System

Abstract

A system is provided.SOLUTION: A system for providing mental health care for disaster-stricken people at the time of occurrence of disasters, comprising: inputting means for a user to input by voice or text; analyzing means for analyzing information received from the inputting means and generating contents of mental care; providing means for providing the contents of mental care generated by the analyzing means to the user; and notifying means for acquiring disaster-stricken information and notifying start of crowdfunding.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] When a disaster occurs, many people in evacuation shelters and other facilities suffer from stress and anxiety, but it is difficult to provide professional mental care immediately. Current mental care systems have difficulty quickly acquiring and analyzing information, and do not properly automate crowdfunding management or donations. This results in insufficient analysis of effective care for disaster victims and the impact on society as a whole. The present invention aims to solve these problems and provide a system for quickly and effectively providing mental care during disasters and in peacetime. [Means for solving the problem]

[0005] The present invention is a mental health care system for use during disasters and in peacetime, comprising an input means for users to input information by voice or text, an analysis means for analyzing the information received from the input means and generating mental health care content, a provision means for providing the mental health care content generated by the analysis means to users, and a notification means for acquiring disaster information and initiating crowdfunding. The system further comprises a means for providing mental health care during peacetime and storing basic user information in a database, and a means for initiating crowdfunding and automatically managing donations in the event of a disaster. This enables prompt and effective mental health care for disaster victims and appropriate management of donations. Furthermore, the system also comprises a means for anonymizing the information stored in the database and analyzing mental health trends by disaster area, enabling the system to quickly identify trends in social issues and consider countermeasures.

[0006] "When a disaster occurs" refers to the situation when a disaster such as an earthquake, typhoon, or flood occurs.

[0007] "Victims" refers to people who have been directly or indirectly affected by a disaster.

[0008] "Mental health care" refers to support activities aimed at reducing stress and anxiety and maintaining and improving mental health.

[0009] A "system" refers to a structure in which multiple elements or components work together to achieve a specific function.

[0010] "User" refers to a person who uses the system.

[0011] "Voice" or "text" refers to the way a user provides input to a system, with voice referring to spoken input and text referring to written input.

[0012] "Input means" refers to a means for receiving voice or text input from a user.

[0013] "Analysis means" refers to a mechanism that processes information received from an input means, understands its meaning, and generates corresponding content.

[0014] "Mental care content" refers to specific advice and guidelines for action provided to improve the user's mental state.

[0015] The "means for providing" refers to a method for presenting the content of mental care generated by the analysis means to the user.

[0016] "Disaster information" refers to information regarding the occurrence, scale, and scope of impact of a disaster.

[0017] "Crowdfunding" refers to the process of raising funds from a large number of people via the Internet for a specific project or activity.

[0018] "Notification means" refers to a mechanism for notifying users of important information or actions.

[0019] "Peacetime" refers to normal conditions when no disasters have occurred.

[0020] "Basic information" refers to personal information such as the user's name, age, industry, and income.

[0021] A "database" refers to a collection of information that stores large amounts of data in an organized manner and allows for efficient management and retrieval.

[0022] "Donation" refers to financial support provided for a specific purpose.

[0023] "Anonymization" refers to the process of modifying data so that it can no longer be used to identify specific individuals.

[0024] "Mental health trends" refer to the general conditions or patterns regarding mental health in a particular population or region. [Brief explanation of the drawings]

[0025] [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

[0026] 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.

[0027] First, the terms used in the following description will be explained.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 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.

[0036] 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).

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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."

[0046] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input information by voice or text, an analysis means for analyzing the information received from the input means and generating mental health care content, a provision means for providing the mental health care content generated by the analysis means to users, and a notification means for acquiring disaster information and starting crowdfunding.

[0047] System configuration

[0048] The system consists of the following major components:

[0049] 1. Input Method

[0050] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[0051] 2. Analysis method

[0052] The system converts voice data sent from the device into text, analyzes the text data, and uses a natural language processing engine to analyze the input content and generate relevant mental care content.

[0053] 3. Means of provision

[0054] The content of mental care generated by the analysis means is sent to the terminal and displayed to the user, who can then receive advice through the application.

[0055] 4. Means of notification

[0056] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[0057] 5. Database

[0058] The system stores basic user information and usage data, and manages data to provide appropriate services both in normal times and in the event of a disaster.

[0059] Program processing

[0060] The program of this system performs the following processes.

[0061] User Registration and Settings

[0062] The user downloads the app and enters basic information such as name, age, industry, and income on the membership registration screen.

[0063] The terminal transmits the input information to the server.

[0064] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[0065] Mental care through voice and chat

[0066] The user inputs the details of the mental care he or she desires through voice or chat.

[0067] The terminal transmits the input data to the server.

[0068] The server analyzes the input using a natural language processing engine, generates appropriate mental care responses, and sends them to the device.

[0069] The terminal displays the response from the server to the user.

[0070] Disaster response

[0071] The server acquires disaster information from an external disaster information service.

[0072] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[0073] Users join the crowdfunding campaign and enter their payment information.

[0074] The terminal transmits the payment information to the server.

[0075] The server manages the donations and donates any surplus funds to relevant organizations.

[0076] Specific examples

[0077] Examples of use in normal times

[0078] 1. User A downloads the app and registers by entering basic information.

[0079] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[0080] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[0081] 4. User A checks the advice he received and puts it into practice.

[0082] Examples of use during disasters

[0083] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0084] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0085] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[0086] 4. Crowdfunding funds will cover operations and provide personalized care.

[0087] This invention makes it possible to provide effective mental health care during disasters as well as during peacetime, and provides a system that can quickly respond to market needs.

[0088] The processing flow will be explained below.

[0089] Program processing steps

[0090] User Registration and Settings

[0091] Step 1:

[0092] User: Downloads the app and installs it on their smartphone or tablet.

[0093] Step 2:

[0094] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[0095] Step 3:

[0096] Terminal: Sends the entered information to the server.

[0097] Step 4:

[0098] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[0099] Mental care through voice and chat

[0100] Step 1:

[0101] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[0102] Step 2:

[0103] Terminal: Sends input voice data and chat text to the server.

[0104] Step 3:

[0105] Server: Converts the received voice data into text and analyzes it together with the chat text using a natural language processing engine.

[0106] Step 4:

[0107] Server: Based on the analysis results, generate appropriate mental care responses and send them to the device.

[0108] Step 5:

[0109] Terminal: Displays the answer received from the server to the user.

[0110] Step 6:

[0111] User: Review the answers received and implement them as needed.

[0112] Disaster response

[0113] Step 1:

[0114] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[0115] Step 2:

[0116] Server: When new disaster information is detected, it starts responding.

[0117] Step 3:

[0118] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[0119] Step 4:

[0120] User: Receives notification and decides whether to participate in crowdfunding.

[0121] Step 5:

[0122] User: When participating in crowdfunding, enter your payment information and make a donation.

[0123] Step 6:

[0124] Terminal: Sends payment information to the server.

[0125] Step 7:

[0126] Server: Processes payment information and manages crowdfunding funds.

[0127] Step 8:

[0128] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[0129] Database construction and understanding of social issues

[0130] Step 1:

[0131] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[0132] Step 2:

[0133] Server: The collected data is anonymized and stored securely in a database.

[0134] Step 3:

[0135] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[0136] Step 4:

[0137] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[0138] Step 5:

[0139] Server: Sends the generated reports to related organizations and facilitates collaboration.

[0140] Example 1

[0141] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0142] Currently, mental health care for disaster victims is inadequate, and there is a lack of support to alleviate the mental burden of disaster victims. Providing continuous mental health care during peacetime is also an issue. Furthermore, the management of crowdfunding platforms to respond quickly and effectively to disasters is inconsistent, which can lead to insufficient support for users.

[0143] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0144] In this invention, the server includes an input means for users to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, a notification means for acquiring disaster information and notifying the user that crowdfunding has begun, a means for storing basic user information in a database, a means for providing mental care to reduce the user's stress and anxiety during peacetime and disasters, a means for analyzing the generated mental care content, a means for displaying advice to the user, and a means for anonymizing the information stored in the database and analyzing regional mental health trends for each disaster. This enables effective and prompt provision of mental health care during disasters and peacetime, and also improves the management of support through crowdfunding.

[0145] "Input means" refers to the function of a device or software that allows a user to input information about mental health care by voice or text.

[0146] The "analysis means" is a processing function for analyzing information received from the input means and generating appropriate mental care content.

[0147] The "provision means" is a system function for providing the content of mental care generated by the analysis means to the user.

[0148] "Notification means" is a system function for obtaining disaster information and sending a notification to users to start crowdfunding.

[0149] "Means for storing data in a database" refers to the function of a data management system for recording and managing basic information about users and information about mental care.

[0150] "Means for providing mental care during peacetime and disasters" is a system function that provides advice and measures to help users reduce stress and anxiety.

[0151] The "means for analyzing the generated mental care content" is a system function that reanalyzes the content of the mental care to be provided in order to make it more effective in accordance with the current state of the user.

[0152] The "means for displaying advice to the user" is a system function that displays advice generated based on the analysis results on the user's device.

[0153] "Anonymization means" refers to a system function that converts user information stored in a database into a form that does not allow individuals to be identified.

[0154] The "means for analyzing regional mental health trends" is a system function that analyzes mental health trends for each designated region and extracts issues and needs specific to that region.

[0155] This invention is a system for providing mental health care during disasters and in peacetime. Specifically, it includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental health care content, a provision means for providing the user with the mental health care content generated by the analysis means, a notification means for acquiring disaster information and starting crowdfunding, and a means for storing basic user information in a database. An embodiment of this system is described below.

[0156] Hardware and software used

[0157] 1. Input Method

[0158] Hardware: Smartphones, tablets

[0159] Software: Voice input applications, text input fields

[0160] 2. Analysis method

[0161] Hardware: Server

[0162] Software: Natural language processing engine (e.g., Google Cloud Natural Language, IBM Watson)

[0163] 3. Means of provision

[0164] Hardware: Smartphones, tablets

[0165] Software: Application interface, display UI components

[0166] 4. Means of notification

[0167] Hardware: Server

[0168] Software: API with disaster information services (e.g., Yahoo! Disaster Prevention Bulletin, J-Alert), push notification services (e.g., Firebase Cloud Messaging)

[0169] 5. How to store data in a database

[0170] Hardware: Server

[0171] Software: Database management system (e.g. MySQL, PostgreSQL)

[0172] System program processing

[0173] User Registration and Settings

[0174] A user downloads the app, launches it, and navigates to the membership registration screen. The user enters basic information such as name, age, industry, and income. The device sends this input data to the server. The server receives this information and stores it in a database. The server then generates recommended settings based on the user's settings and sends them to the device.

[0175] Mental care through voice and chat

[0176] The user inputs the desired mental care information by voice or text. The device sends the input data to the server. The server uses a natural language processing engine to analyze the input and generate an appropriate mental care response. The server then sends the generated mental care response to the device, which then displays the response to the user.

[0177] Disaster response

[0178] The server obtains disaster information from an external disaster information service. When the server detects the disaster information, it sends a notification to the user that crowdfunding has begun. The user participates in crowdfunding and enters payment information. The terminal sends the payment information to the server, which manages the donations and donates any surplus funds to relevant organizations.

[0179] Specific examples

[0180] (Example of normal use)

[0181] 1. User A downloads the app and registers by entering basic information.

[0182] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[0183] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[0184] 4. User A checks the advice he received and puts it into practice.

[0185] (Example of use during a disaster)

[0186] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0187] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0188] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[0189] 4. Crowdfunding funds will cover operations and provide personalized care.

[0190] Prompt Sentence Examples

[0191] An example of a prompt is, "Please give me some advice on how to stay calm and sleep well in a shelter on a very cold day."

[0192] This invention provides specific embodiments for providing effective mental health care during disasters and in peacetime.

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

[0194] Step 1:

[0195] The user downloads the app, launches it, and goes to the membership registration screen.

[0196] Input: User action (downloading and launching the app)

[0197] Output: Display of member registration screen

[0198] Specific operation: The user installs the app from the Google Play Store or Apple App Store, opens the app, and the membership registration screen appears.

[0199] Step 2:

[0200] The user enters basic information such as name, age, industry, and income.

[0201] Input: User's basic information (name, age, industry, income, etc.)

[0202] Output: Send request with basic information entered

[0203] Specific operation: The user enters the requested information into the registration form using the keyboard and presses the submit button to send the data to the server.

[0204] Step 3:

[0205] The terminal transmits these input data to the server.

[0206] Input: User's basic information (name, age, industry, income, etc.)

[0207] Output: Message sent to server

[0208] Specific operation: The app sends the entered data in JSON format to the server, and the server returns a reception completion message.

[0209] Step 4:

[0210] The server receives this information and stores it in a database.

[0211] Input: User's basic information (name, age, industry, income, etc.)

[0212] Output: Information stored in the database

[0213] Specific operation: The server uses a database management system (e.g., MySQL) to insert the received information into the appropriate table and store it.

[0214] Step 5:

[0215] The server generates recommended settings based on the user's settings and sends them to the device.

[0216] Input: User basic information stored in the database

[0217] Output: Message sent with recommended settings

[0218] What it does: The server uses an algorithm to generate recommended settings and returns them to the device in JSON format. The user can then confirm and save the settings.

[0219] Step 6:

[0220] The user inputs the details of the mental care he or she desires by voice or text.

[0221] Input: User's mental health input (voice or text)

[0222] Output: Request to send audio or text data

[0223] What happens: The user touches the microphone icon in the app to begin voice input, or types a message into the text input field.

[0224] Step 7:

[0225] The terminal sends the input data to the server.

[0226] Input: User's mental health input (voice or text)

[0227] Output: Message sent to server

[0228] Specific operation: The app converts the audio data into text data and sends this converted text in JSON format to the server.

[0229] Step 8:

[0230] The server analyzes the input using a natural language processing engine.

[0231] Input: Input data (text) about the user's mental health care

[0232] Output: Mental care answer

[0233] Specific operation: The server calls a natural language processing engine (e.g., Google Cloud Natural Language), performs analysis, and generates appropriate mental health care answers.

[0234] Step 9:

[0235] The server generates mental care answers and sends them to the terminal.

[0236] Input: Generated mental health care answers

[0237] Output: A message to the terminal indicating that transmission is complete

[0238] What it does: The server generates a response and sends it back to the device in JSON format, along with advice and links to resources.

[0239] Step 10:

[0240] The terminal displays the response from the server to the user.

[0241] Input: Generated mental health care answers

[0242] Output: Advice displayed

[0243] Specific operation: The app displays the received answer on the screen, and the user can view it and receive advice.

[0244] Step 11:

[0245] The server acquires disaster information from an external disaster information service.

[0246] Input: Data from external disaster information service

[0247] Output: Disaster information acquisition completion message

[0248] Specific operation: The server periodically makes API calls to obtain disaster information in real time.

[0249] Step 12:

[0250] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[0251] Input: Acquired disaster information

[0252] Output: Crowdfunding start notification message

[0253] Specific operation: The server generates a notification message and sends it to the user using a push notification service (e.g., Firebase Cloud Messaging).

[0254] Step 13:

[0255] A user joins a crowdfunding campaign and enters payment information.

[0256] Input: Payment information (credit card information, etc.)

[0257] Output: Send request

[0258] What happens: The user opens the notification, enters their payment information, and is taken to the crowdfunding page.

[0259] Step 14:

[0260] The terminal sends the payment information to the server.

[0261] Input: User's payment information

[0262] Output: Message sent to server

[0263] What it does: The app sends the entered payment information securely to the server using an SSL / TLS connection.

[0264] Step 15:

[0265] The server manages the donations and donates any surplus funds to relevant organizations.

[0266] Input: Crowdfunding donation data

[0267] Output: Donation management data and remittance information to relevant organizations

[0268] What it does: The server uses a backend system (e.g., PayPal API) to collect and manage donations, and ensures that donations are distributed to the appropriate organizations.

[0269] (Application example 1)

[0270] 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."

[0271] When disasters occur, victims need to be able to effectively reduce the psychological stress and anxiety they experience during evacuation. Furthermore, there is no system in place to provide prompt, appropriate mental health care during evacuation, so this issue needs to be addressed.

[0272] 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.

[0273] In this invention, the server includes an input means for a user to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the user to start crowdfunding, and a means for providing mental health care during evacuation in the event of a disaster by linking the vehicle and smartphone. This makes it possible to provide psychological support to evacuees in real time and reduce anxiety and stress during evacuation.

[0274] - "Input means" refers to an interface that allows a user to input information about mental health into the system by voice or text.

[0275] The "analysis means" is a function for analyzing the voice or text data received from the input means and generating appropriate mental care content.

[0276] The "provision means" is a function that provides the content of mental care generated by the analysis means to the user.

[0277] The "notification means" is a function that acquires disaster information and notifies users to start crowdfunding based on that information.

[0278] "Mental healthcare means during evacuation through collaboration between autonomous vehicles and smartphones" is a function that provides mental healthcare through collaboration between autonomous vehicles and smartphones during evacuation in the event of a disaster.

[0279] A "database" is a system that stores basic information and usage data of users and analyzes and provides them as needed.

[0280] "Crowdfunding" is an online platform that raises funds for specific causes in the event of a disaster.

[0281] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input voice or text, an analysis means, a provision means, and a notification means. It also includes a means for providing mental health care during evacuation in the event of a disaster by linking an autonomous vehicle with a smartphone.

[0282] Users use their smartphones to input their mental health concerns and problems using voice or text. This voice is picked up by the smartphone's microphone, and text is entered using the keyboard. The input data is sent to a server and analyzed using a natural language processing engine. For example, a natural language processing engine such as spaCy is used for this analysis.

[0283] The mental care content generated by the analysis means is sent to the user's smartphone by the provision means. The user receives advice through the application. This advice can be displayed in text or played back as audio.

[0284] The system obtains disaster information from an external disaster information service. Once this information is obtained, the notification means automatically notifies users that crowdfunding has begun. The funds raised through crowdfunding will be used to support the disaster-stricken areas.

[0285] Furthermore, when evacuating in the event of a disaster, autonomous vehicles with autonomous driving capabilities will be linked to smartphones to provide users with mental health care during evacuation. This linkage will provide a function that allows users to receive psychological support with peace of mind even while evacuating.

[0286] Furthermore, for mental health care in normal times, basic information and usage data of users will be stored in a database. The stored data will be anonymized and used to analyze mental health trends in each disaster-stricken area.

[0287] Specific examples

[0288] Examples of use in normal times

[0289] 1. A user downloads the app and registers by entering basic information.

[0290] 2. When a user feels stressed, they launch the app and type "I can't sleep lately" in chat format.

[0291] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[0292] 4. The user checks and implements the advice received.

[0293] Examples of use during disasters

[0294] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0295] 2. The user launches the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0296] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[0297] 4. Crowdfunding funds will cover operations and provide personalized care.

[0298] Prompt Sentence Examples

[0299] Please enter your user information in the following format:

[0300] Name: Name

[0301] Age: 30

[0302] Occupation: Engineer

[0303] Income: 50,000

[0304] Next, enter your mental health question or concern (e.g., "I'm feeling anxious about my current situation").

[0305] Finally, would you like to receive notifications when the app receives disaster information? (Yes / No)

[0306] This system will enable effective mental health care during disasters and in peacetime, and will enable a rapid response to market needs.

[0307] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0308] Step 1:

[0309] A user downloads the app using a smartphone and enters basic information (such as name, age, occupation, and income). This data is entered through the app's interface and displayed on the smartphone screen.

