system

Abstract

We provide the system. [Solution] A user authentication means that receives authentication information from the user and authenticates the user by comparing it with a database, A supply support list management system that receives a list of necessary supplies from disaster-stricken users, stores it in a database, receives information on supplies that can be provided from support users, and manages the status of supply provision. A mental support matching system that receives information on mental support requests from disaster-stricken users, matches it with a list of support providers, and selects appropriate support providers, A system that includes data analysis tools to collect and analyze the history and feedback of users' support activities, extract the effectiveness and challenges of those activities, and reflect them in future support activities.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Japan is an area where earthquakes and other natural disasters occur frequently. During disasters, it is important to provide insufficient materials and mental support required by the affected people. However, during disasters, communication infrastructure may be damaged, making it difficult for affected people and supporters to connect directly. In addition, in the process until the affected people resume their daily lives, effective management and adjustment of material provision and mental support are required. There is a current situation where it is difficult to solve these problems quickly and effectively with existing methods.

Means for Solving the Problems

[0005] This invention provides a system including user authentication means, material support list management means, mental support matching means, and data analysis means. In this system, the user authentication means authenticates disaster victims and supporters, and the material support list management means manages a list of supplies needed by disaster victims and information on supplies provided by supporters. Furthermore, the mental support matching means collects information on the mental support needs of disaster victims and selects appropriate support providers to provide mental support to disaster victims. The data analysis means collects and analyzes the history of support activities and feedback, extracts the effectiveness and challenges of support activities, and reflects them in future support activities. This makes it possible to provide supplies and mental support to disaster victims quickly and effectively.

[0006] A "user authentication method" is a function that receives authentication information from a user and authenticates the user by comparing that information with a database.

[0007] The "supply support list management system" is a function that receives lists of necessary supplies from disaster-stricken users, stores them in a database, and also receives information on supplies that can be provided by support users to manage the status of supply provision.

[0008] The "mental support matching system" is a function that collects information on mental support requests from disaster-stricken users, matches it with a list of support providers, and selects appropriate support providers.

[0009] A "data analysis tool" is a function that collects the history and feedback of users' support activities, analyzes that data to extract the effectiveness and challenges of those support activities, and reflects these findings in future support activities.

[0010] A "disaster-affected user" is an individual or group that has been affected by a disaster and requires the provision of supplies or mental support.

[0011] A "support user" is an individual or organization that provides support to disaster victims through the provision of goods or mental support.

[0012] A "database" is a system for centrally managing and storing user information, material information, mental support information, feedback, and other data. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when combined with an emotion engine.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] <0In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the 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.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0027] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. This system includes user authentication means, supply support list management means, mental support matching means, and data analysis means.

[0035] User authentication method

[0036] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[0037] Material support list management method

[0038] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0039] Mental support matching method

[0040] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0041] Data analysis tools

[0042] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[0043] Specific example

[0044] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[0045] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[0046] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental health support via chat or video call.

[0047] This system allows users to receive disaster relief quickly and effectively, and enables support providers to deliver appropriate assistance.

[0048] The following describes the processing flow.

[0049] User registration and authentication process

[0050] Step 1:

[0051] The device displays a registration form to the user for entering information such as name, address, contact information, user ID, and password.

[0052] Step 2:

[0053] The user fills in the required information on the registration form and presses the submit button.

[0054] Step 3:

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

[0056] Step 4:

[0057] The server stores the received user information in the database.

[0058] Step 5:

[0059] The server generates a registration completion message and sends it to the terminal.

[0060] Step 6:

[0061] The device displays a registration completion message to the user.

[0062] Processing the list of material aid recipients.

[0063] Step 1:

[0064] The device displays a supply support list form to the affected user, allowing them to input the category, quantity, and priority of necessary supplies.

[0065] Step 2:

[0066] Disaster victims fill in the required information on the supplies support list form and press the submit button.

[0067] Step 3:

[0068] The terminal sends the entered supply list information to the server.

[0069] Step 4:

[0070] The server stores the received list of supplies in the database and updates the list of requested assistance.

[0071] Step 5:

[0072] The device displays an interface for the support user to view a list of people who need assistance.

[0073] Step 6:

[0074] Supporting users view the list of requested items, select the categories and quantities of supplies they can provide, and then press the submit button.

[0075] Step 7:

[0076] The terminal sends the selected material provision information to the server.

[0077] Step 8:

[0078] The server stores the received information about the provision of supplies in a database and updates the supply status.

[0079] Step 9:

[0080] The server notifies affected users of the status of supply provision.

[0081] Processing of mental support matching and management

[0082] Step 1:

[0083] The device displays a form for disaster victims to input information about their mental health support needs (such as the type of support they require and their preferred time).

[0084] Step 2:

[0085] Disaster victims enter information about their mental health support needs and press the submit button.

[0086] Step 3:

[0087] The terminal sends the entered mental support request information to the server.

[0088] Step 4:

[0089] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[0090] Step 5:

[0091] The server sends notifications to aid providers and disaster victims.

[0092] Step 6:

[0093] The device receives a notification and displays connection details for the disaster victim and the support provider.

[0094] Step 7:

[0095] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[0096] Data analysis processing

[0097] Step 1:

[0098] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[0099] Step 2:

[0100] After the device completes its support activities, it displays a feedback form to the user.

[0101] Step 3:

[0102] The user enters their opinions and feedback into the feedback form and presses the submit button.

[0103] Step 4:

[0104] The terminal sends the input feedback information to the server.

[0105] Step 5:

[0106] The server stores the feedback information it receives in the database.

[0107] Step 6:

[0108] The server uses generated AI to analyze the collected data.

[0109] Step 7:

[0110] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[0111] In this way, the system of the present invention sequentially carries out processes for effectively providing supplies and mental support in disaster-stricken areas.

[0112] (Example 1)

[0113] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0114] There is a need for a system that enables the rapid and effective provision of supplies and mental support between disaster victims and aid workers. However, current systems have several problems, including time lags in user authentication, the complexity of managing supply lists, inaccuracies in matching mental support, and the effort required to analyze the effectiveness and challenges of support activities. A system is needed that can solve these problems and provide the support that disaster victims need quickly and effectively.

