. In addition, by providing emotionally-based, customized support, the user experience can be improved.

[1616] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1617] Step 1:

[1618] Displaying the input screen

[1619] Terminal: When a user accesses the system, an input screen is displayed in the browser of the communication device (smart device) using HTML and JavaScript. This input screen includes input fields for identification information, age, type of change, etc., and is designed to make it easy for the user to input information.

[1620] Input: System access request from user

[1621] Output: Display of input screen

[1622] Step 2:

[1623] Entering information

[1624] User: Enter the required information using a keyboard or touch input on the displayed input screen. For example, enter "Identification information: User A," "Age: 30," and "Type of change: Name change." Placeholders and explanations are displayed in each field to make input easier.

[1625] Input: Information entered by the user

[1626] Output: The entered information is retained in the form

[1627] Step 3:

[1628] Acquiring emotion data

[1629] Emotion engine: Analyzes the user's input. The analysis method involves using a machine learning model to analyze input speed, input patterns, and writing style characteristics. For example, if the input speed is fast and the writing style is incomplete, it will determine that the user is feeling stressed.

[1630] Input: Information entered by the user

[1631] Output: Parsed emotion data (e.g., stress)

[1632] Step 4:

[1633] Sending input data and emotion data

[1634] On the device: When the user clicks the submit button on the form, the collected information and parsed sentiment data are converted into JSON format using JavaScript and sent as a POST request to the server via a RESTful API.

[1635] Input: Collected information and analyzed emotion data

[1636] Output: JSON data sent to the server

[1637] Step 5:

[1638] Data reception and analysis

[1639] Server: After receiving the POST request, the server first checks the integrity of the data. After the data integrity is confirmed, a server-side program such as Python or Node.js parses the JSON data and extracts the identity, age, type of change, and emotion data.

[1640] Input: JSON data sent from the terminal

[1641] Output: Extracted user information and sentiment data

[1642] Step 6:

[1643] Running the generative model

[1644] Server: Based on the extracted user information and emotion data, the server creates and passes a prompt to the generative AI model. This prompt includes the information and emotion data provided by the user. For example, the server might pass a prompt such as, "User information: Identification: User A, Age: 30, Type of change: Name change. Please generate a list of documents that need to be prepared and relaxation methods based on the stress level obtained from the emotion data."

[1645] Input: Extracted user information and emotion data

[1646] Output: A preparation list and customized advice generated by the generative AI model

[1647] Step 7:

[1648] Generate and return a preparation list

[1649] Server: Converts the list of preparations and customized advice obtained from the generative AI model into JSON format and sends it back to the communication device. Specifically, this includes data such as "required documents: ID card, resident registration card, seal certificate, and suggested relaxation methods based on emotions."

[1650] Input: A list of preparations and customized advice output by the generative AI model

[1651] Output: JSON data sent to the communication device

[1652] Step 8:

[1653] Displaying the preparation list

[1654] Terminal: Receives the data returned from the server and displays a list of preparations and advice on the screen using HTML and JavaScript. By checking this information in advance, users can efficiently make the necessary preparations.

[1655] Input: JSON data returned from the server

[1656] Output: Preparation list and customized advice displayed on the communication device screen

[1657] (Application example 2)

[1658] 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."

[1659] It is difficult for users to know in advance what documents and preparations are required when carrying out a specific procedure, and if there are any inaccuracies, the procedure may not proceed smoothly. In addition, there is a lack of support to reduce the stress and anxiety users feel when carrying out procedures and to help them prepare more efficiently. For this reason, there is a need for a system that allows users to efficiently prepare the necessary items in advance and at the same time receive appropriate advice based on their emotions.

[1660] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input information into an input form using an information terminal, means for transmitting information and emotion data collected from the input form to the server, means for the server to analyze the collected information and emotion data and generate a list of necessary preparations and advice corresponding to the emotion using a generative model, and means for displaying the generated list of necessary preparations and advice corresponding to the emotion on the user's information terminal. This allows the user to efficiently prepare the necessary preparations in advance, making preparations to smoothly proceed with the procedure, and enabling stress and anxiety to be reduced by receiving appropriate advice corresponding to the emotion.

[1661] "User" refers to an individual or organization that uses the system to carry out a specific procedure.

[1662] An "information terminal" is a device such as a smartphone, tablet, or PC that allows users to input information and send and receive data.

[1663] An "input form" is a screen or interface that allows a user to enter specific information, including data fields such as name, age, and type of procedure.

[1664] The "server" is a computer system that analyzes the received information and emotion data and uses a generative model to generate a list of necessary preparations and advice based on the emotion.

[1665] "Collected Information" refers to data provided by users through input forms, including information such as name, age, and type of procedure.

[1666] "Emotional data" is data that represents the user's emotional state and is analyzed based on the speed and content of input.