[0310] Input: Basic information such as name, age, occupation, income, etc.

[0311] Output: Data with basic information entered

[0312] Step 2:

[0313] The device sends the entered basic information to the server, which receives the information, stores it in a database, generates recommended settings for the user, and sends them to the device.

[0314] Input: User basic information

[0315] Data processing: Formatting and saving basic information

[0316] Output: Basic information saved and recommended settings generated

[0317] Step 3:

[0318] Users input their desired mental health care needs through voice or text, and the input data is collected by their smartphone.

[0319] Input: Mental health content in audio or text format

[0320] Output: Audio or text data

[0321] Step 4:

[0322] The device converts the input voice into text using a speech recognition library (e.g., speech_recognition), and the converted text data is sent to the server.

[0323] Input: Audio or text data

[0324] Data processing: speech to text conversion

[0325] Output: Text data

[0326] Step 5:

[0327] The server analyzes the received text data using a natural language processing engine (e.g., spaCy) and generates mental care content.

[0328] Input: Text data

[0329] Data Computing: Analysis with Natural Language Processing

[0330] Output: Generated mental care content

[0331] Step 6:

[0332] The server sends the generated mental care information to the terminal, which then displays it to the user. The display is done in both text and audio format.

[0333] Input: Generated mental care content

[0334] Output: Mental care content displayed to the user

[0335] Step 7:

[0336] The server obtains disaster information from an external disaster information service and notifies the user of the start of crowdfunding based on this information.

[0337] Input: External disaster information

[0338] Output: Crowdfunding notification

[0339] Step 8:

[0340] In the event of a disaster, users' smartphones will be connected to autonomous vehicles to provide mental health care during evacuation. This connection will enable people to receive psychological support in real time.

[0341] Input: Automatic vehicle coordination information, user location information

[0342] Output: Real-time mental health care support

[0343] These steps will ensure effective mental health care during disasters and in peacetime.

[0344] 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.

[0345] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[0346] System configuration

[0347] 1. Input Method

[0348] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[0349] 2. Emotion Engine

[0350] The system analyzes the user's emotions using voice and text data received from the input means, and uses natural language processing and emotion analysis algorithms to assess the user's emotional state in real time.

[0351] 3. Analysis method

[0352] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated.

[0353] 4. Means of provision

[0354] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[0355] 5. Means of notification

[0356] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[0357] 6. Database

[0358] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[0359] Program processing

[0360] The program of this system performs the following processes.

[0361] User Registration and Settings

[0362] A user downloads the app and installs it on their smartphone or tablet.

[0363] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income on the membership registration screen.

[0364] The terminal transmits the input information to the server.

[0365] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[0366] Mental care through voice and chat

[0367] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[0368] The terminal transmits the input voice data and chat text to the server.

[0369] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine.

[0370] The server generates appropriate mental care content based on the emotional data analyzed by the emotion engine and sends it to the terminal.

[0371] The terminal displays the response received from the server to the user.

[0372] The user checks the received answers and implements them as necessary.

[0373] Disaster response

[0374] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[0375] When the server detects new disaster information, it begins responding.

[0376] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[0377] Users will receive a notification and can choose whether or not to participate in crowdfunding.

[0378] When a user participates in crowdfunding, they enter their payment information and make a donation.

[0379] The terminal transmits the payment information to the server.

[0380] The server automatically manages donations and donates any surplus funds to relevant organizations.

[0381] Specific examples

[0382] Examples of use in normal times

[0383] 1. User A downloads the app and registers by entering basic information.

[0384] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[0385] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[0386] 4. The server generates advice on "how to relax" and sends it to the device.

[0387] 5. User A checks the advice he received and puts it into practice.

[0388] Examples of use during disasters

[0389] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0390] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0391] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[0392] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[0393] 5. User B confirms the advice received and reduces the mental load.

[0394] This invention will provide effective mental health care using an emotion engine during disasters and in normal times, enabling appropriate support according to the user's emotional state. Furthermore, by storing emotion data in a database and using it for future improvements, further improvements in the service are expected.

[0395] The processing flow will be explained below.

[0396] Program processing steps

[0397] User Registration and Settings

[0398] Step 1:

[0399] User: Downloads the app and installs it on their smartphone or tablet.

[0400] Step 2:

[0401] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[0402] Step 3:

[0403] Terminal: Sends the entered information to the server.

[0404] Step 4:

[0405] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[0406] Mental care through voice and chat (using emotion engine)

[0407] Step 1:

[0408] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[0409] Step 2:

[0410] Terminal: Sends input voice data and chat text to the server.

[0411] Step 3:

[0412] Server: Converts received voice data into text, using voice recognition technology if necessary.

[0413] Step 4:

[0414] Server: Sends text data to the emotion engine and analyzes the user's emotional state.

[0415] Step 5:

[0416] Server: Based on the analysis results from the emotion engine, the input content and emotional state are comprehensively evaluated, and appropriate mental health care responses are generated.

[0417] Step 6:

[0418] Server: Sends the generated mental care answers to the device.

[0419] Step 7:

[0420] Terminal: Displays the answer received from the server to the user.

[0421] Step 8:

[0422] User: Review the answers received and implement them as needed.

[0423] Disaster response

[0424] Step 1:

[0425] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[0426] Step 2:

[0427] Server: When new disaster information is detected, it starts responding.

[0428] Step 3:

[0429] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[0430] Step 4:

[0431] User: Receives notification and decides whether to participate in crowdfunding.

[0432] Step 5:

[0433] User: When participating in crowdfunding, enter your payment information and make a donation.

[0434] Step 6:

[0435] Terminal: Sends payment information to the server.

[0436] Step 7:

[0437] Server: Processes payment information and manages crowdfunding funds.

[0438] Step 8:

[0439] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[0440] Database construction and understanding of social issues

[0441] Step 1:

[0442] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[0443] Step 2:

[0444] Server: The collected data is anonymized and stored securely in a database.

[0445] Step 3:

[0446] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[0447] Step 4:

[0448] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[0449] Step 5:

[0450] Server: Sends the generated reports to related organizations and facilitates collaboration.

[0451] Example 2

[0452] 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."

[0453] The problem is that users' mental health care is not provided adequately and appropriate support according to their emotional state is lacking, both during disasters and in peacetime.Furthermore, there is no established method for obtaining disaster information in a timely manner and promptly encouraging users to participate in crowdfunding.

[0454] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the start of crowdfunding, and a means for automatically managing donations and distributing them to relevant organizations. This allows users to receive appropriate mental care according to their emotional state and enables them to quickly participate in crowdfunding and contribute to relief efforts in the event of a disaster.

[0455] "Input means" refers to a device or interface that allows a user to input information by voice or text.

[0456] "Analysis means" refers to algorithms or software for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms.

[0457] The "provision means" refers to a device or interface for providing the content of mental care generated by the analysis means to the user.

[0458] "Notification means" refers to the mechanisms and infrastructure for obtaining disaster information and notifying users of the start of crowdfunding.

[0459] "Automated donation management means" refers to a system or algorithm that receives donations from users, manages them appropriately, and distributes them to relevant organizations.

[0460] "Means for generating recommended settings" refers to algorithms or software for generating optimal mental health care settings based on basic user information.

[0461] "Means for entering and saving basic information" refers to an interface or system that allows users to enter basic information such as name, age, occupation, and income and save it in a database.

[0462] "Means for storing emotional data in a database" refers to a mechanism for storing the emotional data obtained by the analysis means in a database and using it to improve mental health care in the future.

[0463] "Anonymization methods" refers to algorithms or technologies used to anonymize information stored in a database so that individuals cannot be identified.

[0464] "Disaster information services" refers to external services and organizations that provide information about disasters.

[0465] "Smart devices" refers to portable electronic devices that can connect to the Internet, such as smartphones and tablets.

[0466] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[0467] 1. Input Method

[0468] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[0469] 2. Emotion Engine

[0470] The system analyzes the user's emotions using voice and text data received from the input means. Specifically, it uses natural language processing and emotion analysis algorithms (e.g., IBM Watson Natural Language Understanding) to evaluate the user's emotional state in real time.

[0471] 3. Analysis method

[0472] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated using natural language processing algorithms (e.g., Google Cloud NLP).

[0473] 4. Means of provision

[0474] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[0475] 5. Means of notification

[0476] Obtain disaster information and notify users of the start of crowdfunding. Disaster information is obtained from an external disaster information service (e.g., Japan Meteorological Agency API).

[0477] 6. Database

[0478] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[0479] Specific examples

[0480] Examples of use in normal times

[0481] 1. User A downloads the app and registers by entering basic information.

[0482] Specific operation: The user inputs "Yamada Taro, 30 years old, engineer, annual income 4 million yen."

[0483] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[0484] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[0485] 4. The server generates advice on "how to relax" and sends it to the device.

[0486] 5. User A checks the advice he received and puts it into practice.

[0487] Examples of use during disasters

[0488] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0489] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0490] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[0491] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[0492] 5. User B confirms the advice received and reduces the mental load.

[0493] Example prompts for generative AI models

[0494] By inputting the following prompt sentences into the generative AI model, specific explanations and suggestions for improvement of the system can be obtained.

[0495] Prompt statement:

[0496] "Please explain the mental health care system I invented. Users download the app, enter their basic information, and then enter their desired mental health care via voice or chat. The server then analyzes the information using an emotion engine and provides appropriate mental health care. In the event of a disaster, the system will notify users of the start of a crowdfunding campaign so that they can make donations. Please suggest any ideas for improving this system."

[0497] This invention allows users to receive effective mental health care using an emotion engine both during disasters and in normal times. It also allows users to participate in community support through crowdfunding, enabling appropriate support tailored to the user's emotional state.

[0498] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0499] Step 1:

[0500] A user downloads and installs the app on their smartphone or tablet.

[0501] Specific behavior: The user searches for "mental healthcare app" in the App Store or Google Play Store and taps the download button to begin installation.

[0502] Step 2:

[0503] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income.

[0504] Specific operation: The user enters "Yamada Taro, 30 years old, engineer, annual income 4 million yen" in the text box and taps the send button.

[0505] Input: Basic information such as name, age, industry, income, etc.

[0506] Output: Basic information data entered

[0507] Step 3:

[0508] The terminal transmits the input information to the server.

[0509] Specific operation: The device encrypts data via the Internet using SSL / TLS and sends it to the server.

[0510] Input: Basic information data when tapping the send button

[0511] Output: Basic information data sent to the server

[0512] Step 4:

[0513] The server stores the received information in a database and generates optimal configuration recommendations for the user.

[0514] How it works: The server stores user information in a MySQL or PostgreSQL database and uses AI algorithms to calculate recommended settings.

[0515] Input: Basic information data

[0516] Output: User information stored in the database, recommended settings data

[0517] Step 5:

[0518] The server generates recommended settings and sends them to the device.

[0519] Specific operation: The server sends the recommended settings to the device in JSON format.

[0520] Input: Recommended setting data

[0521] Output: Recommended configuration data sent to the device

[0522] Step 6:

[0523] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[0524] Specific behavior: The user types "I can't sleep lately" in the chat box and taps the send button, or taps the microphone icon to input voice.

[0525] Input: Text or voice message regarding your request for mental health care

[0526] Output: Sent audio file or text data

[0527] Step 7:

[0528] The terminal sends input voice data and chat text to the server.

[0529] Specific operation: The device saves the voice data as an audio file and sends it to the server along with the text data.

[0530] Input: Audio file or text data

[0531] Output: Audio file or text data sent to the server

[0532] Step 8:

[0533] The server converts the voice data into text and analyzes it using an emotion engine.

[0534] How it works: The server converts the speech to text using the Google Cloud Speech-to-Text API and performs sentiment analysis using IBM Watson Natural Language Understanding.

[0535] Input: Audio file or chat text

[0536] Output: Parsed text data and sentiment data

[0537] Step 9:

[0538] The server generates appropriate mental care content based on emotional data.

[0539] Specific operation: The server generates advice such as "how to relax" based on the analysis results.

[0540] Input: Emotion data

[0541] Output: Mental care advice

[0542] Step 10:

[0543] The mental care content generated by the server is sent to the terminal.

[0544] Specific operation: The server sends mental care advice in JSON format to the terminal.

[0545] Input: Mental care advice

[0546] Output: Mental health advice sent to the device

[0547] Step 11:

[0548] The terminal displays the mental care content received from the server to the user.

[0549] Specific behavior: The device displays advice on the chatbot interface.

[0550] Input: Mental care advice

[0551] Output: Mental health advice displayed to the user

[0552] Step 12:

[0553] The user reviews the advice received and implements it as necessary.

[0554] Specific action: The user reads the displayed advice and performs the action, such as taking a deep breath.

[0555] Input: Mental health advice displayed to the user

[0556] Output: Practical mental health advice

[0557] Step 13:

[0558] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[0559] Specific operation: The server periodically requests the latest disaster information using the Japan Meteorological Agency API.

[0560] Input: APIs that are requested periodically

[0561] Output: Acquired disaster information

[0562] Step 14:

[0563] When the server detects new disaster information, it begins disaster response.

[0564] Specific operation: When the server detects new disaster data, it launches the corresponding module.

[0565] Input: Acquired disaster information

[0566] Output: Corresponding modules launched

[0567] Step 15:

[0568] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[0569] Specific operation: The server generates push notifications and sends them to users in the disaster area.

[0570] Input: Disaster information, user information

[0571] Output: Push notification sent

[0572] Step 16:

[0573] The user receives a notification and can choose whether to participate in the crowdfunding campaign.

[0574] Specific operation: The user taps the notification on the device and moves to the crowdfunding participation screen.

[0575] Input: Push notification

[0576] Output: Crowdfunding participation selection

[0577] Step 17:

[0578] When a user participates in crowdfunding, they enter their payment information and make a donation.

[0579] Specific behavior: The user enters their credit card information and confirms the donation amount.

[0580] Input: Payment information, donation amount

[0581] Output: Donation process completed

[0582] Step 18:

[0583] The terminal sends the payment information to the server.

[0584] What happens: The terminal encrypts the payment information and sends it to the server.

[0585] Input: Payment information

[0586] Output: Payment information sent to the server

[0587] Step 19:

[0588] The server manages the donations and distributes them to the relevant organizations.

[0589] Specific operation: The server manages donations in a dedicated account and periodically transfers any surplus funds to relevant organizations.

[0590] Input: Donation information

[0591] Output: Donations managed, funds sent

[0592] The above are the specific processing steps of this system. This system enables users to receive appropriate mental care during both normal times and disasters.

[0593] (Application example 2)

[0594] 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."

[0595] In the past, mental health care during disasters and in peacetime was often provided with limited resources, making it difficult to effectively support the mental health of disaster victims and general users. Psychological support is particularly urgent during disasters, but the lack of a system to respond to this has been an issue. Furthermore, providing real-time mental health care using emotion analysis technology has not been realized.

[0596] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0597] In this invention, the server includes an input means for a user to input by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, an emotion engine means for analyzing the user's emotional state using an emotion analysis algorithm, and a generation AI model means for generating appropriate mental care advice in real time to provide mental care during peacetime. This makes it possible to provide effective mental health care using emotion analysis both during disasters and peacetime.

[0598] "Input means" refers to the means by which users input information about mental health care by voice or text, and refers to the microphone or keyboard of a device such as a smartphone or tablet.

[0599] The "analysis means" is a means for analyzing information received from the input means and generating mental care content, and uses natural language processing and emotion analysis algorithms.

[0600] The "provision means" is a means for providing the content of mental care generated by the analysis means to the user, and displays advice and care content through an application.

[0601] The "notification means" is a means for obtaining disaster information and notifying users of the start of crowdfunding, and the notification is made based on data from the disaster information provision service.

[0602] The "emotion engine means" is a means for analyzing the user's emotional state using an emotion analysis algorithm, and evaluates emotions based on input voice and text data.

[0603] The "generative AI model means" is a means for generating appropriate mental care advice in real time to provide mental care in peacetime, and uses a generative AI model.

[0604] The present invention is a system for providing mental health care to a user during disasters and in normal times, and provides appropriate mental care according to the emotional state of the user. A specific embodiment of this system will be described.

[0605] System configuration

[0606] The system consists of the following major components:

[0607] 1. Input Method

[0608] Users input their worries and problems about mental health care by voice or text using the microphone and keyboard of their smartphone or tablet.

[0609] 2. Emotional Engine Means

[0610] The system uses emotion analysis algorithms to analyze the user's emotional state based on the voice and text data received from the input means. Specifically, it uses natural language processing libraries such as SpaCy and the Hugging Face emotion analysis model.

[0611] 3. Analysis method

[0612] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated. This analysis uses a generative AI model (e.g., OpenAI's GPT-3).

[0613] 4. Means of provision

[0614] The mental care content generated by the analysis means is sent to the device and provided to the user via an application on a smartphone or tablet.

[0615] 5. Means of notification

[0616] It obtains disaster information from external disaster information services and sends emergency notifications to users in disaster-affected areas, as well as notifying them of the start of crowdfunding.

[0617] 6. Database Means

[0618] The system stores basic information and usage data of users, including emotion data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[0619] Program processing explanation

[0620] The server receives information input by the user via voice or text and analyzes their emotional state using an emotion analysis algorithm. The input voice data and chat text are then processed using a natural language processing module (SpaCy) and an emotion analysis model (Hugging Face). Based on the resulting emotional data, a generative AI model (OpenAI's GPT-3) is used to generate appropriate mental health advice and provide it to the user. Furthermore, based on disaster information from the disaster information provision service, emergency notifications are sent to users in relevant areas. This enables effective mental health care during disasters and in peacetime.

[0621] Examples and prompts

[0622] Examples:

[0623] 1. Examples of use in normal times:

[0624] 1. The user types, "I've been feeling a lot of stress at work lately."

[0625] 2. The server analyzes the input and identifies the emotion "stress" using an emotion engine means.

[0626] 3. Use the generative AI model to generate "stress reduction advice" and provide it to the user.

[0627] 2. Examples of use in times of disaster:

[0628] 1. When a disaster occurs, the server obtains information from the disaster information service and sends notifications to users in the relevant areas.

[0629] 2. The user speaks, "I'm worried about the disaster and can't sleep."

[0630] 3. The server analyzes the voice data and identifies the emotion of "anxiety" using an emotion engine means.

[0631] 4. Use the generative AI model to generate and provide "advice to alleviate anxiety" to the user.

[0632] Example prompt:

[0633] "The user's emotional state is 'Stressed'. Please provide mental health advice for 'Stressed'."

[0634] "The user's emotional state is 'anxious'. Please provide mental health advice for 'anxiety'."

[0635] This system makes it possible to provide appropriate mental care in real time according to the user's emotional state.

[0636] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0637] Step 1:

[0638] The user downloads the app and installs it on their smartphone or tablet. When they launch it for the first time, they enter basic information such as their name, age, occupation, and income on the membership registration screen. The device sends the entered information to the server, which then stores the received information in a database. This registers the user's basic information in the system.

[0639] Input: User's basic information (name, age, occupation, income, etc.)

[0640] Output: User information that will be sent to the server and stored in the database

[0641] Step 2:

[0642] The user launches the app and inputs the details of their desired mental health care needs in voice or text format. The device then sends the input voice data or chat text to the server.

[0643] Input: User's mental health care needs (voice data or text data)

[0644] Output: Audio and text data sent to the server

[0645] Step 3:

[0646] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine. Specifically, it evaluates the emotional state using a natural language processing library (SpaCy) and an emotion analysis model (Hugging Face).