[0115] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0116] In this invention, the server includes user authentication means, material support list management means, mental support matching means, and data analysis means. This enables the rapid and appropriate provision of support based on support requests from disaster victims, efficient support activities based on the analysis of the user's support activity history and feedback, and effective mental support through appropriate matching of supporters.

[0117] A "user authentication means" is a device or program that has the function of authenticating a user by receiving authentication information from the user and comparing it with a database.

[0118] A "supply support list management system" is a device or program that has the function of receiving a list of necessary supplies from disaster-stricken users, storing it in a database, and receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[0119] A "mental support matching system" is a device or program that receives information requesting mental support from disaster victims, matches it with a list of support providers to select an appropriate supporter, and notifies both parties.

[0120] "Data analysis means" refers to a device or program that has the function of collecting the history and feedback of user support activities, storing it in a database, analyzing it using a generated AI model, and proposing appropriate improvement measures.

[0121] A "server" is a central computer system that receives, processes, stores, and transmits data.

[0122] A "terminal" is a device that a user uses to access a system and send input information.

[0123] A "user" refers to an individual or group of disaster victims or supporters who use this system.

[0124] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system consists of a user authentication means, a supplies support list management means, a mental support matching means, and a data analysis means.

[0125] User authentication method

[0126] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by entering the required information (e.g., name, address, contact information, user ID, password) into a registration form using their device and submitting it. Alternatively, users can authenticate themselves by entering the required information into a login form and submitting it. Upon successful authentication, the user can begin using the system.

[0127] Material support list management method

[0128] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0129] Mental support matching method

[0130] The server receives information from disaster victims regarding their requests for mental support (support content, preferred time), matches it with a list of support providers, and selects appropriate supporters. The server matches the disaster victims' support requests with available support information and notifies both the disaster victims and the supporters. At the designated time, the disaster victims and supporters use chat or video calls via their devices to provide mental support.

[0131] Data analysis tools

[0132] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis tool uses a generative AI model to analyze the collected data in detail and propose appropriate improvement measures.

[0133] Specific example

[0134] 1. When a user registers for a new account

[0135] The user uses their device to enter their name, address, contact information, user ID, password, etc., into the registration form and submits it. The server stores the received information in its database and sends a registration completion message to the user.

[0136] 2. When disaster victims request material assistance

[0137] Disaster victims use a terminal to enter a list of necessary supplies and submit it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and submit them. The server registers the information about the donated supplies in its database and notifies the disaster victims.

[0138] 3. When disaster victims request mental health support

[0139] The disaster victim uses a device to input the type of support they need and their preferred time, then submits the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental support through chat or video call.

[0140] 4. When using generative AI models

[0141] The server collects past support activity data and analyzes it using a generative AI model. Based on the analysis results, it proposes measures to improve support activities and provides feedback to supporters.

[0142] Examples of prompts to input into a generative AI model

[0143] "Please describe the components of a system necessary to provide rapid assistance during a disaster. Also, please include the system's operating procedures and specific usage examples."

[0144] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance.

[0145] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0146] Step 1:

[0147] User Registration

[0148] The user uses their device to enter required information such as name, address, contact information, user ID, and password into the registration form and submits it. The entered data is sent to the server as information for each field.

[0149] The server analyzes the received information and stores it in a database. Then, it generates a registration completion message and sends it to the user via the terminal.

[0150] Input: User information (name, address, contact information, user ID, password)

[0151] Output: Messages confirming registration to the database and user registration.

[0152] Step 2:

[0153] User Login

[0154] The user opens the login form on their device and enters their user ID and password.

[0155] The terminal sends the entered information to the server.

[0156] The server compares the received user ID and password with the authentication information in the database and returns the authentication result to the terminal.

[0157] Authentication successful: Generate and send a message to the user granting permission to access the system.

[0158] Authentication failed: Generate an error message and send it to the user.

[0159] Input: User ID, Password

[0160] Output: Authentication result (success or failure), access permission message or error message.

[0161] Step 3:

[0162] Request for material assistance

[0163] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and submit it.

[0164] The terminal sends the input information to the server.

[0165] The server analyzes the received list of supplies and stores it in a database. It then updates the list of people needing assistance and sends notifications to those affected by the disaster.

[0166] Input: List of required supplies (category, quantity, priority)

[0167] Output: Store the list of needed supplies in the database, update the list of people requesting assistance, and notify disaster victims.

[0168] Step 4:

[0169] Registration of information on the provision of supplies

[0170] Supporters use a terminal to enter information about the supplies they can provide (category, quantity) and submit it.

[0171] The terminal sends the input information to the server.

[0172] The server analyzes the received information about the provision of supplies and stores it in a database. It then sends notifications to the affected people.

[0173] Input: Information on available supplies (category, quantity)

[0174] Output: Storage of information on the provision of supplies in the database, notification to disaster victims.

[0175] Step 5:

[0176] Request for mental support

[0177] Disaster victims use a device to input the type of mental support they want and their preferred time, then submit the information.

[0178] The terminal sends the input information to the server.

[0179] The server stores the received information requesting assistance in a database, compares it with a list of assistance providers to select appropriate helpers, and sends notifications to both the disaster victims and the assistance providers.

[0180] Input: Mental support request information (content, preferred time)

[0181] Output: Store information requesting assistance in the database, compare with the list of assistance providers, notify disaster victims, and notify assistance providers.

[0182] Step 6:

[0183] Providing mental support

[0184] Disaster victims and aid providers will initiate chat or video calls via their devices at a designated time.

[0185] The server monitors the connection initiation and provides assistance as needed.

[0186] Input: Chat or video call connection request

[0187] Output: Start of mental support session, session log data

[0188] Step 7:

[0189] Collection and analysis of support activity data

[0190] The server collects historical data on support activities and user feedback, and stores it in a database.

[0191] The server uses a generative AI model to analyze the data in detail, identify the effectiveness and challenges of support activities, and propose solutions for improvement.

[0192] Input: Support activity history data, feedback data

[0193] Output: Analysis results of effects and challenges, and proposed improvement measures.

[0194] Step 8:

[0195] Provide feedback

[0196] The server generates a feedback report based on the analysis results and improvement suggestions, and provides it to the supporter.

[0197] Supporters will use the feedback report to inform their next support activities.