[1667] A "generative model" is an algorithm that uses natural language processing technology to generate a list of necessary preparations and advice based on emotions based on input information and emotional data.

[1668] A "preparation list" is a list of documents and items that a user needs to carry out a specific procedure.

[1669] An "emotion engine" is software that has the function of analyzing the user's input content and input patterns to determine the user's emotional state.

[1670] "Emotionally-responsive advice" refers to appropriate support and suggestions provided based on the user's emotional state.

[1671] System Overview

[1672] The system that realizes this invention allows users to efficiently prepare the necessary documents and preparations for specific procedures in advance. It also provides more customized support by combining it with an emotion engine that recognizes the user's emotions.

[1673] System configuration

[1674] This system mainly consists of the following elements:

[1675] 1. Information terminal (user terminal):

[1676] Displays a form for users to enter information.

[1677] The input information and emotion data are sent to the server.

[1678] 2. Server:

[1679] Receive information and emotional data sent by the user.

[1680] The collected information and emotional data are analyzed, and a generative model is used to generate a preparation list and emotional advice.

[1681] The generated preparation list and advice according to the emotion are returned to the user's information terminal.

[1682] 3. Generative Model:

[1683] An algorithm that uses natural language processing technology to generate optimal preparation lists and emotional advice based on the information and emotional state entered by the user.

[1684] 4. Emotion Engine:

[1685] It has the ability to analyze the user's input content and input patterns to determine the user's emotional state.

[1686] Program processing details

[1687] When a user enters information into an input form using an information terminal, emotional data is obtained from the input content and the speed and content of the input. This data is converted into JSON format and sent to the server. The server analyzes the received data and generates prompts appropriate for the generative model. The generative model uses natural language processing technology to generate a list of necessary preparations and advice based on the emotion.

[1688] The hardware and software used are as follows:

[1689] Hardware: Smartphones, tablets, computers

[1690] Software: Python, TextBlob library, JSON library

[1691] Specific examples

[1692] For example, a user accesses the system to change their name and enters the following information: "Name: Yamada Taro," "Age: 30," and "Type of change: Name change." If the emotion engine detects "stress" at this time, the input details and emotional data are collected. Based on the collected information, the server then generates "Documents required for name change: Driver's license, resident registration, and seal certificate" and "Suggested relaxation methods to reduce stress," which are displayed on the user's information terminal.

[1693] Here is an example of a prompt to input to the generative model:

[1694] What documents do users need to complete the name change and what would you suggest to help them relax if they are feeling stressed from the input?

[1695] Example input:

[1696] Name: Yamada Hanako

[1697] Age: 28

[1698] Type of change: Name change

[1699] Emotion: Stress

[1700] Example answer:

[1701] Required documents: Driver's license, resident card, seal certificate

[1702] Emotional advice: Take deep breaths, listen to relaxing music

[1703] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1704] Step 1:

[1705] The user enters information into the form

[1706] A user uses an information device (smartphone, tablet, PC) to enter information such as name, age, type of procedure, etc. into an input form. This form contains multiple fields for the user to fill out.

[1707] (Input) Information such as name, age, type of procedure, etc.

[1708] (Output) A set of input information

[1709] Step 2:

[1710] Acquiring emotion data

[1711] The information terminal analyzes the user's input content and input speed and uses an emotion engine to determine the user's emotional state, extracting emotions such as stress and anxiety from the input content and speed.

[1712] (Input) Patterns of information entered by the user, such as input speed

[1713] (Output) Emotion data (e.g., "stress," "anxiety")

[1714] Step 3:

[1715] Sending input data and emotion data

[1716] The information terminal converts the collected information and emotion data into JSON format and sends it to the server as a POST request.

[1717] (Input) Information entered by the user, emotional data

[1718] (Output) JSON format data

[1719] Step 4:

[1720] Data reception and analysis by the server

[1721] The server parses the POST request received and extracts the JSON data, from which the name, age, procedure type, and emotion data are obtained.

[1722] (Input) JSON format data

[1723] (Output) Analyzed user information and emotion data

[1724] Step 5:

[1725] Running the generative model

[1726] Based on the acquired user information and emotion data, the server passes appropriate prompts to the generative model, which uses natural language processing technology to generate a list of necessary preparations and emotion-based advice.

[1727] (Input) User information and emotion data

[1728] (Output) Preparation list and emotional advice

[1729] Step 6:

[1730] Return and display of preparation list and advice

[1731] The server returns the prepared list and advice according to the user's emotion to the user's information terminal. The information terminal displays the returned list and advice on the screen, making it easier for the user to prepare in advance. The server also provides advice according to the user's emotion.

[1732] (Input) Generated preparation list and advice based on emotions

[1733] (Output) A list of preparations and advice based on emotions displayed on the device

[1734] The above are the specific processing steps that explain how the system program works. At each step, the input and output are clearly defined, and data processing and calculations are performed based on them.

[1735] 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.