[0647] Input: Audio data and text data

[0648] Output: Emotion data (e.g., "stress," "anxiety," etc.)

[0649] Step 4:

[0650] The server generates appropriate mental health advice using a generative AI model (OpenAI's GPT-3) based on the emotional data analyzed by the emotion engine. The generative AI model generates advice based on the input emotional data and prompt sentence.

[0651] Input: "Emotion data" and "Prompt sentence"

[0652] Output: Generated mental health advice

[0653] Step 5:

[0654] The server sends the generated mental care advice to the device, which then displays it to the user. The user can then confirm and put the advice into practice.

[0655] Input: Generated mental health advice

[0656] Output: Mental health advice displayed on the user's device

[0657] Step 6:

[0658] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service. When new disaster information is obtained, the server sends an emergency notification to users in the disaster-affected area.

[0659] Input: Disaster information from external disaster information services

[0660] Output: Urgent notification sent to the user's device

[0661] Step 7:

[0662] When a user participates in crowdfunding, they enter their payment information and make a donation. The terminal sends the payment information to the server, which stores it in a database. Donations are automatically managed, and any surplus funds are donated to relevant organizations.

[0663] Input: Intention to participate in crowdfunding and payment information

[0664] Output: Payment data and donation management stored on the server

[0665] This will enable effective mental health care to be provided during disasters and in peacetime.

[0666] 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.

[0667] 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.

[0668] 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.

[0669] [Second embodiment]

[0670] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0671] 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.

[0672] 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).

[0673] 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.

[0674] 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.

[0675] 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).

[0676] 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.

[0677] 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.

[0678] 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.

[0679] 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.

[0680] 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.

[0681] 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."

[0682] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input information by voice or text, an analysis means for analyzing the information received from the input means and generating mental health care content, a provision means for providing the mental health care content generated by the analysis means to users, and a notification means for acquiring disaster information and starting crowdfunding.

[0683] System configuration

[0684] The system consists of the following major components:

[0685] 1. Input Method

[0686] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[0687] 2. Analysis method

[0688] The system converts voice data sent from the device into text, analyzes the text data, and uses a natural language processing engine to analyze the input content and generate relevant mental care content.

[0689] 3. Means of provision

[0690] The content of mental care generated by the analysis means is sent to the terminal and displayed to the user, who can then receive advice through the application.

[0691] 4. Means of notification

[0692] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[0693] 5. Database

[0694] The system stores basic user information and usage data, and manages data to provide appropriate services both in normal times and in the event of a disaster.

[0695] Program processing

[0696] The program of this system performs the following processes.

[0697] User Registration and Settings

[0698] The user downloads the app and enters basic information such as name, age, industry, and income on the membership registration screen.

[0699] The terminal transmits the input information to the server.

[0700] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[0701] Mental care through voice and chat

[0702] The user inputs the details of the mental care he or she desires through voice or chat.

[0703] The terminal transmits the input data to the server.

[0704] The server analyzes the input using a natural language processing engine, generates appropriate mental care responses, and sends them to the device.

[0705] The terminal displays the response from the server to the user.

[0706] Disaster response

[0707] The server acquires disaster information from an external disaster information service.

[0708] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[0709] Users join the crowdfunding campaign and enter their payment information.

[0710] The terminal transmits the payment information to the server.

[0711] The server manages the donations and donates any surplus funds to relevant organizations.

[0712] Specific examples

[0713] Examples of use in normal times

[0714] 1. User A downloads the app and registers by entering basic information.

[0715] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[0716] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[0717] 4. User A checks the advice he received and puts it into practice.

[0718] Examples of use during disasters

[0719] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0720] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0721] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[0722] 4. Crowdfunding funds will cover operations and provide personalized care.

[0723] This invention makes it possible to provide effective mental health care during disasters as well as during peacetime, and provides a system that can quickly respond to market needs.

[0724] The processing flow will be explained below.

[0725] Program processing steps

[0726] User Registration and Settings

[0727] Step 1:

[0728] User: Downloads the app and installs it on their smartphone or tablet.

[0729] Step 2:

[0730] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[0731] Step 3:

[0732] Terminal: Sends the entered information to the server.

[0733] Step 4:

[0734] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[0735] Mental care through voice and chat

[0736] Step 1:

[0737] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[0738] Step 2:

[0739] Terminal: Sends input voice data and chat text to the server.

[0740] Step 3:

[0741] Server: Converts the received voice data into text and analyzes it together with the chat text using a natural language processing engine.

[0742] Step 4:

[0743] Server: Based on the analysis results, generate appropriate mental care responses and send them to the device.

[0744] Step 5:

[0745] Terminal: Displays the answer received from the server to the user.

[0746] Step 6:

[0747] User: Review the answers received and implement them as needed.

[0748] Disaster response

[0749] Step 1:

[0750] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[0751] Step 2:

[0752] Server: When new disaster information is detected, it starts responding.

[0753] Step 3:

[0754] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[0755] Step 4:

[0756] User: Receives notification and decides whether to participate in crowdfunding.

[0757] Step 5:

[0758] User: When participating in crowdfunding, enter your payment information and make a donation.

[0759] Step 6:

[0760] Terminal: Sends payment information to the server.

[0761] Step 7:

[0762] Server: Processes payment information and manages crowdfunding funds.

[0763] Step 8:

[0764] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[0765] Database construction and understanding of social issues

[0766] Step 1:

[0767] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[0768] Step 2:

[0769] Server: The collected data is anonymized and stored securely in a database.

[0770] Step 3:

[0771] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[0772] Step 4:

[0773] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[0774] Step 5:

[0775] Server: Sends the generated reports to related organizations and facilitates collaboration.

[0776] Example 1

[0777] 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."

[0778] Currently, mental health care for disaster victims is inadequate, and there is a lack of support to alleviate the mental burden of disaster victims. Providing continuous mental health care during peacetime is also an issue. Furthermore, the management of crowdfunding platforms to respond quickly and effectively to disasters is inconsistent, which can lead to insufficient support for users.

[0779] 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.

[0780] In this invention, the server includes an input means for users to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, a notification means for acquiring disaster information and notifying the user that crowdfunding has begun, a means for storing basic user information in a database, a means for providing mental care to reduce the user's stress and anxiety during peacetime and disasters, a means for analyzing the generated mental care content, a means for displaying advice to the user, and a means for anonymizing the information stored in the database and analyzing regional mental health trends for each disaster. This enables effective and prompt provision of mental health care during disasters and peacetime, and also improves the management of support through crowdfunding.

[0781] "Input means" refers to the function of a device or software that allows a user to input information about mental health care by voice or text.

[0782] The "analysis means" is a processing function for analyzing information received from the input means and generating appropriate mental care content.

[0783] The "provision means" is a system function for providing the content of mental care generated by the analysis means to the user.

[0784] "Notification means" is a system function for obtaining disaster information and sending a notification to users to start crowdfunding.

[0785] "Means for storing data in a database" refers to the function of a data management system for recording and managing basic information about users and information about mental care.

[0786] "Means for providing mental care during peacetime and disasters" is a system function that provides advice and measures to help users reduce stress and anxiety.

[0787] The "means for analyzing the generated mental care content" is a system function that reanalyzes the content of the mental care to be provided in order to make it more effective in accordance with the current state of the user.

[0788] The "means for displaying advice to the user" is a system function that displays advice generated based on the analysis results on the user's device.

[0789] "Anonymization means" refers to a system function that converts user information stored in a database into a form that does not allow individuals to be identified.

[0790] The "means for analyzing regional mental health trends" is a system function that analyzes mental health trends for each designated region and extracts issues and needs specific to that region.

[0791] This invention is a system for providing mental health care during disasters and in peacetime. Specifically, it includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental health care content, a provision means for providing the user with the mental health care content generated by the analysis means, a notification means for acquiring disaster information and starting crowdfunding, and a means for storing basic user information in a database. An embodiment of this system is described below.

[0792] Hardware and software used

[0793] 1. Input Method

[0794] Hardware: Smartphones, tablets

[0795] Software: Voice input applications, text input fields

[0796] 2. Analysis method

[0797] Hardware: Server

[0798] Software: Natural language processing engine (e.g., Google Cloud Natural Language, IBM Watson)

[0799] 3. Means of provision

[0800] Hardware: Smartphones, tablets

[0801] Software: Application interface, display UI components

[0802] 4. Means of notification

[0803] Hardware: Server

[0804] Software: API with disaster information services (e.g., Yahoo! Disaster Prevention Bulletin, J-Alert), push notification services (e.g., Firebase Cloud Messaging)

[0805] 5. How to store data in a database

[0806] Hardware: Server

[0807] Software: Database management system (e.g. MySQL, PostgreSQL)

[0808] System program processing

[0809] User Registration and Settings

[0810] A user downloads the app, launches it, and navigates to the membership registration screen. The user enters basic information such as name, age, industry, and income. The device sends this input data to the server. The server receives this information and stores it in a database. The server then generates recommended settings based on the user's settings and sends them to the device.

[0811] Mental care through voice and chat

[0812] The user inputs the desired mental care information by voice or text. The device sends the input data to the server. The server uses a natural language processing engine to analyze the input and generate an appropriate mental care response. The server then sends the generated mental care response to the device, which then displays the response to the user.

[0813] Disaster response

[0814] The server obtains disaster information from an external disaster information service. When the server detects the disaster information, it sends a notification to the user that crowdfunding has begun. The user participates in crowdfunding and enters payment information. The terminal sends the payment information to the server, which manages the donations and donates any surplus funds to relevant organizations.

[0815] Specific examples

[0816] (Example of normal use)

[0817] 1. User A downloads the app and registers by entering basic information.

[0818] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[0819] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[0820] 4. User A checks the advice he received and puts it into practice.

[0821] (Example of use during a disaster)

[0822] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0823] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0824] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[0825] 4. Crowdfunding funds will cover operations and provide personalized care.

[0826] Prompt Sentence Examples

[0827] An example of a prompt is, "Please give me some advice on how to stay calm and sleep well in a shelter on a very cold day."

[0828] This invention provides specific embodiments for providing effective mental health care during disasters and in peacetime.

[0829] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0830] Step 1:

[0831] The user downloads the app, launches it, and goes to the membership registration screen.

[0832] Input: User action (downloading and launching the app)

[0833] Output: Display of member registration screen

[0834] Specific operation: The user installs the app from the Google Play Store or Apple App Store, opens the app, and the membership registration screen appears.

[0835] Step 2:

[0836] The user enters basic information such as name, age, industry, and income.

[0837] Input: User's basic information (name, age, industry, income, etc.)

[0838] Output: Send request with basic information entered

[0839] Specific operation: The user enters the requested information into the registration form using the keyboard and presses the submit button to send the data to the server.

[0840] Step 3:

[0841] The terminal transmits these input data to the server.

[0842] Input: User's basic information (name, age, industry, income, etc.)

[0843] Output: Message sent to server

[0844] Specific operation: The app sends the entered data in JSON format to the server, and the server returns a reception completion message.

[0845] Step 4:

[0846] The server receives this information and stores it in a database.

[0847] Input: User's basic information (name, age, industry, income, etc.)

[0848] Output: Information stored in the database

[0849] Specific operation: The server uses a database management system (e.g., MySQL) to insert the received information into the appropriate table and store it.

[0850] Step 5:

[0851] The server generates recommended settings based on the user's settings and sends them to the device.

[0852] Input: User basic information stored in the database

[0853] Output: Message sent with recommended settings

[0854] What it does: The server uses an algorithm to generate recommended settings and returns them to the device in JSON format. The user can then confirm and save the settings.

[0855] Step 6:

[0856] The user inputs the details of the mental care he or she desires by voice or text.

[0857] Input: User's mental health input (voice or text)

[0858] Output: Request to send audio or text data

[0859] What happens: The user touches the microphone icon in the app to begin voice input, or types a message into the text input field.

[0860] Step 7:

[0861] The terminal sends the input data to the server.

[0862] Input: User's mental health input (voice or text)

[0863] Output: Message sent to server

[0864] Specific operation: The app converts the audio data into text data and sends this converted text in JSON format to the server.

[0865] Step 8:

[0866] The server analyzes the input using a natural language processing engine.

[0867] Input: Input data (text) about the user's mental health care

[0868] Output: Mental care answer

[0869] Specific operation: The server calls a natural language processing engine (e.g., Google Cloud Natural Language), performs analysis, and generates appropriate mental health care answers.

[0870] Step 9:

[0871] The server generates mental care answers and sends them to the terminal.

[0872] Input: Generated mental health care answers

[0873] Output: A message to the terminal indicating that transmission is complete

[0874] What it does: The server generates a response and sends it back to the device in JSON format, along with advice and links to resources.

[0875] Step 10:

[0876] The terminal displays the response from the server to the user.

[0877] Input: Generated mental health care answers

[0878] Output: Advice displayed

[0879] Specific operation: The app displays the received answer on the screen, and the user can view it and receive advice.

[0880] Step 11:

[0881] The server acquires disaster information from an external disaster information service.

[0882] Input: Data from external disaster information service

[0883] Output: Disaster information acquisition completion message

[0884] Specific operation: The server periodically makes API calls to obtain disaster information in real time.

[0885] Step 12:

[0886] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[0887] Input: Acquired disaster information

[0888] Output: Crowdfunding start notification message

[0889] Specific operation: The server generates a notification message and sends it to the user using a push notification service (e.g., Firebase Cloud Messaging).

[0890] Step 13:

[0891] A user joins a crowdfunding campaign and enters payment information.

[0892] Input: Payment information (credit card information, etc.)

[0893] Output: Send request

[0894] What happens: The user opens the notification, enters their payment information, and is taken to the crowdfunding page.

[0895] Step 14:

[0896] The terminal sends the payment information to the server.

[0897] Input: User's payment information

[0898] Output: Message sent to server

[0899] What it does: The app sends the entered payment information securely to the server using an SSL / TLS connection.

[0900] Step 15:

[0901] The server manages the donations and donates any surplus funds to relevant organizations.

[0902] Input: Crowdfunding donation data

[0903] Output: Donation management data and remittance information to relevant organizations

[0904] What it does: The server uses a backend system (e.g., PayPal API) to collect and manage donations, and ensures that donations are distributed to the appropriate organizations.

[0905] (Application example 1)

[0906] 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."

[0907] When disasters occur, victims need to be able to effectively reduce the psychological stress and anxiety they experience during evacuation. Furthermore, there is no system in place to provide prompt, appropriate mental health care during evacuation, so this issue needs to be addressed.

[0908] 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.

[0909] In this invention, the server includes an input means for a user to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the user to start crowdfunding, and a means for providing mental health care during evacuation in the event of a disaster by linking the vehicle and smartphone. This makes it possible to provide psychological support to evacuees in real time and reduce anxiety and stress during evacuation.

[0910] - "Input means" refers to an interface that allows a user to input information about mental health into the system by voice or text.

[0911] The "analysis means" is a function for analyzing the voice or text data received from the input means and generating appropriate mental care content.

[0912] The "provision means" is a function that provides the content of mental care generated by the analysis means to the user.

[0913] The "notification means" is a function that acquires disaster information and notifies users to start crowdfunding based on that information.

[0914] "Mental healthcare means during evacuation through collaboration between autonomous vehicles and smartphones" is a function that provides mental healthcare through collaboration between autonomous vehicles and smartphones during evacuation in the event of a disaster.

[0915] A "database" is a system that stores basic information and usage data of users and analyzes and provides them as needed.

[0916] "Crowdfunding" is an online platform that raises funds for specific causes in the event of a disaster.

[0917] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input voice or text, an analysis means, a provision means, and a notification means. It also includes a means for providing mental health care during evacuation in the event of a disaster by linking an autonomous vehicle with a smartphone.

[0918] Users use their smartphones to input their mental health concerns and problems using voice or text. This voice is picked up by the smartphone's microphone, and text is entered using the keyboard. The input data is sent to a server and analyzed using a natural language processing engine. For example, a natural language processing engine such as spaCy is used for this analysis.

[0919] The mental care content generated by the analysis means is sent to the user's smartphone by the provision means. The user receives advice through the application. This advice can be displayed in text or played back as audio.

[0920] The system obtains disaster information from an external disaster information service. Once this information is obtained, the notification means automatically notifies users that crowdfunding has begun. The funds raised through crowdfunding will be used to support the disaster-stricken areas.

[0921] Furthermore, when evacuating in the event of a disaster, autonomous vehicles with autonomous driving capabilities will be linked to smartphones to provide users with mental health care during evacuation. This linkage will provide a function that allows users to receive psychological support with peace of mind even while evacuating.

[0922] Furthermore, for mental health care in normal times, basic information and usage data of users will be stored in a database. The stored data will be anonymized and used to analyze mental health trends in each disaster-stricken area.

[0923] Specific examples

[0924] Examples of use in normal times

[0925] 1. A user downloads the app and registers by entering basic information.

[0926] 2. When a user feels stressed, they launch the app and type "I can't sleep lately" in chat format.

[0927] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[0928] 4. The user checks and implements the advice received.

[0929] Examples of use during disasters

[0930] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[0931] 2. The user launches the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[0932] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[0933] 4. Crowdfunding funds will cover operations and provide personalized care.

[0934] Prompt Sentence Examples

[0935] Please enter your user information in the following format:

[0936] Name: Name

[0937] Age: 30

[0938] Occupation: Engineer

[0939] Income: 50,000

[0940] Next, enter your mental health question or concern (e.g., "I'm feeling anxious about my current situation").

[0941] Finally, would you like to receive notifications when the app receives disaster information? (Yes / No)

[0942] This system will enable effective mental health care during disasters and in peacetime, and will enable a rapid response to market needs.

[0943] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0944] Step 1:

[0945] A user downloads the app using a smartphone and enters basic information (such as name, age, occupation, and income). This data is entered through the app's interface and displayed on the smartphone screen.

[0946] Input: Basic information such as name, age, occupation, income, etc.

[0947] Output: Data with basic information entered

[0948] Step 2:

[0949] The device sends the entered basic information to the server, which receives the information, stores it in a database, generates recommended settings for the user, and sends them to the device.

[0950] Input: User basic information

[0951] Data processing: Formatting and saving basic information

[0952] Output: Basic information saved and recommended settings generated

[0953] Step 3:

[0954] Users input their desired mental health care needs through voice or text, and the input data is collected by their smartphone.

[0955] Input: Mental health content in audio or text format

[0956] Output: Audio or text data

[0957] Step 4:

[0958] The device converts the input voice into text using a speech recognition library (e.g., speech_recognition), and the converted text data is sent to the server.

[0959] Input: Audio or text data

[0960] Data processing: speech to text conversion

[0961] Output: Text data

[0962] Step 5:

[0963] The server analyzes the received text data using a natural language processing engine (e.g., spaCy) and generates mental care content.

[0964] Input: Text data

[0965] Data Computing: Analysis with Natural Language Processing

[0966] Output: Generated mental care content

[0967] Step 6:

[0968] The server sends the generated mental care information to the terminal, which then displays it to the user. The display is done in both text and audio format.

[0969] Input: Generated mental care content

[0970] Output: Mental care content displayed to the user

[0971] Step 7:

[0972] The server obtains disaster information from an external disaster information service and notifies the user of the start of crowdfunding based on this information.

[0973] Input: External disaster information

[0974] Output: Crowdfunding notification

[0975] Step 8:

[0976] In the event of a disaster, users' smartphones will be connected to autonomous vehicles to provide mental health care during evacuation. This connection will enable people to receive psychological support in real time.