[0198] Input: Analysis results, improvement suggestions

[0199] Output: Generation and provision of feedback reports

[0200] (Application Example 1)

[0201] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0202] In times of disaster, it is currently difficult for victims to receive necessary material support and mental health support quickly and effectively. Furthermore, there is a lack of systems to accumulate and analyze the effectiveness of these support activities as data and use it to improve future support activities.

[0203] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0204] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data collection means, and data analysis means using a generative AI model. This enables the rapid and effective provision of material support and mental support between disaster victims and supporters, and the improvement of future support activities through data analysis of support activities.

[0205] "User authentication means" refers to a function that verifies the user's identity by comparing authentication information provided by the user with a database.

[0206] A "supply support list management system" is a function that receives lists of necessary supplies from disaster victims, stores them in a database, and manages information on supplies that can be provided by supporters.

[0207] A "mental support matching system" is a function that matches disaster victims with appropriate support providers based on the type of mental support they desire and their preferred time.

[0208] "Data collection means" refers to a function that collects the history and feedback of users' support activities and stores them in a database.

[0209] "Data analysis method using generative AI models" refers to a function that analyzes collected support activity data using generative AI models and proposes appropriate improvement measures.

[0210] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during a disaster, and includes the following means:

[0211] User authentication method

[0212] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. The user registers by entering the required information (name, address, contact information, user ID, password, etc.) into a registration form using their device and submitting it. The server stores the received information in the database and sends a registration completion message to the user. Similarly, when logging in, the user enters the required information into a login form and submits it. The server then authenticates the user, and if authentication is successful, the user can begin using the system.

[0213] Material support list management method

[0214] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0215] Mental support matching method

[0216] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0217] Data acquisition methods

[0218] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be used to improve future support activities.

[0219] Data analysis methods using generative AI models

[0220] The server uses the collected data to perform a detailed analysis using a generative AI model (e.g., OpenAI GPT-4) and proposes appropriate improvement measures. The analysis results are notified to the user by the server and used to improve future support activities.

[0221] Specific example

[0222] When a user registers using the app, they enter their name, address, contact information, user ID, and password and submit them. The server stores this information in its database and returns a registration completion message.

[0223] Disaster victims input and submit a list of necessary supplies. The server receives this information and registers it in a database. Relief workers can view the registered list of supplies, register any supplies they can provide, and submit them.

[0224] If a disaster victim wishes to receive mental health support, they enter and submit the desired support content and duration. The server receives this information, matches them with an appropriate support provider, and notifies them. Support is provided via chat or video call through their device at the designated time.

[0225] Example of a prompt

[0226] Based on the following user data, please analyze the effectiveness and challenges of your support activities and propose improvements:

[0227] User ID: user123

[0228] Support details: Psychological support

[0229] Support provider: provider456

[0230] Feedback: Very satisfied

[0231] Support history: ..."

[0232] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0233] Step 1:

[0234] The user uses their device to enter the required information (name, address, contact information, user ID, password) into the registration form and submits it to the server. The server receives this information and stores it in its database. This completes the registration of the new user.

[0235] Input: User information (Name, Address, Contact Information, User ID, Password)

[0236] Output: Registration of user information to the database

[0237] Step 2:

[0238] The user enters their user ID and password into the login form and submits it to the server. The server compares this authentication information with the database, and if they match, authenticates the user. Once authentication is successful, the user can begin using the system.

[0239] Input: Login information (User ID, Password)

[0240] Output: User authentication success / failure

[0241] Step 3:

[0242] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and send it to the server. The server stores this information in a database and updates the list of supplies needed.

[0243] Input: Supply list (category, quantity, priority)

[0244] Output: Registering the list of supplies to the database

[0245] Step 4:

[0246] Supporters use a terminal to view a list of supplies needed for disaster victims, enter information about the supplies they can provide (category, quantity), and send it to the server. The server stores this information in a database and updates the supply distribution status.

[0247] Input: Information on donated goods (category, quantity)

[0248] Output: Registration of provided material information to the database

[0249] Step 5:

[0250] Disaster victims enter information about their mental support needs (support content, preferred time) into a terminal and send it to the server. The server uses this information to match it with a list of support providers in its database and selects an appropriate supporter. Once the selection is complete, the server sends a notification to both the disaster victim and the supporter.

[0251] Input: Mental support request information (support details, preferred time)

[0252] Output: Notification to supporters and disaster victims

[0253] Step 6:

[0254] The server sets up communication links for disaster victims and supporters to chat or video call at designated times. Both parties use their devices to provide mental support.

[0255] Input: Specified time, communication link settings information

[0256] Output: Start a chat or video call

[0257] Step 7:

[0258] The server collects user support activity history and feedback and stores it in a database. This information is used for later analysis.

[0259] Input: Support activity history, feedback

[0260] Output: Recording of history and feedback to the database

[0261] Step 8:

[0262] The server inputs the collected data into a generating AI model (e.g., OpenAI GPT-4) to analyze the effectiveness and challenges of support activities. The AI ​​model processes the data and generates analysis results. Based on these results, the server proposes measures to improve future support activities.

[0263] Input: Collected data (support activity history, feedback, etc.)

[0264] Output: Analysis results and improvement suggestions

[0265] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0266] This invention combines a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies with an emotion engine that recognizes the user's emotions. The system includes user authentication means, supply support list management means, mental support matching means, data analysis means, and an emotion engine.

[0267] User authentication method

[0268] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[0269] Material support list management method

[0270] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0271] Mental support matching method

[0272] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0273] Emotional Engine

[0274] The server uses an emotion engine to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[0275] Data analysis tools

[0276] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by including emotional data from the emotion engine in the analysis, it becomes possible to improve support activities with greater accuracy. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[0277] Specific example

[0278] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[0279] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[0280] If a disaster victim wishes to receive mental support, they use a device to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time by an emotion engine. The results are sent to the server and stored in a database.

[0281] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of an emotion engine improves the quality of support and allows for more effective psychological care of disaster victims.

[0282] The following describes the process flow.

[0283] Detailed processing of user registration and authentication

[0284] Step 1:

[0285] The terminal displays a registration form for the user to enter information such as name, address, contact information, user ID, password, etc.