[1736] 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.

[1737] 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 robot 414.

[1738] 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.

[1739] 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.

[1740] 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.

[1741] 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).

[1742] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1743] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1744] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1745] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1746] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1747] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1748] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1749] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1750] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1751] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1752] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1753] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1754] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1755] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1756] The following is further disclosed regarding the above embodiment.

[1757] (Claim 1)

[1758] A means for a user to enter information into an input form using a smart device;

[1759] means for transmitting the information collected from the input form to a server;

[1760] A means for the server to analyze the collected information and generate a list of necessary preparations using a generative model;

[1761] a means for displaying the generated preparation list on a user's smart device;

[1762] A system including:

[1763] (Claim 2)

[1764] 10. The system of claim 1, wherein the generative model generates the required preparation list using natural language processing techniques.

[1765] (Claim 3)

[1766] 2. The system of claim 1, wherein the input form includes a plurality of input fields such as name, age, type of change, etc., and the system includes a means for a user to input information into these fields.

[1767] "Example 1"

[1768] (Claim 1)

[1769] A means for a user to input information into an input form using a mobile information terminal;

[1770] means for transmitting the information collected from the input form to a processing device;

[1771] A means for the processing device to analyze the collected information and generate a list of necessary preparations using a generative AI model;

[1772] means for displaying the generated preparation list on a user's mobile information terminal;

[1773] A means for the generative AI model to generate a preparation list using a prompt sentence for a server;

[1774] ...

[1775] A system including:

[1776] (Claim 2)

[1777] 2. The system of claim 1, wherein the generative AI model generates the list of required preparations using natural language processing techniques.

[1778] (Claim 3)

[1779] 2. The system of claim 1, wherein the input form includes a plurality of input fields such as name, age, type of change, etc., and the system includes a means for a user to input information into these fields.

[1780] "Application Example 1"

[1781] (Claim 1)

[1782] A means for a user to input information into an input form using an information processing terminal;

[1783] means for transmitting the information collected from the input form to a data analysis device;

[1784] a means for analyzing the collected information by the data analysis device and generating a list of necessary preparations using natural language processing technology;

[1785] a means for displaying the generated preparation list on a user's information processing terminal;

[1786] A means for providing a list of items required for a procedure at a physical store based on the information input by the user;

[1787] A system including:

[1788] (Claim 2)

[1789] The system of claim 1 , wherein the generative model generates the list of necessary preparations using a question-and-answer generation algorithm.

[1790] (Claim 3)

[1791] 2. The system according to claim 1, wherein the input form includes a plurality of input fields such as name, age, type of procedure, etc., and the system is provided with a means for a user to input information into these fields.

[1792] "Example 2: Combining Emotion Engines"

[1793] (Claim 1)

[1794] A means for a user to input information into an input screen using a communication device;

[1795] means for transmitting the information collected from the input screen to a server;

[1796] A means for the server to analyze the collected information and generate a list of necessary preparations using a generative model;

[1797] means for analyzing emotion data extracted from the input information;

[1798] means for displaying, on a user's communication device, a customized advice based on the generated preparation list and emotion data;

[1799] A system including:

[1800] (Claim 2)

[1801] 10. The system of claim 1, wherein the generative model uses natural language processing techniques to generate a list of necessary preparations and customized advice based on sentiment data.

[1802] (Claim 3)

[1803] 2. The system according to claim 1, wherein the input screen includes a plurality of input fields for identification information, age, type of change, etc., and the system is provided with means for a user to input information into these fields.

[1804] "Application example 2 when combining emotion engines"

[1805] (Claim 1)

[1806] A means for a user to input information into an input form using an information terminal;

[1807] means for transmitting the information and emotion data collected from the input form to a server;

[1808] a means for the server to analyze the collected information and emotion data and generate a list of necessary preparations and advice according to the emotion using a generative model;

[1809] a means for displaying the generated preparation list and advice according to the emotion on an information terminal of the user;

[1810] A system including:

[1811] (Claim 2)

[1812] 2. The system of claim 1, wherein the generative model generates a preparation list and sentiment-based advice using natural language processing techniques.

[1813] (Claim 3)

[1814] The system of claim 1, wherein the input form includes multiple input fields such as name, age, and type of procedure, and the system is provided with a means for a user to enter information into these fields and an emotion engine that acquires emotion data from the speed and content of input. [Explanation of symbols]

[1815] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a user to enter information into an input form using a smart device; means for transmitting the information collected from the input form to a server; A means for the server to analyze the collected information and generate a list of necessary preparations using a generative model; a means for displaying the generated preparation list on a user's smart device; A system including:

2. The system of claim 1 , wherein the generative model generates the required preparation list using natural language processing techniques.

3. 2. The system of claim 1, wherein the input form includes a plurality of input fields such as name, age, type of change, etc., and the system includes means for a user to input information into these fields.

Images