[0977] Input: Automatic vehicle coordination information, user location information

[0978] Output: Real-time mental health care support

[0979] These steps will ensure effective mental health care during disasters and in peacetime.

[0980] 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.

[0981] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[0982] System configuration

[0983] 1. Input Method

[0984] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[0985] 2. Emotion Engine

[0986] The system analyzes the user's emotions using voice and text data received from the input means, and uses natural language processing and emotion analysis algorithms to assess the user's emotional state in real time.

[0987] 3. Analysis method

[0988] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated.

[0989] 4. Means of provision

[0990] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[0991] 5. Means of notification

[0992] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[0993] 6. Database

[0994] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[0995] Program processing

[0996] The program of this system performs the following processes.

[0997] User Registration and Settings

[0998] A user downloads the app and installs it on their smartphone or tablet.

[0999] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income on the membership registration screen.

[1000] The terminal transmits the input information to the server.

[1001] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[1002] Mental care through voice and chat

[1003] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[1004] The terminal transmits the input voice data and chat text to the server.

[1005] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine.

[1006] The server generates appropriate mental care content based on the emotional data analyzed by the emotion engine and sends it to the terminal.

[1007] The terminal displays the response received from the server to the user.

[1008] The user checks the received answers and implements them as necessary.

[1009] Disaster response

[1010] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[1011] When the server detects new disaster information, it begins responding.

[1012] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[1013] Users will receive a notification and can choose whether or not to participate in crowdfunding.

[1014] When a user participates in crowdfunding, they enter their payment information and make a donation.

[1015] The terminal transmits the payment information to the server.

[1016] The server automatically manages donations and donates any surplus funds to relevant organizations.

[1017] Specific examples

[1018] Examples of use in normal times

[1019] 1. User A downloads the app and registers by entering basic information.

[1020] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[1021] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[1022] 4. The server generates advice on "how to relax" and sends it to the device.

[1023] 5. User A checks the advice he received and puts it into practice.

[1024] Examples of use during disasters

[1025] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1026] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1027] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[1028] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[1029] 5. User B confirms the advice received and reduces the mental load.

[1030] This invention will provide effective mental health care using an emotion engine during disasters and in normal times, enabling appropriate support according to the user's emotional state. Furthermore, by storing emotion data in a database and using it for future improvements, further improvements in the service are expected.

[1031] The processing flow will be explained below.

[1032] Program processing steps

[1033] User Registration and Settings

[1034] Step 1:

[1035] User: Downloads the app and installs it on their smartphone or tablet.

[1036] Step 2:

[1037] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[1038] Step 3:

[1039] Terminal: Sends the entered information to the server.

[1040] Step 4:

[1041] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[1042] Mental care through voice and chat (using emotion engine)

[1043] Step 1:

[1044] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[1045] Step 2:

[1046] Terminal: Sends input voice data and chat text to the server.

[1047] Step 3:

[1048] Server: Converts received voice data into text, using voice recognition technology if necessary.

[1049] Step 4:

[1050] Server: Sends text data to the emotion engine and analyzes the user's emotional state.

[1051] Step 5:

[1052] Server: Based on the analysis results from the emotion engine, the input content and emotional state are comprehensively evaluated, and appropriate mental health care responses are generated.

[1053] Step 6:

[1054] Server: Sends the generated mental care answers to the device.

[1055] Step 7:

[1056] Terminal: Displays the answer received from the server to the user.

[1057] Step 8:

[1058] User: Review the answers received and implement them as needed.

[1059] Disaster response

[1060] Step 1:

[1061] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[1062] Step 2:

[1063] Server: When new disaster information is detected, it starts responding.

[1064] Step 3:

[1065] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[1066] Step 4:

[1067] User: Receives notification and decides whether to participate in crowdfunding.

[1068] Step 5:

[1069] User: When participating in crowdfunding, enter your payment information and make a donation.

[1070] Step 6:

[1071] Terminal: Sends payment information to the server.

[1072] Step 7:

[1073] Server: Processes payment information and manages crowdfunding funds.

[1074] Step 8:

[1075] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[1076] Database construction and understanding of social issues

[1077] Step 1:

[1078] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[1079] Step 2:

[1080] Server: The collected data is anonymized and stored securely in a database.

[1081] Step 3:

[1082] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[1083] Step 4:

[1084] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[1085] Step 5:

[1086] Server: Sends the generated reports to related organizations and facilitates collaboration.

[1087] Example 2

[1088] 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."

[1089] The problem is that users' mental health care is not provided adequately and appropriate support according to their emotional state is lacking, both during disasters and in peacetime.Furthermore, there is no established method for obtaining disaster information in a timely manner and promptly encouraging users to participate in crowdfunding.

[1090] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the start of crowdfunding, and a means for automatically managing donations and distributing them to relevant organizations. This allows users to receive appropriate mental care according to their emotional state and enables them to quickly participate in crowdfunding and contribute to relief efforts in the event of a disaster.

[1091] "Input means" refers to a device or interface that allows a user to input information by voice or text.

[1092] "Analysis means" refers to algorithms or software for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms.

[1093] The "provision means" refers to a device or interface for providing the content of mental care generated by the analysis means to the user.

[1094] "Notification means" refers to the mechanisms and infrastructure for obtaining disaster information and notifying users of the start of crowdfunding.

[1095] "Automated donation management means" refers to a system or algorithm that receives donations from users, manages them appropriately, and distributes them to relevant organizations.

[1096] "Means for generating recommended settings" refers to algorithms or software for generating optimal mental health care settings based on basic user information.

[1097] "Means for entering and saving basic information" refers to an interface or system that allows users to enter basic information such as name, age, occupation, and income and save it in a database.

[1098] "Means for storing emotional data in a database" refers to a mechanism for storing the emotional data obtained by the analysis means in a database and using it to improve mental health care in the future.

[1099] "Anonymization methods" refers to algorithms or technologies used to anonymize information stored in a database so that individuals cannot be identified.

[1100] "Disaster information services" refers to external services and organizations that provide information about disasters.

[1101] "Smart devices" refers to portable electronic devices that can connect to the Internet, such as smartphones and tablets.

[1102] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[1103] 1. Input Method

[1104] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[1105] 2. Emotion Engine

[1106] The system analyzes the user's emotions using voice and text data received from the input means. Specifically, it uses natural language processing and emotion analysis algorithms (e.g., IBM Watson Natural Language Understanding) to evaluate the user's emotional state in real time.

[1107] 3. Analysis method

[1108] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated using natural language processing algorithms (e.g., Google Cloud NLP).

[1109] 4. Means of provision

[1110] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[1111] 5. Means of notification

[1112] Obtain disaster information and notify users of the start of crowdfunding. Disaster information is obtained from an external disaster information service (e.g., Japan Meteorological Agency API).

[1113] 6. Database

[1114] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[1115] Specific examples

[1116] Examples of use in normal times

[1117] 1. User A downloads the app and registers by entering basic information.

[1118] Specific operation: The user inputs "Yamada Taro, 30 years old, engineer, annual income 4 million yen."

[1119] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[1120] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[1121] 4. The server generates advice on "how to relax" and sends it to the device.

[1122] 5. User A checks the advice he received and puts it into practice.

[1123] Examples of use during disasters

[1124] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1125] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1126] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[1127] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[1128] 5. User B confirms the advice received and reduces the mental load.

[1129] Example prompts for generative AI models

[1130] By inputting the following prompt sentences into the generative AI model, specific explanations and suggestions for improvement of the system can be obtained.

[1131] Prompt statement:

[1132] "Please explain the mental health care system I invented. Users download the app, enter their basic information, and then enter their desired mental health care via voice or chat. The server then analyzes the information using an emotion engine and provides appropriate mental health care. In the event of a disaster, the system will notify users of the start of a crowdfunding campaign so that they can make donations. Please suggest any ideas for improving this system."

[1133] This invention allows users to receive effective mental health care using an emotion engine both during disasters and in normal times. It also allows users to participate in community support through crowdfunding, enabling appropriate support tailored to the user's emotional state.

[1134] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1135] Step 1:

[1136] A user downloads and installs the app on their smartphone or tablet.

[1137] Specific behavior: The user searches for "mental healthcare app" in the App Store or Google Play Store and taps the download button to begin installation.

[1138] Step 2:

[1139] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income.

[1140] Specific operation: The user enters "Yamada Taro, 30 years old, engineer, annual income 4 million yen" in the text box and taps the send button.

[1141] Input: Basic information such as name, age, industry, income, etc.

[1142] Output: Basic information data entered

[1143] Step 3:

[1144] The terminal transmits the input information to the server.

[1145] Specific operation: The device encrypts data via the Internet using SSL / TLS and sends it to the server.

[1146] Input: Basic information data when tapping the send button

[1147] Output: Basic information data sent to the server

[1148] Step 4:

[1149] The server stores the received information in a database and generates optimal configuration recommendations for the user.

[1150] How it works: The server stores user information in a MySQL or PostgreSQL database and uses AI algorithms to calculate recommended settings.

[1151] Input: Basic information data

[1152] Output: User information stored in the database, recommended settings data

[1153] Step 5:

[1154] The server generates recommended settings and sends them to the device.

[1155] Specific operation: The server sends the recommended settings to the device in JSON format.

[1156] Input: Recommended setting data

[1157] Output: Recommended configuration data sent to the device

[1158] Step 6:

[1159] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[1160] Specific behavior: The user types "I can't sleep lately" in the chat box and taps the send button, or taps the microphone icon to input voice.

[1161] Input: Text or voice message regarding your request for mental health care

[1162] Output: Sent audio file or text data

[1163] Step 7:

[1164] The terminal sends input voice data and chat text to the server.

[1165] Specific operation: The device saves the voice data as an audio file and sends it to the server along with the text data.

[1166] Input: Audio file or text data

[1167] Output: Audio file or text data sent to the server

[1168] Step 8:

[1169] The server converts the voice data into text and analyzes it using an emotion engine.

[1170] How it works: The server converts the speech to text using the Google Cloud Speech-to-Text API and performs sentiment analysis using IBM Watson Natural Language Understanding.

[1171] Input: Audio file or chat text

[1172] Output: Parsed text data and sentiment data

[1173] Step 9:

[1174] The server generates appropriate mental care content based on emotional data.

[1175] Specific operation: The server generates advice such as "how to relax" based on the analysis results.

[1176] Input: Emotion data

[1177] Output: Mental care advice

[1178] Step 10:

[1179] The mental care content generated by the server is sent to the terminal.

[1180] Specific operation: The server sends mental care advice in JSON format to the terminal.

[1181] Input: Mental care advice

[1182] Output: Mental health advice sent to the device

[1183] Step 11:

[1184] The terminal displays the mental care content received from the server to the user.

[1185] Specific behavior: The device displays advice on the chatbot interface.

[1186] Input: Mental care advice

[1187] Output: Mental health advice displayed to the user

[1188] Step 12:

[1189] The user reviews the advice received and implements it as necessary.

[1190] Specific action: The user reads the displayed advice and performs the action, such as taking a deep breath.

[1191] Input: Mental health advice displayed to the user

[1192] Output: Practical mental health advice

[1193] Step 13:

[1194] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[1195] Specific operation: The server periodically requests the latest disaster information using the Japan Meteorological Agency API.

[1196] Input: APIs that are requested periodically

[1197] Output: Acquired disaster information

[1198] Step 14:

[1199] When the server detects new disaster information, it begins disaster response.

[1200] Specific operation: When the server detects new disaster data, it launches the corresponding module.

[1201] Input: Acquired disaster information

[1202] Output: Corresponding modules launched

[1203] Step 15:

[1204] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[1205] Specific operation: The server generates push notifications and sends them to users in the disaster area.

[1206] Input: Disaster information, user information

[1207] Output: Push notification sent

[1208] Step 16:

[1209] The user receives a notification and can choose whether to participate in the crowdfunding campaign.

[1210] Specific operation: The user taps the notification on the device and moves to the crowdfunding participation screen.

[1211] Input: Push notification

[1212] Output: Crowdfunding participation selection

[1213] Step 17:

[1214] When a user participates in crowdfunding, they enter their payment information and make a donation.

[1215] Specific behavior: The user enters their credit card information and confirms the donation amount.

[1216] Input: Payment information, donation amount

[1217] Output: Donation process completed

[1218] Step 18:

[1219] The terminal sends the payment information to the server.

[1220] What happens: The terminal encrypts the payment information and sends it to the server.

[1221] Input: Payment information

[1222] Output: Payment information sent to the server

[1223] Step 19:

[1224] The server manages the donations and distributes them to the relevant organizations.

[1225] Specific operation: The server manages donations in a dedicated account and periodically transfers any surplus funds to relevant organizations.

[1226] Input: Donation information

[1227] Output: Donations managed, funds sent

[1228] The above are the specific processing steps of this system. This system enables users to receive appropriate mental care during both normal times and disasters.

[1229] (Application example 2)

[1230] 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."

[1231] In the past, mental health care during disasters and in peacetime was often provided with limited resources, making it difficult to effectively support the mental health of disaster victims and general users. Psychological support is particularly urgent during disasters, but the lack of a system to respond to this has been an issue. Furthermore, providing real-time mental health care using emotion analysis technology has not been realized.

[1232] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1233] In this invention, the server includes an input means for a user to input by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, an emotion engine means for analyzing the user's emotional state using an emotion analysis algorithm, and a generation AI model means for generating appropriate mental care advice in real time to provide mental care during peacetime. This makes it possible to provide effective mental health care using emotion analysis both during disasters and peacetime.

[1234] "Input means" refers to the means by which users input information about mental health care by voice or text, and refers to the microphone or keyboard of a device such as a smartphone or tablet.

[1235] The "analysis means" is a means for analyzing information received from the input means and generating mental care content, and uses natural language processing and emotion analysis algorithms.

[1236] The "provision means" is a means for providing the content of mental care generated by the analysis means to the user, and displays advice and care content through an application.

[1237] The "notification means" is a means for obtaining disaster information and notifying users of the start of crowdfunding, and the notification is made based on data from the disaster information provision service.

[1238] The "emotion engine means" is a means for analyzing the user's emotional state using an emotion analysis algorithm, and evaluates emotions based on input voice and text data.

[1239] The "generative AI model means" is a means for generating appropriate mental care advice in real time to provide mental care in peacetime, and uses a generative AI model.

[1240] The present invention is a system for providing mental health care to a user during disasters and in normal times, and provides appropriate mental care according to the emotional state of the user. A specific embodiment of this system will be described.

[1241] System configuration

[1242] The system consists of the following major components:

[1243] 1. Input Method

[1244] Users input their worries and problems about mental health care by voice or text using the microphone and keyboard of their smartphone or tablet.

[1245] 2. Emotional Engine Means

[1246] The system uses emotion analysis algorithms to analyze the user's emotional state based on the voice and text data received from the input means. Specifically, it uses natural language processing libraries such as SpaCy and the Hugging Face emotion analysis model.

[1247] 3. Analysis method

[1248] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated. This analysis uses a generative AI model (e.g., OpenAI's GPT-3).

[1249] 4. Means of provision

[1250] The mental care content generated by the analysis means is sent to the device and provided to the user via an application on a smartphone or tablet.

[1251] 5. Means of notification

[1252] It obtains disaster information from external disaster information services and sends emergency notifications to users in disaster-affected areas, as well as notifying them of the start of crowdfunding.

[1253] 6. Database Means

[1254] The system stores basic information and usage data of users, including emotion data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[1255] Program processing explanation

[1256] The server receives information input by the user via voice or text and analyzes their emotional state using an emotion analysis algorithm. The input voice data and chat text are then processed using a natural language processing module (SpaCy) and an emotion analysis model (Hugging Face). Based on the resulting emotional data, a generative AI model (OpenAI's GPT-3) is used to generate appropriate mental health advice and provide it to the user. Furthermore, based on disaster information from the disaster information provision service, emergency notifications are sent to users in relevant areas. This enables effective mental health care during disasters and in peacetime.

[1257] Examples and prompts

[1258] Examples:

[1259] 1. Examples of use in normal times:

[1260] 1. The user types, "I've been feeling a lot of stress at work lately."

[1261] 2. The server analyzes the input and identifies the emotion "stress" using an emotion engine means.

[1262] 3. Use the generative AI model to generate "stress reduction advice" and provide it to the user.

[1263] 2. Examples of use in times of disaster:

[1264] 1. When a disaster occurs, the server obtains information from the disaster information service and sends notifications to users in the relevant areas.

[1265] 2. The user speaks, "I'm worried about the disaster and can't sleep."

[1266] 3. The server analyzes the voice data and identifies the emotion of "anxiety" using an emotion engine means.

[1267] 4. Use the generative AI model to generate and provide "advice to alleviate anxiety" to the user.

[1268] Example prompt:

[1269] "The user's emotional state is 'Stressed'. Please provide mental health advice for 'Stressed'."

[1270] "The user's emotional state is 'anxious'. Please provide mental health advice for 'anxiety'."

[1271] This system makes it possible to provide appropriate mental care in real time according to the user's emotional state.

[1272] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1273] Step 1:

[1274] The user downloads the app and installs it on their smartphone or tablet. When they launch it for the first time, they enter basic information such as their name, age, occupation, and income on the membership registration screen. The device sends the entered information to the server, which then stores the received information in a database. This registers the user's basic information in the system.

[1275] Input: User's basic information (name, age, occupation, income, etc.)

[1276] Output: User information that will be sent to the server and stored in the database

[1277] Step 2:

[1278] The user launches the app and inputs the details of their desired mental health care needs in voice or text format. The device then sends the input voice data or chat text to the server.

[1279] Input: User's mental health care needs (voice data or text data)

[1280] Output: Audio and text data sent to the server

[1281] Step 3:

[1282] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine. Specifically, it evaluates the emotional state using a natural language processing library (SpaCy) and an emotion analysis model (Hugging Face).

[1283] Input: Audio data and text data

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

[1285] Step 4:

[1286] The server generates appropriate mental health advice using a generative AI model (OpenAI's GPT-3) based on the emotional data analyzed by the emotion engine. The generative AI model generates advice based on the input emotional data and prompt sentence.

[1287] Input: "Emotion data" and "Prompt sentence"

[1288] Output: Generated mental health advice

[1289] Step 5:

[1290] The server sends the generated mental care advice to the device, which then displays it to the user. The user can then confirm and put the advice into practice.

[1291] Input: Generated mental health advice

[1292] Output: Mental health advice displayed on the user's device

[1293] Step 6:

[1294] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service. When new disaster information is obtained, the server sends an emergency notification to users in the disaster-affected area.

[1295] Input: Disaster information from external disaster information services

[1296] Output: Urgent notification sent to the user's device

[1297] Step 7:

[1298] When a user participates in crowdfunding, they enter their payment information and make a donation. The terminal sends the payment information to the server, which stores it in a database. Donations are automatically managed, and any surplus funds are donated to relevant organizations.

[1299] Input: Intention to participate in crowdfunding and payment information

[1300] Output: Payment data and donation management stored on the server

[1301] This will enable effective mental health care to be provided during disasters and in peacetime.

[1302] 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.

[1303] 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.

[1304] 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.

[1305] [Third embodiment]

[1306] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1307] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1308] 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).

[1309] 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.

[1310] 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.

[1311] 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).

[1312] 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.

[1313] 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.

[1314] 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.

[1315] 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.

[1316] 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.

[1317] 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."

[1318] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input information by voice or text, an analysis means for analyzing the information received from the input means and generating mental health care content, a provision means for providing the mental health care content generated by the analysis means to users, and a notification means for acquiring disaster information and starting crowdfunding.