[0286] Step 2:

[0287] The user enters the necessary items in the registration form and presses the send button.

[0288] Step 3:

[0289] The terminal sends the entered information to the server.

[0290] Step 4:

[0291] The server stores the received user information in the database.

[0292] Step 5:

[0293] The server generates a registration completion message and sends it to the terminal.

[0294] Step 6:

[0295] The terminal displays the registration completion message to the user.

[0296] Detailed processing of material support list management

[0297] Step 1:

[0298] The terminal displays a material support list form for the affected users to enter the category, quantity, priority, etc. of the necessary materials.

[0299] Step 2:

[0300] The disaster-stricken user enters the necessary information into the material support list form and presses the send button.

[0301] Step 3:

[0302] The terminal sends the entered material list information to the server.

[0303] Step 4:

[0304] The server stores the received material list information in the database and updates the support wish list.

[0305] Step 5:

[0306] The terminal displays an interface for the support user to view the support wish list.

[0307] Step 6:

[0308] The support user views the support wish list, selects the category, quantity, etc. of the available materials, and presses the send button.

[0309] Step 7:

[0310] The terminal sends the selected material offer information to the server.

[0311] Step 8:

[0312] The server stores the received material offer information in the database and updates the material offer status.

[0313] Step 9:

[0314] The server notifies the disaster-stricken user of the material offer status.

[0315] Detailed processing of mental support matching and management

[0316] Step 1:

[0317] The device displays a form for disaster victims to input information about their mental health support needs (such as the type of support they require and their preferred time).

[0318] Step 2:

[0319] Disaster victims enter information about their mental health support needs and press the submit button.

[0320] Step 3:

[0321] The terminal sends the entered mental support request information to the server.

[0322] Step 4:

[0323] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[0324] Step 5:

[0325] The server sends notifications to both aid providers and disaster victims.

[0326] Step 6:

[0327] The device receives a notification and displays connection details for the disaster victim and the support provider.

[0328] Step 7:

[0329] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[0330] Detailed processing of the emotion engine

[0331] Step 1:

[0332] While the device is chatting or video-calling with disaster victims and aid providers, the emotion engine analyzes the conversation in real time.

[0333] Step 2:

[0334] The emotion engine analyzes text and audio data to recognize the user's emotional state.

[0335] Step 3:

[0336] The emotion engine sends the recognized emotion data to the server.

[0337] Step 4:

[0338] The server stores emotional data in a database.

[0339] Step 5:

[0340] The emotional engine uses the analysis results to provide feedback to support providers and adjust the support provided.

[0341] Detailed processing of data analysis

[0342] Step 1:

[0343] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[0344] Step 2:

[0345] After the device completes its support activities, it displays a feedback form to the user.

[0346] Step 3:

[0347] The user enters their opinions and feedback into the feedback form and presses the submit button.

[0348] Step 4:

[0349] The terminal sends the input feedback information to the server.

[0350] Step 5:

[0351] The server stores the feedback information it receives in the database.

[0352] Step 6:

[0353] The server uses generated AI to analyze the collected data.

[0354] Step 7:

[0355] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[0356] This allows users to receive disaster relief quickly and effectively, and enables supporters to provide appropriate assistance. Furthermore, the introduction of an emotional engine improves the quality of support and enables better psychological care.

[0357] (Example 2)

[0358] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0359] During disasters, the rapid and effective provision of supplies and mental support are essential, but traditional systems have struggled to deliver these in a timely and appropriate manner. Furthermore, there was a lack of means to provide mental health care to disaster victims, resulting in ineffective support. Moreover, methods for continuously analyzing the effectiveness and challenges of these support activities and for improvement had not been established.

[0360] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0361] In this invention, the server includes user authentication means, material support list management means, mental support matching means, emotion recognition means, and data collection and analysis means. This enables the rapid and effective provision of materials and mental support to disaster victims, as well as the ability to grasp the mental state of disaster victims in real time and improve the quality of support. Furthermore, by analyzing the effectiveness and challenges of support activities in detail, it becomes possible to effectively improve future support activities.

[0362] A "user authentication method" is a means of authenticating a user by receiving authentication information from the user and comparing that information with a database.

[0363] A "supply support list management system" is a means of receiving lists of necessary supplies from disaster-stricken users, storing them in a database, receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[0364] A "mental support matching system" is a means of receiving information on mental support requests from disaster victims, matching it with a list of support providers to select an appropriate supporter, and notifying both parties.

[0365] An "emotion recognition method" is a means of analyzing a user's statements and voice in real time through chat or video calls to recognize the user's emotional state.

[0366] "Data collection and analysis means" refers to a method for collecting users' support activity history and emotional data, storing it in a database, and analyzing that data in detail to evaluate the effectiveness and challenges of support activities and propose improvements for future support activities.

[0367] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system includes user authentication means, supply support list management means, mental support matching means, emotion recognition means, and data collection and analysis means.

[0368] User authentication method

[0369] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by filling out the required information on the registration form using their terminal and submitting it. The server authenticates the user when they fill out the required information on the login form and submit it. Upon successful authentication, the user can use the system.

[0370] Material support list management method

[0371] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[0372] Mental support matching method

[0373] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0374] emotion recognition means

[0375] The server uses emotion recognition technology to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion recognition technology grasps the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[0376] Data acquisition and analysis means

[0377] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be reflected in future support activities. Furthermore, by including emotional data from emotion recognition devices in the analysis, it becomes possible to improve support activities with greater accuracy. The data collection and analysis devices use generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[0378] Specific example

[0379] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[0380] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[0381] If a disaster victim wishes to receive mental support, they use a terminal to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time using emotion recognition technology. The results are sent to the server and stored in a database.

[0382] Example of a prompt

[0383] "Design a system to effectively provide supplies and mental support to disaster victims during emergencies. This system should include user authentication, supply list management, mental support matching, real-time emotion recognition, and data collection and analysis capabilities."

[0384] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of emotion recognition mechanisms improves the quality of support and allows for more effective psychological care of disaster victims.

[0385] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0386] Step 1:

[0387] User Registration

[0388] The system displays a form on the user's device for them to enter necessary information such as their name, address, contact information, user ID, and password. Once the user enters the required information and clicks the "Submit" button, the device sends the entered information to the server. The server stores the received data in its database. The server then sends a registration completion message to the device, which is displayed to the user.