[1319] System configuration

[1320] The system consists of the following major components:

[1321] 1. Input Method

[1322] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[1323] 2. Analysis method

[1324] The system converts voice data sent from the device into text, analyzes the text data, and uses a natural language processing engine to analyze the input content and generate relevant mental care content.

[1325] 3. Means of provision

[1326] The content of mental care generated by the analysis means is sent to the terminal and displayed to the user, who can then receive advice through the application.

[1327] 4. Means of notification

[1328] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[1329] 5. Database

[1330] The system stores basic user information and usage data, and manages data to provide appropriate services both in normal times and in the event of a disaster.

[1331] Program processing

[1332] The program of this system performs the following processes.

[1333] User Registration and Settings

[1334] The user downloads the app and enters basic information such as name, age, industry, and income on the membership registration screen.

[1335] The terminal transmits the input information to the server.

[1336] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[1337] Mental care through voice and chat

[1338] The user inputs the details of the mental care he or she desires through voice or chat.

[1339] The terminal transmits the input data to the server.

[1340] The server analyzes the input using a natural language processing engine, generates appropriate mental care responses, and sends them to the device.

[1341] The terminal displays the response from the server to the user.

[1342] Disaster response

[1343] The server acquires disaster information from an external disaster information service.

[1344] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[1345] Users join the crowdfunding campaign and enter their payment information.

[1346] The terminal transmits the payment information to the server.

[1347] The server manages the donations and donates any surplus funds to relevant organizations.

[1348] Specific examples

[1349] Examples of use in normal times

[1350] 1. User A downloads the app and registers by entering basic information.

[1351] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[1352] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[1353] 4. User A checks the advice he received and puts it into practice.

[1354] Examples of use during disasters

[1355] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1356] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1357] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[1358] 4. Crowdfunding funds will cover operations and provide personalized care.

[1359] This invention makes it possible to provide effective mental health care during disasters as well as during peacetime, and provides a system that can quickly respond to market needs.

[1360] The processing flow will be explained below.

[1361] Program processing steps

[1362] User Registration and Settings

[1363] Step 1:

[1364] User: Downloads the app and installs it on their smartphone or tablet.

[1365] Step 2:

[1366] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[1367] Step 3:

[1368] Terminal: Sends the entered information to the server.

[1369] Step 4:

[1370] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[1371] Mental care through voice and chat

[1372] Step 1:

[1373] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[1374] Step 2:

[1375] Terminal: Sends input voice data and chat text to the server.

[1376] Step 3:

[1377] Server: Converts the received voice data into text and analyzes it together with the chat text using a natural language processing engine.

[1378] Step 4:

[1379] Server: Based on the analysis results, generate appropriate mental care responses and send them to the device.

[1380] Step 5:

[1381] Terminal: Displays the answer received from the server to the user.

[1382] Step 6:

[1383] User: Review the answers received and implement them as needed.

[1384] Disaster response

[1385] Step 1:

[1386] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[1387] Step 2:

[1388] Server: When new disaster information is detected, it starts responding.

[1389] Step 3:

[1390] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[1391] Step 4:

[1392] User: Receives notification and decides whether to participate in crowdfunding.

[1393] Step 5:

[1394] User: When participating in crowdfunding, enter your payment information and make a donation.

[1395] Step 6:

[1396] Terminal: Sends payment information to the server.

[1397] Step 7:

[1398] Server: Processes payment information and manages crowdfunding funds.

[1399] Step 8:

[1400] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[1401] Database construction and understanding of social issues

[1402] Step 1:

[1403] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[1404] Step 2:

[1405] Server: The collected data is anonymized and stored securely in a database.

[1406] Step 3:

[1407] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[1408] Step 4:

[1409] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[1410] Step 5:

[1411] Server: Sends the generated reports to related organizations and facilitates collaboration.

[1412] Example 1

[1413] 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."

[1414] Currently, mental health care for disaster victims is inadequate, and there is a lack of support to alleviate the mental burden of disaster victims. Providing continuous mental health care during peacetime is also an issue. Furthermore, the management of crowdfunding platforms to respond quickly and effectively to disasters is inconsistent, which can lead to insufficient support for users.

[1415] 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.

[1416] In this invention, the server includes an input means for users to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, a notification means for acquiring disaster information and notifying the user that crowdfunding has begun, a means for storing basic user information in a database, a means for providing mental care to reduce the user's stress and anxiety during peacetime and disasters, a means for analyzing the generated mental care content, a means for displaying advice to the user, and a means for anonymizing the information stored in the database and analyzing regional mental health trends for each disaster. This enables effective and prompt provision of mental health care during disasters and peacetime, and also improves the management of support through crowdfunding.

[1417] "Input means" refers to the function of a device or software that allows a user to input information about mental health care by voice or text.

[1418] The "analysis means" is a processing function for analyzing information received from the input means and generating appropriate mental care content.

[1419] The "provision means" is a system function for providing the content of mental care generated by the analysis means to the user.

[1420] "Notification means" is a system function for obtaining disaster information and sending a notification to users to start crowdfunding.

[1421] "Means for storing data in a database" refers to the function of a data management system for recording and managing basic information about users and information about mental care.

[1422] "Means for providing mental care during peacetime and disasters" is a system function that provides advice and measures to help users reduce stress and anxiety.

[1423] The "means for analyzing the generated mental care content" is a system function that reanalyzes the content of the mental care to be provided in order to make it more effective in accordance with the current state of the user.

[1424] The "means for displaying advice to the user" is a system function that displays advice generated based on the analysis results on the user's device.

[1425] "Anonymization means" refers to a system function that converts user information stored in a database into a form that does not allow individuals to be identified.

[1426] The "means for analyzing regional mental health trends" is a system function that analyzes mental health trends for each designated region and extracts issues and needs specific to that region.

[1427] This invention is a system for providing mental health care during disasters and in peacetime. Specifically, it includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental health care content, a provision means for providing the user with the mental health care content generated by the analysis means, a notification means for acquiring disaster information and starting crowdfunding, and a means for storing basic user information in a database. An embodiment of this system is described below.

[1428] Hardware and software used

[1429] 1. Input Method

[1430] Hardware: Smartphones, tablets

[1431] Software: Voice input applications, text input fields

[1432] 2. Analysis method

[1433] Hardware: Server

[1434] Software: Natural language processing engine (e.g., Google Cloud Natural Language, IBM Watson)

[1435] 3. Means of provision

[1436] Hardware: Smartphones, tablets

[1437] Software: Application interface, display UI components

[1438] 4. Means of notification

[1439] Hardware: Server

[1440] Software: API with disaster information services (e.g., Yahoo! Disaster Prevention Bulletin, J-Alert), push notification services (e.g., Firebase Cloud Messaging)

[1441] 5. How to store data in a database

[1442] Hardware: Server

[1443] Software: Database management system (e.g. MySQL, PostgreSQL)

[1444] System program processing

[1445] User Registration and Settings

[1446] A user downloads the app, launches it, and navigates to the membership registration screen. The user enters basic information such as name, age, industry, and income. The device sends this input data to the server. The server receives this information and stores it in a database. The server then generates recommended settings based on the user's settings and sends them to the device.

[1447] Mental care through voice and chat

[1448] The user inputs the desired mental care information by voice or text. The device sends the input data to the server. The server uses a natural language processing engine to analyze the input and generate an appropriate mental care response. The server then sends the generated mental care response to the device, which then displays the response to the user.

[1449] Disaster response

[1450] The server obtains disaster information from an external disaster information service. When the server detects the disaster information, it sends a notification to the user that crowdfunding has begun. The user participates in crowdfunding and enters payment information. The terminal sends the payment information to the server, which manages the donations and donates any surplus funds to relevant organizations.

[1451] Specific examples

[1452] (Example of normal use)

[1453] 1. User A downloads the app and registers by entering basic information.

[1454] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[1455] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[1456] 4. User A checks the advice he received and puts it into practice.

[1457] (Example of use during a disaster)

[1458] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1459] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1460] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[1461] 4. Crowdfunding funds will cover operations and provide personalized care.

[1462] Prompt Sentence Examples

[1463] An example of a prompt is, "Please give me some advice on how to stay calm and sleep well in a shelter on a very cold day."

[1464] This invention provides specific embodiments for providing effective mental health care during disasters and in peacetime.

[1465] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1466] Step 1:

[1467] The user downloads the app, launches it, and goes to the membership registration screen.

[1468] Input: User action (downloading and launching the app)

[1469] Output: Display of member registration screen

[1470] Specific operation: The user installs the app from the Google Play Store or Apple App Store, opens the app, and the membership registration screen appears.

[1471] Step 2:

[1472] The user enters basic information such as name, age, industry, and income.

[1473] Input: User's basic information (name, age, industry, income, etc.)

[1474] Output: Send request with basic information entered

[1475] Specific operation: The user enters the requested information into the registration form using the keyboard and presses the submit button to send the data to the server.

[1476] Step 3:

[1477] The terminal transmits these input data to the server.

[1478] Input: User's basic information (name, age, industry, income, etc.)

[1479] Output: Message sent to server

[1480] Specific operation: The app sends the entered data in JSON format to the server, and the server returns a reception completion message.

[1481] Step 4:

[1482] The server receives this information and stores it in a database.

[1483] Input: User's basic information (name, age, industry, income, etc.)

[1484] Output: Information stored in the database

[1485] Specific operation: The server uses a database management system (e.g., MySQL) to insert the received information into the appropriate table and store it.

[1486] Step 5:

[1487] The server generates recommended settings based on the user's settings and sends them to the device.

[1488] Input: User basic information stored in the database

[1489] Output: Message sent with recommended settings

[1490] What it does: The server uses an algorithm to generate recommended settings and returns them to the device in JSON format. The user can then confirm and save the settings.

[1491] Step 6:

[1492] The user inputs the details of the mental care he or she desires by voice or text.

[1493] Input: User's mental health input (voice or text)

[1494] Output: Request to send audio or text data

[1495] What happens: The user touches the microphone icon in the app to begin voice input, or types a message into the text input field.

[1496] Step 7:

[1497] The terminal sends the input data to the server.

[1498] Input: User's mental health input (voice or text)

[1499] Output: Message sent to server

[1500] Specific operation: The app converts the audio data into text data and sends this converted text in JSON format to the server.

[1501] Step 8:

[1502] The server analyzes the input using a natural language processing engine.

[1503] Input: Input data (text) about the user's mental health care

[1504] Output: Mental care answer

[1505] Specific operation: The server calls a natural language processing engine (e.g., Google Cloud Natural Language), performs analysis, and generates appropriate mental health care answers.

[1506] Step 9:

[1507] The server generates mental care answers and sends them to the terminal.

[1508] Input: Generated mental health care answers

[1509] Output: A message to the terminal indicating that transmission is complete

[1510] What it does: The server generates a response and sends it back to the device in JSON format, along with advice and links to resources.

[1511] Step 10:

[1512] The terminal displays the response from the server to the user.

[1513] Input: Generated mental health care answers

[1514] Output: Advice displayed

[1515] Specific operation: The app displays the received answer on the screen, and the user can view it and receive advice.

[1516] Step 11:

[1517] The server acquires disaster information from an external disaster information service.

[1518] Input: Data from external disaster information service

[1519] Output: Disaster information acquisition completion message

[1520] Specific operation: The server periodically makes API calls to obtain disaster information in real time.

[1521] Step 12:

[1522] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[1523] Input: Acquired disaster information

[1524] Output: Crowdfunding start notification message

[1525] Specific operation: The server generates a notification message and sends it to the user using a push notification service (e.g., Firebase Cloud Messaging).

[1526] Step 13:

[1527] A user joins a crowdfunding campaign and enters payment information.

[1528] Input: Payment information (credit card information, etc.)

[1529] Output: Send request

[1530] What happens: The user opens the notification, enters their payment information, and is taken to the crowdfunding page.

[1531] Step 14:

[1532] The terminal sends the payment information to the server.

[1533] Input: User's payment information

[1534] Output: Message sent to server

[1535] What it does: The app sends the entered payment information securely to the server using an SSL / TLS connection.

[1536] Step 15:

[1537] The server manages the donations and donates any surplus funds to relevant organizations.

[1538] Input: Crowdfunding donation data

[1539] Output: Donation management data and remittance information to relevant organizations

[1540] What it does: The server uses a backend system (e.g., PayPal API) to collect and manage donations, and ensures that donations are distributed to the appropriate organizations.

[1541] (Application example 1)

[1542] 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."

[1543] When disasters occur, victims need to be able to effectively reduce the psychological stress and anxiety they experience during evacuation. Furthermore, there is no system in place to provide prompt, appropriate mental health care during evacuation, so this issue needs to be addressed.

[1544] 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.

[1545] In this invention, the server includes an input means for a user to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the user to start crowdfunding, and a means for providing mental health care during evacuation in the event of a disaster by linking the vehicle and smartphone. This makes it possible to provide psychological support to evacuees in real time and reduce anxiety and stress during evacuation.

[1546] - "Input means" refers to an interface that allows a user to input information about mental health into the system by voice or text.

[1547] The "analysis means" is a function for analyzing the voice or text data received from the input means and generating appropriate mental care content.

[1548] The "provision means" is a function that provides the content of mental care generated by the analysis means to the user.

[1549] The "notification means" is a function that acquires disaster information and notifies users to start crowdfunding based on that information.

[1550] "Mental healthcare means during evacuation through collaboration between autonomous vehicles and smartphones" is a function that provides mental healthcare through collaboration between autonomous vehicles and smartphones during evacuation in the event of a disaster.

[1551] A "database" is a system that stores basic information and usage data of users and analyzes and provides them as needed.

[1552] "Crowdfunding" is an online platform that raises funds for specific causes in the event of a disaster.

[1553] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input voice or text, an analysis means, a provision means, and a notification means. It also includes a means for providing mental health care during evacuation in the event of a disaster by linking an autonomous vehicle with a smartphone.

[1554] Users use their smartphones to input their mental health concerns and problems using voice or text. This voice is picked up by the smartphone's microphone, and text is entered using the keyboard. The input data is sent to a server and analyzed using a natural language processing engine. For example, a natural language processing engine such as spaCy is used for this analysis.

[1555] The mental care content generated by the analysis means is sent to the user's smartphone by the provision means. The user receives advice through the application. This advice can be displayed in text or played back as audio.

[1556] The system obtains disaster information from an external disaster information service. Once this information is obtained, the notification means automatically notifies users that crowdfunding has begun. The funds raised through crowdfunding will be used to support the disaster-stricken areas.

[1557] Furthermore, when evacuating in the event of a disaster, autonomous vehicles with autonomous driving capabilities will be linked to smartphones to provide users with mental health care during evacuation. This linkage will provide a function that allows users to receive psychological support with peace of mind even while evacuating.

[1558] Furthermore, for mental health care in normal times, basic information and usage data of users will be stored in a database. The stored data will be anonymized and used to analyze mental health trends in each disaster-stricken area.

[1559] Specific examples

[1560] Examples of use in normal times

[1561] 1. A user downloads the app and registers by entering basic information.

[1562] 2. When a user feels stressed, they launch the app and type "I can't sleep lately" in chat format.

[1563] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[1564] 4. The user checks and implements the advice received.

[1565] Examples of use during disasters

[1566] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1567] 2. The user launches the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1568] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[1569] 4. Crowdfunding funds will cover operations and provide personalized care.

[1570] Prompt Sentence Examples

[1571] Please enter your user information in the following format:

[1572] Name: Name

[1573] Age: 30

[1574] Occupation: Engineer

[1575] Income: 50,000

[1576] Next, enter your mental health question or concern (e.g., "I'm feeling anxious about my current situation").

[1577] Finally, would you like to receive notifications when the app receives disaster information? (Yes / No)

[1578] This system will enable effective mental health care during disasters and in peacetime, and will enable a rapid response to market needs.

[1579] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1580] Step 1:

[1581] A user downloads the app using a smartphone and enters basic information (such as name, age, occupation, and income). This data is entered through the app's interface and displayed on the smartphone screen.

[1582] Input: Basic information such as name, age, occupation, income, etc.

[1583] Output: Data with basic information entered

[1584] Step 2:

[1585] The device sends the entered basic information to the server, which receives the information, stores it in a database, generates recommended settings for the user, and sends them to the device.

[1586] Input: User basic information

[1587] Data processing: Formatting and saving basic information

[1588] Output: Basic information saved and recommended settings generated

[1589] Step 3:

[1590] Users input their desired mental health care needs through voice or text, and the input data is collected by their smartphone.

[1591] Input: Mental health content in audio or text format

[1592] Output: Audio or text data

[1593] Step 4:

[1594] The device converts the input voice into text using a speech recognition library (e.g., speech_recognition), and the converted text data is sent to the server.

[1595] Input: Audio or text data

[1596] Data processing: speech to text conversion

[1597] Output: Text data

[1598] Step 5:

[1599] The server analyzes the received text data using a natural language processing engine (e.g., spaCy) and generates mental care content.

[1600] Input: Text data

[1601] Data Computing: Analysis with Natural Language Processing

[1602] Output: Generated mental care content

[1603] Step 6:

[1604] The server sends the generated mental care information to the terminal, which then displays it to the user. The display is done in both text and audio format.

[1605] Input: Generated mental care content

[1606] Output: Mental care content displayed to the user

[1607] Step 7:

[1608] The server obtains disaster information from an external disaster information service and notifies the user of the start of crowdfunding based on this information.

[1609] Input: External disaster information

[1610] Output: Crowdfunding notification

[1611] Step 8:

[1612] In the event of a disaster, users' smartphones will be connected to autonomous vehicles to provide mental health care during evacuation. This connection will enable people to receive psychological support in real time.

[1613] Input: Automatic vehicle coordination information, user location information

[1614] Output: Real-time mental health care support

[1615] These steps will ensure effective mental health care during disasters and in peacetime.

[1616] 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.

[1617] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[1618] System configuration

[1619] 1. Input Method

[1620] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[1621] 2. Emotion Engine

[1622] The system analyzes the user's emotions using voice and text data received from the input means, and uses natural language processing and emotion analysis algorithms to assess the user's emotional state in real time.

[1623] 3. Analysis method

[1624] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated.

[1625] 4. Means of provision

[1626] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[1627] 5. Means of notification

[1628] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[1629] 6. Database

[1630] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[1631] Program processing

[1632] The program of this system performs the following processes.

[1633] User Registration and Settings

[1634] A user downloads the app and installs it on their smartphone or tablet.

[1635] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income on the membership registration screen.

[1636] The terminal transmits the input information to the server.

[1637] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[1638] Mental care through voice and chat

[1639] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[1640] The terminal transmits the input voice data and chat text to the server.

[1641] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine.

[1642] The server generates appropriate mental care content based on the emotional data analyzed by the emotion engine and sends it to the terminal.

[1643] The terminal displays the response received from the server to the user.

[1644] The user checks the received answers and implements them as necessary.

[1645] Disaster response

[1646] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[1647] When the server detects new disaster information, it begins responding.

[1648] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[1649] Users will receive a notification and can choose whether or not to participate in crowdfunding.

[1650] When a user participates in crowdfunding, they enter their payment information and make a donation.

[1651] The terminal transmits the payment information to the server.

[1652] The server automatically manages donations and donates any surplus funds to relevant organizations.

[1653] Specific examples

[1654] Examples of use in normal times

[1655] 1. User A downloads the app and registers by entering basic information.

[1656] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[1657] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[1658] 4. The server generates advice on "how to relax" and sends it to the device.

[1659] 5. User A checks the advice he received and puts it into practice.

[1660] Examples of use during disasters

[1661] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1662] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1663] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[1664] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[1665] 5. User B confirms the advice received and reduces the mental load.

[1666] This invention will provide effective mental health care using an emotion engine during disasters and in normal times, enabling appropriate support according to the user's emotional state. Furthermore, by storing emotion data in a database and using it for future improvements, further improvements in the service are expected.

[1667] The processing flow will be explained below.

[1668] Program processing steps

[1669] User Registration and Settings

[1670] Step 1:

[1671] User: Downloads the app and installs it on their smartphone or tablet.

[1672] Step 2:

[1673] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[1674] Step 3:

[1675] Terminal: Sends the entered information to the server.

[1676] Step 4:

[1677] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[1678] Mental care through voice and chat (using emotion engine)

[1679] Step 1:

[1680] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[1681] Step 2:

[1682] Terminal: Sends input voice data and chat text to the server.

[1683] Step 3:

[1684] Server: Converts received voice data into text, using voice recognition technology if necessary.

[1685] Step 4:

[1686] Server: Sends text data to the emotion engine and analyzes the user's emotional state.

[1687] Step 5:

[1688] Server: Based on the analysis results from the emotion engine, the input content and emotional state are comprehensively evaluated, and appropriate mental health care responses are generated.

[1689] Step 6:

[1690] Server: Sends the generated mental care answers to the device.

[1691] Step 7:

[1692] Terminal: Displays the answer received from the server to the user.

[1693] Step 8:

[1694] User: Review the answers received and implement them as needed.

[1695] Disaster response

[1696] Step 1:

[1697] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[1698] Step 2:

[1699] Server: When new disaster information is detected, it starts responding.

[1700] Step 3:

[1701] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[1702] Step 4:

[1703] User: Receives notification and decides whether to participate in crowdfunding.

[1704] Step 5:

[1705] User: When participating in crowdfunding, enter your payment information and make a donation.

[1706] Step 6:

[1707] Terminal: Sends payment information to the server.

[1708] Step 7:

[1709] Server: Processes payment information and manages crowdfunding funds.

[1710] Step 8:

[1711] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[1712] Database construction and understanding of social issues

[1713] Step 1:

[1714] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[1715] Step 2:

[1716] Server: The collected data is anonymized and stored securely in a database.

[1717] Step 3:

[1718] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[1719] Step 4:

[1720] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[1721] Step 5:

[1722] Server: Sends the generated reports to related organizations and facilitates collaboration.

[1723] Example 2

[1724] 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."

[1725] The problem is that users' mental health care is not provided adequately and appropriate support according to their emotional state is lacking, both during disasters and in peacetime.Furthermore, there is no established method for obtaining disaster information in a timely manner and promptly encouraging users to participate in crowdfunding.

[1726] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the start of crowdfunding, and a means for automatically managing donations and distributing them to relevant organizations. This allows users to receive appropriate mental care according to their emotional state and enables them to quickly participate in crowdfunding and contribute to relief efforts in the event of a disaster.

[1727] "Input means" refers to a device or interface that allows a user to input information by voice or text.

[1728] "Analysis means" refers to algorithms or software for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms.

[1729] The "provision means" refers to a device or interface for providing the content of mental care generated by the analysis means to the user.

[1730] "Notification means" refers to the mechanisms and infrastructure for obtaining disaster information and notifying users of the start of crowdfunding.

[1731] "Automated donation management means" refers to a system or algorithm that receives donations from users, manages them appropriately, and distributes them to relevant organizations.

[1732] "Means for generating recommended settings" refers to algorithms or software for generating optimal mental health care settings based on basic user information.

[1733] "Means for entering and saving basic information" refers to an interface or system that allows users to enter basic information such as name, age, occupation, and income and save it in a database.

[1734] "Means for storing emotional data in a database" refers to a mechanism for storing the emotional data obtained by the analysis means in a database and using it to improve mental health care in the future.

[1735] "Anonymization methods" refers to algorithms or technologies used to anonymize information stored in a database so that individuals cannot be identified.

[1736] "Disaster information services" refers to external services and organizations that provide information about disasters.

[1737] "Smart devices" refers to portable electronic devices that can connect to the Internet, such as smartphones and tablets.

[1738] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[1739] 1. Input Method

[1740] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[1741] 2. Emotion Engine

[1742] The system analyzes the user's emotions using voice and text data received from the input means. Specifically, it uses natural language processing and emotion analysis algorithms (e.g., IBM Watson Natural Language Understanding) to evaluate the user's emotional state in real time.

[1743] 3. Analysis method

[1744] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated using natural language processing algorithms (e.g., Google Cloud NLP).

[1745] 4. Means of provision

[1746] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[1747] 5. Means of notification

[1748] Obtain disaster information and notify users of the start of crowdfunding. Disaster information is obtained from an external disaster information service (e.g., Japan Meteorological Agency API).

[1749] 6. Database

[1750] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[1751] Specific examples

[1752] Examples of use in normal times

[1753] 1. User A downloads the app and registers by entering basic information.

[1754] Specific operation: The user inputs "Yamada Taro, 30 years old, engineer, annual income 4 million yen."

[1755] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[1756] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[1757] 4. The server generates advice on "how to relax" and sends it to the device.

[1758] 5. User A checks the advice he received and puts it into practice.

[1759] Examples of use during disasters

[1760] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1761] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1762] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[1763] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[1764] 5. User B confirms the advice received and reduces the mental load.

[1765] Example prompts for generative AI models

[1766] By inputting the following prompt sentences into the generative AI model, specific explanations and suggestions for improvement of the system can be obtained.

[1767] Prompt statement:

[1768] "Please explain the mental health care system I invented. Users download the app, enter their basic information, and then enter their desired mental health care via voice or chat. The server then analyzes the information using an emotion engine and provides appropriate mental health care. In the event of a disaster, the system will notify users of the start of a crowdfunding campaign so that they can make donations. Please suggest any ideas for improving this system."

[1769] This invention allows users to receive effective mental health care using an emotion engine both during disasters and in normal times. It also allows users to participate in community support through crowdfunding, enabling appropriate support tailored to the user's emotional state.

[1770] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1771] Step 1:

[1772] A user downloads and installs the app on their smartphone or tablet.

[1773] Specific behavior: The user searches for "mental healthcare app" in the App Store or Google Play Store and taps the download button to begin installation.

[1774] Step 2:

[1775] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income.

[1776] Specific operation: The user enters "Yamada Taro, 30 years old, engineer, annual income 4 million yen" in the text box and taps the send button.

[1777] Input: Basic information such as name, age, industry, income, etc.

[1778] Output: Basic information data entered

[1779] Step 3:

[1780] The terminal transmits the input information to the server.

[1781] Specific operation: The device encrypts data via the Internet using SSL / TLS and sends it to the server.

[1782] Input: Basic information data when tapping the send button

[1783] Output: Basic information data sent to the server

[1784] Step 4:

[1785] The server stores the received information in a database and generates optimal configuration recommendations for the user.

[1786] How it works: The server stores user information in a MySQL or PostgreSQL database and uses AI algorithms to calculate recommended settings.

[1787] Input: Basic information data

[1788] Output: User information stored in the database, recommended settings data

[1789] Step 5:

[1790] The server generates recommended settings and sends them to the device.

[1791] Specific operation: The server sends the recommended settings to the device in JSON format.

[1792] Input: Recommended setting data

[1793] Output: Recommended configuration data sent to the device

[1794] Step 6:

[1795] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[1796] Specific behavior: The user types "I can't sleep lately" in the chat box and taps the send button, or taps the microphone icon to input voice.

[1797] Input: Text or voice message regarding your request for mental health care

[1798] Output: Sent audio file or text data

[1799] Step 7:

[1800] The terminal sends input voice data and chat text to the server.

[1801] Specific operation: The device saves the voice data as an audio file and sends it to the server along with the text data.

[1802] Input: Audio file or text data

[1803] Output: Audio file or text data sent to the server

[1804] Step 8:

[1805] The server converts the voice data into text and analyzes it using an emotion engine.

[1806] How it works: The server converts the speech to text using the Google Cloud Speech-to-Text API and performs sentiment analysis using IBM Watson Natural Language Understanding.

[1807] Input: Audio file or chat text

[1808] Output: Parsed text data and sentiment data

[1809] Step 9:

[1810] The server generates appropriate mental care content based on emotional data.

[1811] Specific operation: The server generates advice such as "how to relax" based on the analysis results.

[1812] Input: Emotion data

[1813] Output: Mental care advice

[1814] Step 10:

[1815] The mental care content generated by the server is sent to the terminal.

[1816] Specific operation: The server sends mental care advice in JSON format to the terminal.

[1817] Input: Mental care advice

[1818] Output: Mental health advice sent to the device

[1819] Step 11:

[1820] The terminal displays the mental care content received from the server to the user.

[1821] Specific behavior: The device displays advice on the chatbot interface.

[1822] Input: Mental care advice

[1823] Output: Mental health advice displayed to the user

[1824] Step 12:

[1825] The user reviews the advice received and implements it as necessary.

[1826] Specific action: The user reads the displayed advice and performs the action, such as taking a deep breath.

[1827] Input: Mental health advice displayed to the user

[1828] Output: Practical mental health advice

[1829] Step 13:

[1830] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[1831] Specific operation: The server periodically requests the latest disaster information using the Japan Meteorological Agency API.

[1832] Input: APIs that are requested periodically

[1833] Output: Acquired disaster information

[1834] Step 14:

[1835] When the server detects new disaster information, it begins disaster response.

[1836] Specific operation: When the server detects new disaster data, it launches the corresponding module.

[1837] Input: Acquired disaster information

[1838] Output: Corresponding modules launched

[1839] Step 15:

[1840] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[1841] Specific operation: The server generates push notifications and sends them to users in the disaster area.

[1842] Input: Disaster information, user information

[1843] Output: Push notification sent

[1844] Step 16:

[1845] The user receives a notification and can choose whether to participate in the crowdfunding campaign.

[1846] Specific operation: The user taps the notification on the device and moves to the crowdfunding participation screen.

[1847] Input: Push notification

[1848] Output: Crowdfunding participation selection

[1849] Step 17:

[1850] When a user participates in crowdfunding, they enter their payment information and make a donation.

[1851] Specific behavior: The user enters their credit card information and confirms the donation amount.

[1852] Input: Payment information, donation amount

[1853] Output: Donation process completed

[1854] Step 18:

[1855] The terminal sends the payment information to the server.

[1856] What happens: The terminal encrypts the payment information and sends it to the server.

[1857] Input: Payment information

[1858] Output: Payment information sent to the server

[1859] Step 19:

[1860] The server manages the donations and distributes them to the relevant organizations.

[1861] Specific operation: The server manages donations in a dedicated account and periodically transfers any surplus funds to relevant organizations.

[1862] Input: Donation information

[1863] Output: Donations managed, funds sent

[1864] The above are the specific processing steps of this system. This system enables users to receive appropriate mental care during both normal times and disasters.

[1865] (Application example 2)

[1866] 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."

[1867] In the past, mental health care during disasters and in peacetime was often provided with limited resources, making it difficult to effectively support the mental health of disaster victims and general users. Psychological support is particularly urgent during disasters, but the lack of a system to respond to this has been an issue. Furthermore, providing real-time mental health care using emotion analysis technology has not been realized.

[1868] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1869] In this invention, the server includes an input means for a user to input by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, an emotion engine means for analyzing the user's emotional state using an emotion analysis algorithm, and a generation AI model means for generating appropriate mental care advice in real time to provide mental care during peacetime. This makes it possible to provide effective mental health care using emotion analysis both during disasters and peacetime.

[1870] "Input means" refers to the means by which users input information about mental health care by voice or text, and refers to the microphone or keyboard of a device such as a smartphone or tablet.

[1871] The "analysis means" is a means for analyzing information received from the input means and generating mental care content, and uses natural language processing and emotion analysis algorithms.

[1872] The "provision means" is a means for providing the content of mental care generated by the analysis means to the user, and displays advice and care content through an application.

[1873] The "notification means" is a means for obtaining disaster information and notifying users of the start of crowdfunding, and the notification is made based on data from the disaster information provision service.

[1874] The "emotion engine means" is a means for analyzing the user's emotional state using an emotion analysis algorithm, and evaluates emotions based on input voice and text data.

[1875] The "generative AI model means" is a means for generating appropriate mental care advice in real time to provide mental care in peacetime, and uses a generative AI model.

[1876] The present invention is a system for providing mental health care to a user during disasters and in normal times, and provides appropriate mental care according to the emotional state of the user. A specific embodiment of this system will be described.

[1877] System configuration

[1878] The system consists of the following major components:

[1879] 1. Input Method

[1880] Users input their worries and problems about mental health care by voice or text using the microphone and keyboard of their smartphone or tablet.

[1881] 2. Emotional Engine Means

[1882] The system uses emotion analysis algorithms to analyze the user's emotional state based on the voice and text data received from the input means. Specifically, it uses natural language processing libraries such as SpaCy and the Hugging Face emotion analysis model.

[1883] 3. Analysis method

[1884] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated. This analysis uses a generative AI model (e.g., OpenAI's GPT-3).

[1885] 4. Means of provision

[1886] The mental care content generated by the analysis means is sent to the device and provided to the user via an application on a smartphone or tablet.

[1887] 5. Means of notification

[1888] It obtains disaster information from external disaster information services and sends emergency notifications to users in disaster-affected areas, as well as notifying them of the start of crowdfunding.

[1889] 6. Database Means

[1890] The system stores basic information and usage data of users, including emotion data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[1891] Program processing explanation

[1892] The server receives information input by the user via voice or text and analyzes their emotional state using an emotion analysis algorithm. The input voice data and chat text are then processed using a natural language processing module (SpaCy) and an emotion analysis model (Hugging Face). Based on the resulting emotional data, a generative AI model (OpenAI's GPT-3) is used to generate appropriate mental health advice and provide it to the user. Furthermore, based on disaster information from the disaster information provision service, emergency notifications are sent to users in relevant areas. This enables effective mental health care during disasters and in peacetime.

[1893] Examples and prompts

[1894] Examples:

[1895] 1. Examples of use in normal times:

[1896] 1. The user types, "I've been feeling a lot of stress at work lately."

[1897] 2. The server analyzes the input and identifies the emotion "stress" using an emotion engine means.

[1898] 3. Use the generative AI model to generate "stress reduction advice" and provide it to the user.

[1899] 2. Examples of use in times of disaster:

[1900] 1. When a disaster occurs, the server obtains information from the disaster information service and sends notifications to users in the relevant areas.

[1901] 2. The user speaks, "I'm worried about the disaster and can't sleep."

[1902] 3. The server analyzes the voice data and identifies the emotion of "anxiety" using an emotion engine means.

[1903] 4. Use the generative AI model to generate and provide "advice to alleviate anxiety" to the user.

[1904] Example prompt:

[1905] "The user's emotional state is 'Stressed'. Please provide mental health advice for 'Stressed'."

[1906] "The user's emotional state is 'anxious'. Please provide mental health advice for 'anxiety'."

[1907] This system makes it possible to provide appropriate mental care in real time according to the user's emotional state.

[1908] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1909] Step 1:

[1910] The user downloads the app and installs it on their smartphone or tablet. When they launch it for the first time, they enter basic information such as their name, age, occupation, and income on the membership registration screen. The device sends the entered information to the server, which then stores the received information in a database. This registers the user's basic information in the system.

[1911] Input: User's basic information (name, age, occupation, income, etc.)

[1912] Output: User information that will be sent to the server and stored in the database

[1913] Step 2:

[1914] The user launches the app and inputs the details of their desired mental health care needs in voice or text format. The device then sends the input voice data or chat text to the server.

[1915] Input: User's mental health care needs (voice data or text data)

[1916] Output: Audio and text data sent to the server

[1917] Step 3:

[1918] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine. Specifically, it evaluates the emotional state using a natural language processing library (SpaCy) and an emotion analysis model (Hugging Face).

[1919] Input: Audio data and text data

[1920] Output: Emotion data (e.g., "stress," "anxiety," etc.)

[1921] Step 4:

[1922] The server generates appropriate mental health advice using a generative AI model (OpenAI's GPT-3) based on the emotional data analyzed by the emotion engine. The generative AI model generates advice based on the input emotional data and prompt sentence.

[1923] Input: "Emotion data" and "Prompt sentence"

[1924] Output: Generated mental health advice

[1925] Step 5:

[1926] The server sends the generated mental care advice to the device, which then displays it to the user. The user can then confirm and put the advice into practice.

[1927] Input: Generated mental health advice

[1928] Output: Mental health advice displayed on the user's device

[1929] Step 6:

[1930] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service. When new disaster information is obtained, the server sends an emergency notification to users in the disaster-affected area.

[1931] Input: Disaster information from external disaster information services

[1932] Output: Urgent notification sent to the user's device

[1933] Step 7:

[1934] When a user participates in crowdfunding, they enter their payment information and make a donation. The terminal sends the payment information to the server, which stores it in a database. Donations are automatically managed, and any surplus funds are donated to relevant organizations.

[1935] Input: Intention to participate in crowdfunding and payment information

[1936] Output: Payment data and donation management stored on the server

[1937] This will enable effective mental health care to be provided during disasters and in peacetime.

[1938] 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.

[1939] 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.

[1940] 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.

[1941] [Fourth embodiment]

[1942] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1943] 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.

[1944] 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).

[1945] 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.

[1946] 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.

[1947] 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).

[1948] 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.

[1949] 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.

[1950] 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.

[1951] 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.

[1952] 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.

[1953] 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.

[1954] 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."

[1955] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input information by voice or text, an analysis means for analyzing the information received from the input means and generating mental health care content, a provision means for providing the mental health care content generated by the analysis means to users, and a notification means for acquiring disaster information and starting crowdfunding.

[1956] System configuration

[1957] The system consists of the following major components:

[1958] 1. Input Method

[1959] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[1960] 2. Analysis method

[1961] The system converts voice data sent from the device into text, analyzes the text data, and uses a natural language processing engine to analyze the input content and generate relevant mental care content.

[1962] 3. Means of provision

[1963] The content of mental care generated by the analysis means is sent to the terminal and displayed to the user, who can then receive advice through the application.

[1964] 4. Means of notification

[1965] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[1966] 5. Database

[1967] The system stores basic user information and usage data, and manages data to provide appropriate services both in normal times and in the event of a disaster.

[1968] Program processing

[1969] The program of this system performs the following processes.

[1970] User Registration and Settings

[1971] The user downloads the app and enters basic information such as name, age, industry, and income on the membership registration screen.

[1972] The terminal transmits the input information to the server.

[1973] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[1974] Mental care through voice and chat

[1975] The user inputs the details of the mental care he or she desires through voice or chat.

[1976] The terminal transmits the input data to the server.

[1977] The server analyzes the input using a natural language processing engine, generates appropriate mental care responses, and sends them to the device.

[1978] The terminal displays the response from the server to the user.

[1979] Disaster response

[1980] The server acquires disaster information from an external disaster information service.

[1981] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[1982] Users join the crowdfunding campaign and enter their payment information.

[1983] The terminal transmits the payment information to the server.

[1984] The server manages the donations and donates any surplus funds to relevant organizations.

[1985] Specific examples

[1986] Examples of use in normal times

[1987] 1. User A downloads the app and registers by entering basic information.

[1988] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[1989] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[1990] 4. User A checks the advice he received and puts it into practice.