[0389] Input: Name, Address, Contact Information, User ID, Password

[0390] Data processing: The server receives the input information and stores it in the database.

[0391] Output: Registration complete message

[0392] Specific actions:

[0393] The device displays the form

[0394] User enters information

[0395] The server receives the information and stores it in the database.

[0396] Display a registration success message to the user.

[0397] Step 2:

[0398] User Authentication

[0399] The user enters their user ID and password into the login form on their device and clicks the "Login" button. The device sends the entered authentication information to the server. The server compares the received information with its database and performs authentication. If authentication is successful, the server sends an authentication success message to the device and displays it to the user. If authentication fails, an authentication failure message is sent.

[0400] Input: User ID, Password

[0401] Data processing: The server matches the input information against the database.

[0402] Output: Authentication success message or authentication failure message

[0403] Specific actions:

[0404] The user enters their ID and password.

[0405] The server compares with the database.

[0406] Notify the user of the authentication result.

[0407] Step 3:

[0408] Registration and management of the list of material aid.

[0409] The disaster victim enters the category, quantity, and priority of the necessary supplies into the support list form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server registers the received information in its database and updates the list of requested supplies. Supporters check the support list, which is updated in real time, on their devices, select the supplies they can provide, and click the "Submit" button. The device sends the support information to the server, which stores the received information in its database. The server then notifies the disaster victim.

[0410] Input: Information on the supplies needed by disaster victims, and information on the supplies that aid workers can provide.

[0411] Data processing: The server stores the received information in the database and updates the list.

[0412] Output: Support list update notification

[0413] Specific actions:

[0414] Disaster victims enter information about supplies.

[0415] Enter information about the supplies that supporters can provide.

[0416] The server stores each piece of information in a database and updates it in real time.

[0417] The disaster victims will be notified.

[0418] Step 4:

[0419] Mental Support Matching

[0420] The disaster victim enters the support request and desired time into the support form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server receives the support request information, matches it against the provider list, and selects an appropriate supporter. The server then sends notifications to both the supporter and the disaster victim. At the designated time, the disaster victim and supporter begin chatting or video calling through their devices.

[0421] Input: Information on support requests from disaster victims, and information on support provided by aid workers.

[0422] Data processing: The server verifies and matches the information.

[0423] Output: Notification to supporters and disaster victims

[0424] Specific actions:

[0425] Disaster victims enter the type of support they need and their preferred time.

[0426] The server selects supporters and sends notifications.

[0427] Disaster victims and aid workers communicate at the designated time.

[0428] Step 5:

[0429] Emotion recognition by means of emotion recognition

[0430] During mental support sessions, the server monitors chats and video calls and analyzes the user's emotions in real time using emotion recognition technology. This technology performs text and voice analysis to recognize the user's emotional state. The server stores the analysis results in a database and provides feedback to the support provider.

[0431] Input: Text and audio data from chats and video calls

[0432] Data processing: Text and speech analysis using emotion recognition methods.

[0433] Output: Sentiment analysis results, feedback

[0434] Specific actions:

[0435] The server performs sentiment analysis through chat and video calls.

[0436] The emotion analysis results are stored in the database.

[0437] Providing feedback to supporters

[0438] Step 6:

[0439] Data collection and analysis

[0440] The server continuously collects user support activity history and feedback and stores it in a database. Periodically, the server uses generated AI to analyze this data in detail and evaluate the effectiveness and challenges of the support activities. Based on the analysis results, it proposes measures to improve future support activities.

[0441] Input: Support activity history, feedback, emotional data

[0442] Data processing: Data collection and generation by servers, followed by analysis by AI.

[0443] Output: Evaluation report of support activities, improvement suggestions

[0444] Specific actions:

[0445] The server collects support history and sentiment data.

[0446] Stored in the database

[0447] Data analysis using generative AI

[0448] Generate a report proposing improvement measures.

[0449] The above series of processing steps enables rapid and effective support during disasters.

[0450] (Application Example 2)

[0451] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0452] During disasters, it is difficult for victims to receive prompt and appropriate supplies and mental support. Furthermore, there is a lack of means to properly understand the psychological state of victims and enhance the effectiveness of support activities. Therefore, a system is needed that accurately grasps the material needs and mental support needs of victims, monitors their emotional state, and provides appropriate support.

[0453] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0454] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data analysis means, real-time emotion recognition means, and support activity presentation means. This enables user authentication, management of material provision status, mental support matching, data analysis, real-time emotion recognition, and effective presentation of support activities.

[0455] A "user authentication method" is a means of authenticating a user by comparing authentication information sent by the user with a database.

[0456] A "supply support list management system" is a means of receiving lists of necessary supplies sent by disaster victims and storing them in a database, while also receiving information on supplies that can be provided by supporters and managing the status of supply provision.

[0457] A "mental support matching method" is a system that receives information on the mental support needs of disaster victims, matches them with appropriate support providers, and notifies both parties.

[0458] "Data analysis methods" refer to methods for collecting and analyzing users' support activity history and emotional data to evaluate the effectiveness and challenges of support activities and propose improvement measures.

[0459] A "real-time emotion recognition method" is a means of analyzing text and audio during communication between disaster victims and supporters to recognize the emotional state of the user in real time.

[0460] A "support activity presentation method" is a means of proposing and presenting effective support activities to users based on analysis results.

[0461] Modes for carrying out the invention

[0462] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies. This system includes the following means:

[0463] User authentication method:

[0464] The server receives authentication information (user ID, password) sent by the user and authenticates the user by comparing it with the database. This authentication process is performed using Firebase Authentication. Users register by filling out the required information in the registration form using their smartphone and submitting it. Similarly, users authenticate themselves by filling out the required information in the login form and submitting it. Upon successful authentication, the user can begin using the system.

[0465] Specific example:

[0466] When a user registers, they enter their name, address, contact information, user ID, password, etc. into a registration form and submit it. The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[0467] Methods for managing the list of supplies provided:

[0468] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in the Firebase Realtime Database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[0469] Specific example:

[0470] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and submit it. The server registers the received list of supplies in the Firebase Realtime Database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and submit them. The server registers the information about the supplies provided in the database and notifies the disaster victims.