[1991] Examples of use during disasters

[1992] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[1993] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[1994] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[1995] 4. Crowdfunding funds will cover operations and provide personalized care.

[1996] This invention makes it possible to provide effective mental health care during disasters as well as during peacetime, and provides a system that can quickly respond to market needs.

[1997] The processing flow will be explained below.

[1998] Program processing steps

[1999] User Registration and Settings

[2000] Step 1:

[2001] User: Downloads the app and installs it on their smartphone or tablet.

[2002] Step 2:

[2003] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[2004] Step 3:

[2005] Terminal: Sends the entered information to the server.

[2006] Step 4:

[2007] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[2008] Mental care through voice and chat

[2009] Step 1:

[2010] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[2011] Step 2:

[2012] Terminal: Sends input voice data and chat text to the server.

[2013] Step 3:

[2014] Server: Converts the received voice data into text and analyzes it together with the chat text using a natural language processing engine.

[2015] Step 4:

[2016] Server: Based on the analysis results, generate appropriate mental care responses and send them to the device.

[2017] Step 5:

[2018] Terminal: Displays the answer received from the server to the user.

[2019] Step 6:

[2020] User: Review the answers received and implement them as needed.

[2021] Disaster response

[2022] Step 1:

[2023] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[2024] Step 2:

[2025] Server: When new disaster information is detected, it starts responding.

[2026] Step 3:

[2027] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[2028] Step 4:

[2029] User: Receives notification and decides whether to participate in crowdfunding.

[2030] Step 5:

[2031] User: When participating in crowdfunding, enter your payment information and make a donation.

[2032] Step 6:

[2033] Terminal: Sends payment information to the server.

[2034] Step 7:

[2035] Server: Processes payment information and manages crowdfunding funds.

[2036] Step 8:

[2037] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[2038] Database construction and understanding of social issues

[2039] Step 1:

[2040] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[2041] Step 2:

[2042] Server: The collected data is anonymized and stored securely in a database.

[2043] Step 3:

[2044] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[2045] Step 4:

[2046] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[2047] Step 5:

[2048] Server: Sends the generated reports to related organizations and facilitates collaboration.

[2049] Example 1

[2050] 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."

[2051] Currently, mental health care for disaster victims is inadequate, and there is a lack of support to alleviate the mental burden of disaster victims. Providing continuous mental health care during peacetime is also an issue. Furthermore, the management of crowdfunding platforms to respond quickly and effectively to disasters is inconsistent, which can lead to insufficient support for users.

[2052] 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.

[2053] In this invention, the server includes an input means for users to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, a notification means for acquiring disaster information and notifying the user that crowdfunding has begun, a means for storing basic user information in a database, a means for providing mental care to reduce the user's stress and anxiety during peacetime and disasters, a means for analyzing the generated mental care content, a means for displaying advice to the user, and a means for anonymizing the information stored in the database and analyzing regional mental health trends for each disaster. This enables effective and prompt provision of mental health care during disasters and peacetime, and also improves the management of support through crowdfunding.

[2054] "Input means" refers to the function of a device or software that allows a user to input information about mental health care by voice or text.

[2055] The "analysis means" is a processing function for analyzing information received from the input means and generating appropriate mental care content.

[2056] The "provision means" is a system function for providing the content of mental care generated by the analysis means to the user.

[2057] "Notification means" is a system function for obtaining disaster information and sending a notification to users to start crowdfunding.

[2058] "Means for storing data in a database" refers to the function of a data management system for recording and managing basic information about users and information about mental care.

[2059] "Means for providing mental care during peacetime and disasters" is a system function that provides advice and measures to help users reduce stress and anxiety.

[2060] The "means for analyzing the generated mental care content" is a system function that reanalyzes the content of the mental care to be provided in order to make it more effective in accordance with the current state of the user.

[2061] The "means for displaying advice to the user" is a system function that displays advice generated based on the analysis results on the user's device.

[2062] "Anonymization means" refers to a system function that converts user information stored in a database into a form that does not allow individuals to be identified.

[2063] The "means for analyzing regional mental health trends" is a system function that analyzes mental health trends for each designated region and extracts issues and needs specific to that region.

[2064] This invention is a system for providing mental health care during disasters and in peacetime. Specifically, it includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental health care content, a provision means for providing the user with the mental health care content generated by the analysis means, a notification means for acquiring disaster information and starting crowdfunding, and a means for storing basic user information in a database. An embodiment of this system is described below.

[2065] Hardware and software used

[2066] 1. Input Method

[2067] Hardware: Smartphones, tablets

[2068] Software: Voice input applications, text input fields

[2069] 2. Analysis method

[2070] Hardware: Server

[2071] Software: Natural language processing engine (e.g., Google Cloud Natural Language, IBM Watson)

[2072] 3. Means of provision

[2073] Hardware: Smartphones, tablets

[2074] Software: Application interface, display UI components

[2075] 4. Means of notification

[2076] Hardware: Server

[2077] Software: API with disaster information services (e.g., Yahoo! Disaster Prevention Bulletin, J-Alert), push notification services (e.g., Firebase Cloud Messaging)

[2078] 5. How to store data in a database

[2079] Hardware: Server

[2080] Software: Database management system (e.g. MySQL, PostgreSQL)

[2081] System program processing

[2082] User Registration and Settings

[2083] A user downloads the app, launches it, and navigates to the membership registration screen. The user enters basic information such as name, age, industry, and income. The device sends this input data to the server. The server receives this information and stores it in a database. The server then generates recommended settings based on the user's settings and sends them to the device.

[2084] Mental care through voice and chat

[2085] The user inputs the desired mental care information by voice or text. The device sends the input data to the server. The server uses a natural language processing engine to analyze the input and generate an appropriate mental care response. The server then sends the generated mental care response to the device, which then displays the response to the user.

[2086] Disaster response

[2087] The server obtains disaster information from an external disaster information service. When the server detects the disaster information, it sends a notification to the user that crowdfunding has begun. The user participates in crowdfunding and enters payment information. The terminal sends the payment information to the server, which manages the donations and donates any surplus funds to relevant organizations.

[2088] Specific examples

[2089] (Example of normal use)

[2090] 1. User A downloads the app and registers by entering basic information.

[2091] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[2092] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[2093] 4. User A checks the advice he received and puts it into practice.

[2094] (Example of use during a disaster)

[2095] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[2096] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[2097] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[2098] 4. Crowdfunding funds will cover operations and provide personalized care.

[2099] Prompt Sentence Examples

[2100] An example of a prompt is, "Please give me some advice on how to stay calm and sleep well in a shelter on a very cold day."

[2101] This invention provides specific embodiments for providing effective mental health care during disasters and in peacetime.

[2102] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2103] Step 1:

[2104] The user downloads the app, launches it, and goes to the membership registration screen.

[2105] Input: User action (downloading and launching the app)

[2106] Output: Display of member registration screen

[2107] Specific operation: The user installs the app from the Google Play Store or Apple App Store, opens the app, and the membership registration screen appears.

[2108] Step 2:

[2109] The user enters basic information such as name, age, industry, and income.

[2110] Input: User's basic information (name, age, industry, income, etc.)

[2111] Output: Send request with basic information entered

[2112] Specific operation: The user enters the requested information into the registration form using the keyboard and presses the submit button to send the data to the server.

[2113] Step 3:

[2114] The terminal transmits these input data to the server.

[2115] Input: User's basic information (name, age, industry, income, etc.)

[2116] Output: Message sent to server

[2117] Specific operation: The app sends the entered data in JSON format to the server, and the server returns a reception completion message.

[2118] Step 4:

[2119] The server receives this information and stores it in a database.

[2120] Input: User's basic information (name, age, industry, income, etc.)

[2121] Output: Information stored in the database

[2122] Specific operation: The server uses a database management system (e.g., MySQL) to insert the received information into the appropriate table and store it.

[2123] Step 5:

[2124] The server generates recommended settings based on the user's settings and sends them to the device.

[2125] Input: User basic information stored in the database

[2126] Output: Message sent with recommended settings

[2127] What it does: The server uses an algorithm to generate recommended settings and returns them to the device in JSON format. The user can then confirm and save the settings.

[2128] Step 6:

[2129] The user inputs the details of the mental care he or she desires by voice or text.

[2130] Input: User's mental health input (voice or text)

[2131] Output: Request to send audio or text data

[2132] What happens: The user touches the microphone icon in the app to begin voice input, or types a message into the text input field.

[2133] Step 7:

[2134] The terminal sends the input data to the server.

[2135] Input: User's mental health input (voice or text)

[2136] Output: Message sent to server

[2137] Specific operation: The app converts the audio data into text data and sends this converted text in JSON format to the server.

[2138] Step 8:

[2139] The server analyzes the input using a natural language processing engine.

[2140] Input: Input data (text) about the user's mental health care

[2141] Output: Mental care answer

[2142] Specific operation: The server calls a natural language processing engine (e.g., Google Cloud Natural Language), performs analysis, and generates appropriate mental health care answers.

[2143] Step 9:

[2144] The server generates mental care answers and sends them to the terminal.

[2145] Input: Generated mental health care answers

[2146] Output: A message to the terminal indicating that transmission is complete

[2147] What it does: The server generates a response and sends it back to the device in JSON format, along with advice and links to resources.

[2148] Step 10:

[2149] The terminal displays the response from the server to the user.

[2150] Input: Generated mental health care answers

[2151] Output: Advice displayed

[2152] Specific operation: The app displays the received answer on the screen, and the user can view it and receive advice.

[2153] Step 11:

[2154] The server acquires disaster information from an external disaster information service.

[2155] Input: Data from external disaster information service

[2156] Output: Disaster information acquisition completion message

[2157] Specific operation: The server periodically makes API calls to obtain disaster information in real time.

[2158] Step 12:

[2159] When the server detects disaster information, it sends a notification to the user that crowdfunding has begun.

[2160] Input: Acquired disaster information

[2161] Output: Crowdfunding start notification message

[2162] Specific operation: The server generates a notification message and sends it to the user using a push notification service (e.g., Firebase Cloud Messaging).

[2163] Step 13:

[2164] A user joins a crowdfunding campaign and enters payment information.

[2165] Input: Payment information (credit card information, etc.)

[2166] Output: Send request

[2167] What happens: The user opens the notification, enters their payment information, and is taken to the crowdfunding page.

[2168] Step 14:

[2169] The terminal sends the payment information to the server.

[2170] Input: User's payment information

[2171] Output: Message sent to server

[2172] What it does: The app sends the entered payment information securely to the server using an SSL / TLS connection.

[2173] Step 15:

[2174] The server manages the donations and donates any surplus funds to relevant organizations.

[2175] Input: Crowdfunding donation data

[2176] Output: Donation management data and remittance information to relevant organizations

[2177] What it does: The server uses a backend system (e.g., PayPal API) to collect and manage donations, and ensures that donations are distributed to the appropriate organizations.

[2178] (Application example 1)

[2179] 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."

[2180] When disasters occur, victims need to be able to effectively reduce the psychological stress and anxiety they experience during evacuation. Furthermore, there is no system in place to provide prompt, appropriate mental health care during evacuation, so this issue needs to be addressed.

[2181] 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.

[2182] In this invention, the server includes an input means for a user to input information by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the user to start crowdfunding, and a means for providing mental health care during evacuation in the event of a disaster by linking the vehicle and smartphone. This makes it possible to provide psychological support to evacuees in real time and reduce anxiety and stress during evacuation.

[2183] - "Input means" refers to an interface that allows a user to input information about mental health into the system by voice or text.

[2184] The "analysis means" is a function for analyzing the voice or text data received from the input means and generating appropriate mental care content.

[2185] The "provision means" is a function that provides the content of mental care generated by the analysis means to the user.

[2186] The "notification means" is a function that acquires disaster information and notifies users to start crowdfunding based on that information.

[2187] "Mental healthcare means during evacuation through collaboration between autonomous vehicles and smartphones" is a function that provides mental healthcare through collaboration between autonomous vehicles and smartphones during evacuation in the event of a disaster.

[2188] A "database" is a system that stores basic information and usage data of users and analyzes and provides them as needed.

[2189] "Crowdfunding" is an online platform that raises funds for specific causes in the event of a disaster.

[2190] This invention is a system for providing mental health care during disasters and in peacetime. The system includes an input means for users to input voice or text, an analysis means, a provision means, and a notification means. It also includes a means for providing mental health care during evacuation in the event of a disaster by linking an autonomous vehicle with a smartphone.

[2191] Users use their smartphones to input their mental health concerns and problems using voice or text. This voice is picked up by the smartphone's microphone, and text is entered using the keyboard. The input data is sent to a server and analyzed using a natural language processing engine. For example, a natural language processing engine such as spaCy is used for this analysis.

[2192] The mental care content generated by the analysis means is sent to the user's smartphone by the provision means. The user receives advice through the application. This advice can be displayed in text or played back as audio.

[2193] The system obtains disaster information from an external disaster information service. Once this information is obtained, the notification means automatically notifies users that crowdfunding has begun. The funds raised through crowdfunding will be used to support the disaster-stricken areas.

[2194] Furthermore, when evacuating in the event of a disaster, autonomous vehicles with autonomous driving capabilities will be linked to smartphones to provide users with mental health care during evacuation. This linkage will provide a function that allows users to receive psychological support with peace of mind even while evacuating.

[2195] Furthermore, for mental health care in normal times, basic information and usage data of users will be stored in a database. The stored data will be anonymized and used to analyze mental health trends in each disaster-stricken area.

[2196] Specific examples

[2197] Examples of use in normal times

[2198] 1. A user downloads the app and registers by entering basic information.

[2199] 2. When a user feels stressed, they launch the app and type "I can't sleep lately" in chat format.

[2200] 3. The server analyzes the input, generates advice on "how to relax," and sends it to the device.

[2201] 4. The user checks and implements the advice received.

[2202] Examples of use during disasters

[2203] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[2204] 2. The user launches the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[2205] 3. The server analyzes the voice data, generates mental care advice, and sends it to the device.

[2206] 4. Crowdfunding funds will cover operations and provide personalized care.

[2207] Prompt Sentence Examples

[2208] Please enter your user information in the following format:

[2209] Name: Name

[2210] Age: 30

[2211] Occupation: Engineer

[2212] Income: 50,000

[2213] Next, enter your mental health question or concern (e.g., "I'm feeling anxious about my current situation").

[2214] Finally, would you like to receive notifications when the app receives disaster information? (Yes / No)

[2215] This system will enable effective mental health care during disasters and in peacetime, and will enable a rapid response to market needs.

[2216] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2217] Step 1:

[2218] A user downloads the app using a smartphone and enters basic information (such as name, age, occupation, and income). This data is entered through the app's interface and displayed on the smartphone screen.

[2219] Input: Basic information such as name, age, occupation, income, etc.

[2220] Output: Data with basic information entered

[2221] Step 2:

[2222] The device sends the entered basic information to the server, which receives the information, stores it in a database, generates recommended settings for the user, and sends them to the device.

[2223] Input: User basic information

[2224] Data processing: Formatting and saving basic information

[2225] Output: Basic information saved and recommended settings generated

[2226] Step 3:

[2227] Users input their desired mental health care needs through voice or text, and the input data is collected by their smartphone.

[2228] Input: Mental health content in audio or text format

[2229] Output: Audio or text data

[2230] Step 4:

[2231] The device converts the input voice into text using a speech recognition library (e.g., speech_recognition), and the converted text data is sent to the server.

[2232] Input: Audio or text data

[2233] Data processing: speech to text conversion

[2234] Output: Text data

[2235] Step 5:

[2236] The server analyzes the received text data using a natural language processing engine (e.g., spaCy) and generates mental care content.

[2237] Input: Text data

[2238] Data Computing: Analysis with Natural Language Processing

[2239] Output: Generated mental care content

[2240] Step 6:

[2241] The server sends the generated mental care information to the terminal, which then displays it to the user. The display is done in both text and audio format.

[2242] Input: Generated mental care content

[2243] Output: Mental care content displayed to the user

[2244] Step 7:

[2245] The server obtains disaster information from an external disaster information service and notifies the user of the start of crowdfunding based on this information.

[2246] Input: External disaster information

[2247] Output: Crowdfunding notification

[2248] Step 8:

[2249] In the event of a disaster, users' smartphones will be connected to autonomous vehicles to provide mental health care during evacuation. This connection will enable people to receive psychological support in real time.

[2250] Input: Automatic vehicle coordination information, user location information

[2251] Output: Real-time mental health care support

[2252] These steps will ensure effective mental health care during disasters and in peacetime.

[2253] 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.

[2254] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[2255] System configuration

[2256] 1. Input Method

[2257] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[2258] 2. Emotion Engine

[2259] The system analyzes the user's emotions using voice and text data received from the input means, and uses natural language processing and emotion analysis algorithms to assess the user's emotional state in real time.

[2260] 3. Analysis method

[2261] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated.

[2262] 4. Means of provision

[2263] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[2264] 5. Means of notification

[2265] Disaster information is obtained from an external disaster information service and users are notified of the start of crowdfunding.

[2266] 6. Database

[2267] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[2268] Program processing

[2269] The program of this system performs the following processes.

[2270] User Registration and Settings

[2271] A user downloads the app and installs it on their smartphone or tablet.

[2272] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income on the membership registration screen.

[2273] The terminal transmits the input information to the server.

[2274] The server stores the received information in a database, generates recommended settings, and sends them to the device.

[2275] Mental care through voice and chat

[2276] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[2277] The terminal transmits the input voice data and chat text to the server.

[2278] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine.

[2279] The server generates appropriate mental care content based on the emotional data analyzed by the emotion engine and sends it to the terminal.

[2280] The terminal displays the response received from the server to the user.

[2281] The user checks the received answers and implements them as necessary.

[2282] Disaster response

[2283] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[2284] When the server detects new disaster information, it begins responding.

[2285] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[2286] Users will receive a notification and can choose whether or not to participate in crowdfunding.

[2287] When a user participates in crowdfunding, they enter their payment information and make a donation.

[2288] The terminal transmits the payment information to the server.

[2289] The server automatically manages donations and donates any surplus funds to relevant organizations.

[2290] Specific examples

[2291] Examples of use in normal times

[2292] 1. User A downloads the app and registers by entering basic information.

[2293] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[2294] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[2295] 4. The server generates advice on "how to relax" and sends it to the device.

[2296] 5. User A checks the advice he received and puts it into practice.

[2297] Examples of use during disasters

[2298] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[2299] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[2300] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[2301] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[2302] 5. User B confirms the advice received and reduces the mental load.

[2303] This invention will provide effective mental health care using an emotion engine during disasters and in normal times, enabling appropriate support according to the user's emotional state. Furthermore, by storing emotion data in a database and using it for future improvements, further improvements in the service are expected.

[2304] The processing flow will be explained below.

[2305] Program processing steps

[2306] User Registration and Settings

[2307] Step 1:

[2308] User: Downloads the app and installs it on their smartphone or tablet.

[2309] Step 2:

[2310] User: Launches the app for the first time and enters basic information such as name, age, industry, and income on the membership registration screen.

[2311] Step 3:

[2312] Terminal: Sends the entered information to the server.

[2313] Step 4:

[2314] Server: Stores the received information in a database, generates recommended settings, and sends them to the device.

[2315] Mental care through voice and chat (using emotion engine)

[2316] Step 1:

[2317] User: Launch the app and enter the details of the mental care they would like to receive via voice or chat.

[2318] Step 2:

[2319] Terminal: Sends input voice data and chat text to the server.