[0471] Mental support matching method:

[0472] The server receives information from disaster victims regarding their requests for mental support (support content, desired time) and uses the Firebase Realtime Database to match it with a list of support providers and select an appropriate supporter. This process utilizes the Twilio API to provide mental support via chat or video call. At the designated time, the disaster victim and support provider use chat or video call via their devices to provide mental support.

[0473] Specific example:

[0474] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental health support via chat or video call.

[0475] Real-time emotion recognition method:

[0476] The server uses IBM Watson to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in the Firebase Realtime Database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[0477] Specific example:

[0478] During mental support, an emotion engine is used to recognize the user's emotions in real time, and the results are sent to a server and stored in a database.

[0479] Data analysis methods:

[0480] The server collects user support activity history and feedback, and analyzes the data using TensorFlow. This allows for evaluation of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by using a generative AI model, emotional data from the emotion engine is also included in the analysis, enabling more accurate improvements to support activities.

[0481] Specific example:

[0482] Based on the collected data, the server analyzes the effectiveness and challenges of support activities and proposes appropriate improvement measures using a generative AI model.

[0483] Example of a prompt:

[0484] 1. "Patient A, please enter the information required for registration. Please enter your name, address, contact information, user ID, and password."

[0485] 2. "Victim B, please list the supplies you need. Please include the category, quantity, and priority."

[0486] 3. "Victim C, please fill in the details of the mental support you require and your preferred time."

[0487] 4. "The emotion engine recognizes your emotional state in real time."

[0488] This system allows disaster victims to quickly receive necessary supplies and mental support, and enables aid providers to deliver assistance smoothly and effectively. Real-time emotion recognition improves the quality of assistance and enables better relief efforts.

[0489] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0490] Step 1:

[0491] User registration process

[0492] Input: The user uses their device to enter their name, address, contact information, user ID, and password into the new registration form and submit it.

[0493] Data processing: The device sends the entered information to the Firebase Authentication server.

[0494] Output: The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[0495] Specific operation: The user enters information into a form, presses the submit button, the server receives the data, saves it to the database, and sends a completion message to the terminal.

[0496] Step 2:

[0497] User authentication process

[0498] Input: The user uses their device to enter their user ID and password into the login form and submit it.

[0499] Data processing: The device sends the transmitted authentication information to the Firebase Authentication server.

[0500] Output: The server verifies the authentication information against the database and, if authentication is successful, logs the user into the system. If authentication fails, it returns an error message.

[0501] Specific operation: The user enters their ID and password into the login form, the server authenticates them, and if successful, logs them into the system.

[0502] Step 3:

[0503] Create a list of supplies to be provided.

[0504] Input: Disaster victims use a terminal to input the necessary supplies (category, quantity, priority) and submit the information.

[0505] Data processing: The terminal sends the entered supply list information to the server.

[0506] Output: The server stores the received supply list information in the Firebase Realtime Database and updates the list of requested assistance.

[0507] Specific operation: Disaster victims enter information about supplies on a terminal, press the send button, and the server stores the information in the database and updates the list.

[0508] Step 4:

[0509] Registration of supporter's material donation information

[0510] Input: Supporters enter the available supplies (category, quantity) on their devices and submit the information.

[0511] Data processing: The terminal sends the entered material provision information to the server.

[0512] Output: The server stores the received information about the provision of supplies in the Firebase Realtime Database and notifies the disaster victims.

[0513] Specific operation: Supporters enter information about supplies on a terminal, press the send button, the server stores the information in the database, and notifies the disaster victims.

[0514] Step 5:

[0515] Submit information requesting mental support

[0516] Input: The disaster victim uses a device to enter the details of the mental support they need and their preferred time, then submits the information.

[0517] Data processing: The terminal sends the entered desired information to the server.

[0518] Output: The server stores the received information in Firebase Realtime Database, selects the appropriate supporter, and notifies both parties.

[0519] Specific operation: The disaster victim enters the type of support needed and their preferred time, presses the submit button, and the server selects an appropriate supporter and sends a notification.

[0520] Step 6:

[0521] Real-time emotion recognition

[0522] Input: Disaster victims and aid workers begin communicating via chat or video call.

[0523] Data processing: The server uses IBM Watson to analyze speech and text and recognize emotional states.

[0524] Output: The server stores the recognized emotion data in the Firebase Realtime Database and returns feedback to the supporter.

[0525] Specific operation: Analyzes voice and text data during communication, recognizes emotional states in real time, and stores them in a database.

[0526] Step 7:

[0527] Data Analysis

[0528] Input: User support activity history and sentiment data.

[0529] Data processing: The server performs data analysis using TensorFlow.

[0530] Output: The server evaluates the effectiveness and challenges of the support activities and proposes improvement measures.

[0531] Specific operation: The server analyzes and evaluates collected historical and sentiment data, and proposes improvement measures using a generative AI model.

[0532] This system enables the rapid and smooth delivery of necessary supplies and mental support to disaster victims, maximizing the effectiveness of relief efforts.

[0533] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0534] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0535] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0536] [Second Embodiment]

[0537] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0538] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0539] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0540] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0541] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0542] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0543] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0544] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0545] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0546] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0547] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0548] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0549] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. This system includes user authentication means, supply support list management means, mental support matching means, and data analysis means.

[0550] User authentication method

[0551] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[0552] Material support list management method

[0553] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0554] Mental support matching method

[0555] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0556] Data analysis tools

[0557] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[0558] Specific example

[0559] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[0560] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[0561] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental health support via chat or video call.

[0562] This system allows users to receive disaster relief quickly and effectively, and enables support providers to deliver appropriate assistance.

[0563] The following describes the processing flow.

[0564] User registration and authentication process

[0565] Step 1:

[0566] The device displays a registration form to the user for entering information such as name, address, contact information, user ID, and password.

[0567] Step 2:

[0568] The user fills in the required information on the registration form and presses the submit button.

[0569] Step 3:

[0570] The terminal sends the entered information to the server.

[0571] Step 4:

[0572] The server stores the received user information in the database.

[0573] Step 5:

[0574] The server generates a registration completion message and sends it to the terminal.

[0575] Step 6:

[0576] The device displays a registration completion message to the user.

[0577] Processing the list of material aid recipients.

[0578] Step 1:

[0579] The device displays a supply support list form to the affected user, allowing them to input the category, quantity, and priority of necessary supplies.

[0580] Step 2:

[0581] Disaster victims fill in the required information on the supplies support list form and press the submit button.

[0582] Step 3:

[0583] The terminal sends the entered supply list information to the server.

[0584] Step 4:

[0585] The server stores the received list of supplies in the database and updates the list of requested assistance.

[0586] Step 5:

[0587] The device displays an interface for the support user to view a list of people who need assistance.

[0588] Step 6:

[0589] Supporting users view the list of requested items, select the categories and quantities of supplies they can provide, and then press the submit button.

[0590] Step 7:

[0591] The terminal sends the selected material provision information to the server.

[0592] Step 8:

[0593] The server stores the received information about the provision of supplies in a database and updates the supply status.

[0594] Step 9:

[0595] The server notifies affected users of the status of supply provision.

[0596] Processing of mental support matching and management

[0597] Step 1:

[0598] The device displays a form for disaster victims to input information about their mental health support needs (such as the type of support they require and their preferred time).

[0599] Step 2:

[0600] Disaster victims enter information about their mental health support needs and press the submit button.

[0601] Step 3:

[0602] The terminal sends the entered mental support request information to the server.

[0603] Step 4:

[0604] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[0605] Step 5:

[0606] The server sends notifications to aid providers and disaster victims.

[0607] Step 6:

[0608] The device receives a notification and displays connection details for the disaster victim and the support provider.

[0609] Step 7:

[0610] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[0611] Data analysis processing

[0612] Step 1:

[0613] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[0614] Step 2:

[0615] After the device completes its support activities, it displays a feedback form to the user.

[0616] Step 3:

[0617] The user enters their opinions and feedback into the feedback form and presses the submit button.

[0618] Step 4:

[0619] The terminal sends the input feedback information to the server.

[0620] Step 5:

[0621] The server stores the feedback information it receives in the database.

[0622] Step 6:

[0623] The server uses generated AI to analyze the collected data.

[0624] Step 7:

[0625] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[0626] In this way, the system of the present invention sequentially carries out processes for effectively providing supplies and mental support in disaster-stricken areas.

[0627] (Example 1)

[0628] Next, we will describe Example 1. 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".

[0629] There is a need for a system that enables the rapid and effective provision of supplies and mental support between disaster victims and aid workers. However, current systems have several problems, including time lags in user authentication, the complexity of managing supply lists, inaccuracies in matching mental support, and the effort required to analyze the effectiveness and challenges of support activities. A system is needed that can solve these problems and provide the support that disaster victims need quickly and effectively.

[0630] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0631] In this invention, the server includes user authentication means, material support list management means, mental support matching means, and data analysis means. This enables the rapid and appropriate provision of support based on support requests from disaster victims, efficient support activities based on the analysis of the user's support activity history and feedback, and effective mental support through appropriate matching of supporters.

[0632] A "user authentication means" is a device or program that has the function of authenticating a user by receiving authentication information from the user and comparing it with a database.

[0633] A "supply support list management system" is a device or program that has the function of receiving a list of necessary supplies from disaster-stricken users, storing it in a database, and receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[0634] A "mental support matching system" is a device or program that receives information requesting mental support from disaster victims, matches it with a list of support providers to select an appropriate supporter, and notifies both parties.

[0635] "Data analysis means" refers to a device or program that has the function of collecting the history and feedback of user support activities, storing it in a database, analyzing it using a generated AI model, and proposing appropriate improvement measures.

[0636] A "server" is a central computer system that receives, processes, stores, and transmits data.

[0637] A "terminal" is a device that a user uses to access a system and send input information.

[0638] A "user" refers to an individual or group of disaster victims or supporters who use this system.

[0639] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system consists of a user authentication means, a supplies support list management means, a mental support matching means, and a data analysis means.

[0640] User authentication method

[0641] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by entering the required information (e.g., name, address, contact information, user ID, password) into a registration form using their device and submitting it. Alternatively, users can authenticate themselves by entering the required information into a login form and submitting it. Upon successful authentication, the user can begin using the system.

[0642] Material support list management method

[0643] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0644] Mental support matching method

[0645] The server receives information from disaster victims regarding their requests for mental support (support content, preferred time), matches it with a list of support providers, and selects appropriate supporters. The server matches the disaster victims' support requests with available support information and notifies both the disaster victims and the supporters. At the designated time, the disaster victims and supporters use chat or video calls via their devices to provide mental support.

[0646] Data analysis tools

[0647] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis tool uses a generative AI model to analyze the collected data in detail and propose appropriate improvement measures.

[0648] Specific example

[0649] 1. When a user registers for a new account

[0650] The user uses their device to enter their name, address, contact information, user ID, password, etc., into the registration form and submits it. The server stores the received information in its database and sends a registration completion message to the user.

[0651] 2. When disaster victims request material assistance

[0652] Disaster victims use a terminal to enter a list of necessary supplies and submit it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and submit them. The server registers the information about the donated supplies in its database and notifies the disaster victims.

[0653] 3. When disaster victims request mental health support

[0654] The disaster victim uses a device to input the type of support they need and their preferred time, then submits the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental support through chat or video call.

[0655] 4. When using generative AI models

[0656] The server collects past support activity data and analyzes it using a generative AI model. Based on the analysis results, it proposes measures to improve support activities and provides feedback to supporters.

[0657] Examples of prompts to input into a generative AI model

[0658] "Please describe the components of a system necessary to provide rapid assistance during a disaster. Also, please include the system's operating procedures and specific usage examples."

[0659] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance.

[0660] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0661] Step 1:

[0662] User Registration

[0663] The user uses their device to enter required information such as name, address, contact information, user ID, and password into the registration form and submits it. The entered data is sent to the server as information for each field.

[0664] The server analyzes the received information and stores it in a database. Then, it generates a registration completion message and sends it to the user via the terminal.

[0665] Input: User information (name, address, contact information, user ID, password)

[0666] Output: Messages confirming registration to the database and user registration.

[0667] Step 2:

[0668] User Login

[0669] The user opens the login form on their device and enters their user ID and password.