[2320] Step 3:

[2321] Server: Converts received voice data into text, using voice recognition technology if necessary.

[2322] Step 4:

[2323] Server: Sends text data to the emotion engine and analyzes the user's emotional state.

[2324] Step 5:

[2325] Server: Based on the analysis results from the emotion engine, the input content and emotional state are comprehensively evaluated, and appropriate mental health care responses are generated.

[2326] Step 6:

[2327] Server: Sends the generated mental care answers to the device.

[2328] Step 7:

[2329] Terminal: Displays the answer received from the server to the user.

[2330] Step 8:

[2331] User: Review the answers received and implement them as needed.

[2332] Disaster response

[2333] Step 1:

[2334] Server: Regularly obtains disaster information such as earthquakes and typhoons from external disaster information services.

[2335] Step 2:

[2336] Server: When new disaster information is detected, it starts responding.

[2337] Step 3:

[2338] Server: Sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[2339] Step 4:

[2340] User: Receives notification and decides whether to participate in crowdfunding.

[2341] Step 5:

[2342] User: When participating in crowdfunding, enter your payment information and make a donation.

[2343] Step 6:

[2344] Terminal: Sends payment information to the server.

[2345] Step 7:

[2346] Server: Processes payment information and manages crowdfunding funds.

[2347] Step 8:

[2348] Server: Automatically donates surplus funds raised through crowdfunding to relevant organizations.

[2349] Database construction and understanding of social issues

[2350] Step 1:

[2351] Server: Collects user mental care usage data (input content, usage time, frequency, etc.).

[2352] Step 2:

[2353] Server: The collected data is anonymized and stored securely in a database.

[2354] Step 3:

[2355] Server: Analyzes accumulated data to identify trends in mental health and signs of social problems.

[2356] Step 4:

[2357] Server: Generates reports based on the analysis results and prepares them for delivery to relevant organizations.

[2358] Step 5:

[2359] Server: Sends the generated reports to related organizations and facilitates collaboration.

[2360] Example 2

[2361] 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."

[2362] The problem is that users' mental health care is not provided adequately and appropriate support according to their emotional state is lacking, both during disasters and in peacetime.Furthermore, there is no established method for obtaining disaster information in a timely manner and promptly encouraging users to participate in crowdfunding.

[2363] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input voice or text, an analysis means for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms, a provision means for providing the mental care content generated by the analysis means to the user, a notification means for acquiring disaster information and notifying the start of crowdfunding, and a means for automatically managing donations and distributing them to relevant organizations. This allows users to receive appropriate mental care according to their emotional state and enables them to quickly participate in crowdfunding and contribute to relief efforts in the event of a disaster.

[2364] "Input means" refers to a device or interface that allows a user to input information by voice or text.

[2365] "Analysis means" refers to algorithms or software for analyzing information received from the input means and generating mental care content using natural language processing and emotion analysis algorithms.

[2366] The "provision means" refers to a device or interface for providing the content of mental care generated by the analysis means to the user.

[2367] "Notification means" refers to the mechanisms and infrastructure for obtaining disaster information and notifying users of the start of crowdfunding.

[2368] "Automated donation management means" refers to a system or algorithm that receives donations from users, manages them appropriately, and distributes them to relevant organizations.

[2369] "Means for generating recommended settings" refers to algorithms or software for generating optimal mental health care settings based on basic user information.

[2370] "Means for entering and saving basic information" refers to an interface or system that allows users to enter basic information such as name, age, occupation, and income and save it in a database.

[2371] "Means for storing emotional data in a database" refers to a mechanism for storing the emotional data obtained by the analysis means in a database and using it to improve mental health care in the future.

[2372] "Anonymization methods" refers to algorithms or technologies used to anonymize information stored in a database so that individuals cannot be identified.

[2373] "Disaster information services" refers to external services and organizations that provide information about disasters.

[2374] "Smart devices" refers to portable electronic devices that can connect to the Internet, such as smartphones and tablets.

[2375] This invention is a system for providing mental health care to users during disasters and in normal times, and by combining an emotion engine that recognizes the user's emotions, it provides appropriate mental care according to the user's emotional state. This system is composed of the following main components:

[2376] 1. Input Method

[2377] Users input their mental health concerns and problems via voice or text using the microphone and keyboard of their smartphone or tablet.

[2378] 2. Emotion Engine

[2379] The system analyzes the user's emotions using voice and text data received from the input means. Specifically, it uses natural language processing and emotion analysis algorithms (e.g., IBM Watson Natural Language Understanding) to evaluate the user's emotional state in real time.

[2380] 3. Analysis method

[2381] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated using natural language processing algorithms (e.g., Google Cloud NLP).

[2382] 4. Means of provision

[2383] The content of mental care generated by the analysis means is sent to the terminal and provided to the user, who can receive advice and care content through the application.

[2384] 5. Means of notification

[2385] Obtain disaster information and notify users of the start of crowdfunding. Disaster information is obtained from an external disaster information service (e.g., Japan Meteorological Agency API).

[2386] 6. Database

[2387] The user's basic information and usage data are stored, including emotional data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[2388] Specific examples

[2389] Examples of use in normal times

[2390] 1. User A downloads the app and registers by entering basic information.

[2391] Specific operation: The user inputs "Yamada Taro, 30 years old, engineer, annual income 4 million yen."

[2392] 2. When User A feels stressed, he launches the app and types in chat, "I haven't been able to sleep lately."

[2393] 3. The server analyzes the input and uses an emotion engine to identify the emotion of "anxiety."

[2394] 4. The server generates advice on "how to relax" and sends it to the device.

[2395] 5. User A checks the advice he received and puts it into practice.

[2396] Examples of use during disasters

[2397] 1. When a disaster occurs, the server obtains information from an external disaster information service and sends notifications to users in the relevant areas.

[2398] 2. User B starts the app at the evacuation shelter and voice-inputs, "I'm anxious and can't sleep."

[2399] 3. The server analyzes the voice data and uses an emotion engine to identify the emotion of "fear."

[2400] 4. The server generates mental care advice based on the emotional state and sends it to the device.

[2401] 5. User B confirms the advice received and reduces the mental load.

[2402] Example prompts for generative AI models

[2403] By inputting the following prompt sentences into the generative AI model, specific explanations and suggestions for improvement of the system can be obtained.

[2404] Prompt statement:

[2405] "Please explain the mental health care system I invented. Users download the app, enter their basic information, and then enter their desired mental health care via voice or chat. The server then analyzes the information using an emotion engine and provides appropriate mental health care. In the event of a disaster, the system will notify users of the start of a crowdfunding campaign so that they can make donations. Please suggest any ideas for improving this system."

[2406] This invention allows users to receive effective mental health care using an emotion engine both during disasters and in normal times. It also allows users to participate in community support through crowdfunding, enabling appropriate support tailored to the user's emotional state.

[2407] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2408] Step 1:

[2409] A user downloads and installs the app on their smartphone or tablet.

[2410] Specific behavior: The user searches for "mental healthcare app" in the App Store or Google Play Store and taps the download button to begin installation.

[2411] Step 2:

[2412] When a user launches the app for the first time, they enter basic information such as their name, age, industry, and income.

[2413] Specific operation: The user enters "Yamada Taro, 30 years old, engineer, annual income 4 million yen" in the text box and taps the send button.

[2414] Input: Basic information such as name, age, industry, income, etc.

[2415] Output: Basic information data entered

[2416] Step 3:

[2417] The terminal transmits the input information to the server.

[2418] Specific operation: The device encrypts data via the Internet using SSL / TLS and sends it to the server.

[2419] Input: Basic information data when tapping the send button

[2420] Output: Basic information data sent to the server

[2421] Step 4:

[2422] The server stores the received information in a database and generates optimal configuration recommendations for the user.

[2423] How it works: The server stores user information in a MySQL or PostgreSQL database and uses AI algorithms to calculate recommended settings.

[2424] Input: Basic information data

[2425] Output: User information stored in the database, recommended settings data

[2426] Step 5:

[2427] The server generates recommended settings and sends them to the device.

[2428] Specific operation: The server sends the recommended settings to the device in JSON format.

[2429] Input: Recommended setting data

[2430] Output: Recommended configuration data sent to the device

[2431] Step 6:

[2432] The user launches the app and inputs the details of the mental care they would like to receive via voice or chat.

[2433] Specific behavior: The user types "I can't sleep lately" in the chat box and taps the send button, or taps the microphone icon to input voice.

[2434] Input: Text or voice message regarding your request for mental health care

[2435] Output: Sent audio file or text data

[2436] Step 7:

[2437] The terminal sends input voice data and chat text to the server.

[2438] Specific operation: The device saves the voice data as an audio file and sends it to the server along with the text data.

[2439] Input: Audio file or text data

[2440] Output: Audio file or text data sent to the server

[2441] Step 8:

[2442] The server converts the voice data into text and analyzes it using an emotion engine.

[2443] How it works: The server converts the speech to text using the Google Cloud Speech-to-Text API and performs sentiment analysis using IBM Watson Natural Language Understanding.

[2444] Input: Audio file or chat text

[2445] Output: Parsed text data and sentiment data

[2446] Step 9:

[2447] The server generates appropriate mental care content based on emotional data.

[2448] Specific operation: The server generates advice such as "how to relax" based on the analysis results.

[2449] Input: Emotion data

[2450] Output: Mental care advice

[2451] Step 10:

[2452] The mental care content generated by the server is sent to the terminal.

[2453] Specific operation: The server sends mental care advice in JSON format to the terminal.

[2454] Input: Mental care advice

[2455] Output: Mental health advice sent to the device

[2456] Step 11:

[2457] The terminal displays the mental care content received from the server to the user.

[2458] Specific behavior: The device displays advice on the chatbot interface.

[2459] Input: Mental care advice

[2460] Output: Mental health advice displayed to the user

[2461] Step 12:

[2462] The user reviews the advice received and implements it as necessary.

[2463] Specific action: The user reads the displayed advice and performs the action, such as taking a deep breath.

[2464] Input: Mental health advice displayed to the user

[2465] Output: Practical mental health advice

[2466] Step 13:

[2467] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service.

[2468] Specific operation: The server periodically requests the latest disaster information using the Japan Meteorological Agency API.

[2469] Input: APIs that are requested periodically

[2470] Output: Acquired disaster information

[2471] Step 14:

[2472] When the server detects new disaster information, it begins disaster response.

[2473] Specific operation: When the server detects new disaster data, it launches the corresponding module.

[2474] Input: Acquired disaster information

[2475] Output: Corresponding modules launched

[2476] Step 15:

[2477] The server sends a notification of the start of crowdfunding to users in the disaster-stricken area.

[2478] Specific operation: The server generates push notifications and sends them to users in the disaster area.

[2479] Input: Disaster information, user information

[2480] Output: Push notification sent

[2481] Step 16:

[2482] The user receives a notification and can choose whether to participate in the crowdfunding campaign.

[2483] Specific operation: The user taps the notification on the device and moves to the crowdfunding participation screen.

[2484] Input: Push notification

[2485] Output: Crowdfunding participation selection

[2486] Step 17:

[2487] When a user participates in crowdfunding, they enter their payment information and make a donation.

[2488] Specific behavior: The user enters their credit card information and confirms the donation amount.

[2489] Input: Payment information, donation amount

[2490] Output: Donation process completed

[2491] Step 18:

[2492] The terminal sends the payment information to the server.

[2493] What happens: The terminal encrypts the payment information and sends it to the server.

[2494] Input: Payment information

[2495] Output: Payment information sent to the server

[2496] Step 19:

[2497] The server manages the donations and distributes them to the relevant organizations.

[2498] Specific operation: The server manages donations in a dedicated account and periodically transfers any surplus funds to relevant organizations.

[2499] Input: Donation information

[2500] Output: Donations managed, funds sent

[2501] The above are the specific processing steps of this system. This system enables users to receive appropriate mental care during both normal times and disasters.

[2502] (Application example 2)

[2503] 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."

[2504] In the past, mental health care during disasters and in peacetime was often provided with limited resources, making it difficult to effectively support the mental health of disaster victims and general users. Psychological support is particularly urgent during disasters, but the lack of a system to respond to this has been an issue. Furthermore, providing real-time mental health care using emotion analysis technology has not been realized.

[2505] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2506] In this invention, the server includes an input means for a user to input by voice or text, an analysis means for analyzing information received from the input means and generating mental care content, a provision means for providing the user with the mental care content generated by the analysis means, an emotion engine means for analyzing the user's emotional state using an emotion analysis algorithm, and a generation AI model means for generating appropriate mental care advice in real time to provide mental care during peacetime. This makes it possible to provide effective mental health care using emotion analysis both during disasters and peacetime.

[2507] "Input means" refers to the means by which users input information about mental health care by voice or text, and refers to the microphone or keyboard of a device such as a smartphone or tablet.

[2508] The "analysis means" is a means for analyzing information received from the input means and generating mental care content, and uses natural language processing and emotion analysis algorithms.

[2509] The "provision means" is a means for providing the content of mental care generated by the analysis means to the user, and displays advice and care content through an application.

[2510] The "notification means" is a means for obtaining disaster information and notifying users of the start of crowdfunding, and the notification is made based on data from the disaster information provision service.

[2511] The "emotion engine means" is a means for analyzing the user's emotional state using an emotion analysis algorithm, and evaluates emotions based on input voice and text data.

[2512] The "generative AI model means" is a means for generating appropriate mental care advice in real time to provide mental care in peacetime, and uses a generative AI model.

[2513] The present invention is a system for providing mental health care to a user during disasters and in normal times, and provides appropriate mental care according to the emotional state of the user. A specific embodiment of this system will be described.

[2514] System configuration

[2515] The system consists of the following major components:

[2516] 1. Input Method

[2517] Users input their worries and problems about mental health care by voice or text using the microphone and keyboard of their smartphone or tablet.

[2518] 2. Emotional Engine Means

[2519] The system uses emotion analysis algorithms to analyze the user's emotional state based on the voice and text data received from the input means. Specifically, it uses natural language processing libraries such as SpaCy and the Hugging Face emotion analysis model.

[2520] 3. Analysis method

[2521] Based on the emotional data analyzed by the emotion engine, the input content is analyzed and appropriate mental care content is generated. This analysis uses a generative AI model (e.g., OpenAI's GPT-3).

[2522] 4. Means of provision

[2523] The mental care content generated by the analysis means is sent to the device and provided to the user via an application on a smartphone or tablet.

[2524] 5. Means of notification

[2525] It obtains disaster information from external disaster information services and sends emergency notifications to users in disaster-affected areas, as well as notifying them of the start of crowdfunding.

[2526] 6. Database Means

[2527] The system stores basic information and usage data of users, including emotion data analyzed by the emotion engine. The stored data will be used to improve mental health care in the future.

[2528] Program processing explanation

[2529] The server receives information input by the user via voice or text and analyzes their emotional state using an emotion analysis algorithm. The input voice data and chat text are then processed using a natural language processing module (SpaCy) and an emotion analysis model (Hugging Face). Based on the resulting emotional data, a generative AI model (OpenAI's GPT-3) is used to generate appropriate mental health advice and provide it to the user. Furthermore, based on disaster information from the disaster information provision service, emergency notifications are sent to users in relevant areas. This enables effective mental health care during disasters and in peacetime.

[2530] Examples and prompts

[2531] Examples:

[2532] 1. Examples of use in normal times:

[2533] 1. The user types, "I've been feeling a lot of stress at work lately."

[2534] 2. The server analyzes the input and identifies the emotion "stress" using an emotion engine means.

[2535] 3. Use the generative AI model to generate "stress reduction advice" and provide it to the user.

[2536] 2. Examples of use in times of disaster:

[2537] 1. When a disaster occurs, the server obtains information from the disaster information service and sends notifications to users in the relevant areas.

[2538] 2. The user speaks, "I'm worried about the disaster and can't sleep."

[2539] 3. The server analyzes the voice data and identifies the emotion of "anxiety" using an emotion engine means.

[2540] 4. Use the generative AI model to generate and provide "advice to alleviate anxiety" to the user.

[2541] Example prompt:

[2542] "The user's emotional state is 'Stressed'. Please provide mental health advice for 'Stressed'."

[2543] "The user's emotional state is 'anxious'. Please provide mental health advice for 'anxiety'."

[2544] This system makes it possible to provide appropriate mental care in real time according to the user's emotional state.

[2545] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2546] Step 1:

[2547] The user downloads the app and installs it on their smartphone or tablet. When they launch it for the first time, they enter basic information such as their name, age, occupation, and income on the membership registration screen. The device sends the entered information to the server, which then stores the received information in a database. This registers the user's basic information in the system.

[2548] Input: User's basic information (name, age, occupation, income, etc.)

[2549] Output: User information that will be sent to the server and stored in the database

[2550] Step 2:

[2551] The user launches the app and inputs the details of their desired mental health care needs in voice or text format. The device then sends the input voice data or chat text to the server.

[2552] Input: User's mental health care needs (voice data or text data)

[2553] Output: Audio and text data sent to the server

[2554] Step 3:

[2555] The server converts the received voice data into text and analyzes it together with the chat text using an emotion engine. Specifically, it evaluates the emotional state using a natural language processing library (SpaCy) and an emotion analysis model (Hugging Face).

[2556] Input: Audio data and text data

[2557] Output: Emotion data (e.g., "stress," "anxiety," etc.)

[2558] Step 4:

[2559] The server generates appropriate mental health advice using a generative AI model (OpenAI's GPT-3) based on the emotional data analyzed by the emotion engine. The generative AI model generates advice based on the input emotional data and prompt sentence.

[2560] Input: "Emotion data" and "Prompt sentence"

[2561] Output: Generated mental health advice

[2562] Step 5:

[2563] The server sends the generated mental care advice to the device, which then displays it to the user. The user can then confirm and put the advice into practice.

[2564] Input: Generated mental health advice

[2565] Output: Mental health advice displayed on the user's device

[2566] Step 6:

[2567] The server periodically obtains disaster information such as earthquakes and typhoons from an external disaster information service. When new disaster information is obtained, the server sends an emergency notification to users in the disaster-affected area.

[2568] Input: Disaster information from external disaster information services

[2569] Output: Urgent notification sent to the user's device

[2570] Step 7:

[2571] When a user participates in crowdfunding, they enter their payment information and make a donation. The terminal sends the payment information to the server, which stores it in a database. Donations are automatically managed, and any surplus funds are donated to relevant organizations.

[2572] Input: Intention to participate in crowdfunding and payment information

[2573] Output: Payment data and donation management stored on the server

[2574] This will enable effective mental health care to be provided during disasters and in peacetime.

[2575] 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.

[2576] 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.

[2577] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2578] 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.

[2579] 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.

[2580] 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.

[2581] 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).

[2582] 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.

[2583] 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."

[2584] 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.

[2585] 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).

[2586] 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.

[2587] 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.

[2588] 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.

[2589] 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.

[2590] 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.

[2591] 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 ...

Claims

1. A system for providing mental health care to disaster victims in the event of a disaster, an input means for a user to input voice or text; an analysis means for analyzing the information received from the input means and generating content for mental care; providing means for providing the content of mental care generated by the analysis means to a user; A notification means for acquiring disaster information and notifying the start of crowdfunding; A system including:

2. The system of claim 1 further comprises a means for providing mental health care during peacetime and storing basic information of users in a database, and a means for initiating crowdfunding and automatically managing donations in the event of a disaster.

3. The system of claim 1 , further comprising means for anonymizing the information stored in the database and analyzing mental health trends by disaster area.

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