[0670] The terminal sends the entered information to the server.

[0671] The server compares the received user ID and password with the authentication information in the database and returns the authentication result to the terminal.

[0672] Authentication successful: Generate and send a message to the user granting permission to access the system.

[0673] Authentication failed: Generate an error message and send it to the user.

[0674] Input: User ID, Password

[0675] Output: Authentication result (success or failure), access permission message or error message.

[0676] Step 3:

[0677] Request for material assistance

[0678] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and submit it.

[0679] The terminal sends the input information to the server.

[0680] The server analyzes the received list of supplies and stores it in a database. It then updates the list of people needing assistance and sends notifications to those affected by the disaster.

[0681] Input: List of required supplies (category, quantity, priority)

[0682] Output: Store the list of needed supplies in the database, update the list of people requesting assistance, and notify disaster victims.

[0683] Step 4:

[0684] Registration of information on the provision of supplies

[0685] Supporters use a terminal to enter information about the supplies they can provide (category, quantity) and submit it.

[0686] The terminal sends the input information to the server.

[0687] The server analyzes the received information about the provision of supplies and stores it in a database. It then sends notifications to the affected people.

[0688] Input: Information on available supplies (category, quantity)

[0689] Output: Storage of information on the provision of supplies in the database, notification to disaster victims.

[0690] Step 5:

[0691] Request for mental support

[0692] Disaster victims use a device to input the type of mental support they want and their preferred time, then submit the information.

[0693] The terminal sends the input information to the server.

[0694] The server stores the received information requesting assistance in a database, compares it with a list of assistance providers to select appropriate helpers, and sends notifications to both the disaster victims and the assistance providers.

[0695] Input: Mental support request information (content, preferred time)

[0696] Output: Store information requesting assistance in the database, compare with the list of assistance providers, notify disaster victims, and notify assistance providers.

[0697] Step 6:

[0698] Providing mental support

[0699] Disaster victims and aid providers will initiate chat or video calls via their devices at a designated time.

[0700] The server monitors the connection initiation and provides assistance as needed.

[0701] Input: Chat or video call connection request

[0702] Output: Start of mental support session, session log data

[0703] Step 7:

[0704] Collection and analysis of support activity data

[0705] The server collects historical data on support activities and user feedback, and stores it in a database.

[0706] The server uses a generative AI model to analyze the data in detail, identify the effectiveness and challenges of support activities, and propose solutions for improvement.

[0707] Input: Support activity history data, feedback data

[0708] Output: Analysis results of effects and challenges, and proposed improvement measures.

[0709] Step 8:

[0710] Provide feedback

[0711] The server generates a feedback report based on the analysis results and improvement suggestions, and provides it to the supporter.

[0712] Supporters will use the feedback report to inform their next support activities.

[0713] Input: Analysis results, improvement suggestions

[0714] Output: Generation and provision of feedback reports

[0715] (Application Example 1)

[0716] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0717] In times of disaster, it is currently difficult for victims to receive necessary material support and mental health support quickly and effectively. Furthermore, there is a lack of systems to accumulate and analyze the effectiveness of these support activities as data and use it to improve future support activities.

[0718] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0719] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data collection means, and data analysis means using a generative AI model. This enables the rapid and effective provision of material support and mental support between disaster victims and supporters, and the improvement of future support activities through data analysis of support activities.

[0720] "User authentication means" refers to a function that verifies the user's identity by comparing authentication information provided by the user with a database.

[0721] A "supply support list management system" is a function that receives lists of necessary supplies from disaster victims, stores them in a database, and manages information on supplies that can be provided by supporters.

[0722] A "mental support matching system" is a function that matches disaster victims with appropriate support providers based on the type of mental support they desire and their preferred time.

[0723] "Data collection means" refers to a function that collects the history and feedback of users' support activities and stores them in a database.

[0724] "Data analysis method using generative AI models" refers to a function that analyzes collected support activity data using generative AI models and proposes appropriate improvement measures.

[0725] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during a disaster, and includes the following means:

[0726] User authentication method

[0727] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. The user registers by entering the required information (name, address, contact information, user ID, password, etc.) into a registration form using their device and submitting it. The server stores the received information in the database and sends a registration completion message to the user. Similarly, when logging in, the user enters the required information into a login form and submits it. The server then authenticates the user, and if authentication is successful, the user can begin using the system.

[0728] Material support list management method

[0729] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0730] Mental support matching method

[0731] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0732] Data acquisition methods

[0733] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be used to improve future support activities.

[0734] Data analysis methods using generative AI models

[0735] The server uses the collected data to perform a detailed analysis using a generative AI model (e.g., OpenAI GPT-4) and proposes appropriate improvement measures. The analysis results are notified to the user by the server and used to improve future support activities.

[0736] Specific example

[0737] When a user registers using the app, they enter their name, address, contact information, user ID, and password and submit them. The server stores this information in its database and returns a registration completion message.

[0738] Disaster victims input and submit a list of necessary supplies. The server receives this information and registers it in a database. Relief workers can view the registered list of supplies, register any supplies they can provide, and submit them.

[0739] If a disaster victim wishes to receive mental health support, they enter and submit the desired support content and duration. The server receives this information, matches them with an appropriate support provider, and notifies them. Support is provided via chat or video call through their device at the designated time.

[0740] Example of a prompt

[0741] Based on the following user data, please analyze the effectiveness and challenges of your support activities and propose improvements:

[0742] User ID: user123

[0743] Support details: Psychological support

[0744] Support provider: provider456

[0745] Feedback: Very satisfied

[0746] Support history: ..."

[0747] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0748] Step 1:

[0749] The user uses their device to enter the required information (name, address, contact information, user ID, password) into the registration form and submits it to the server. The server receives this information and stores it in its database. This completes the registration of the new user.

[0750] Input: User information (Name, Address, Contact Information, User ID, Password)

[0751] Output: Registration of user information to the database

[0752] Step 2:

[0753] The user enters their user ID and password into the login form and submits it to the server. The server compares this authentication information with the database, and if they match, authenticates the user. Once authentication is successful, the user can begin using the system.

[0754] Input: Login information (User ID, Password)

[0755] Output: User authentication success / failure

[0756] Step 3:

[0757] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and send it to the server. The server stores this information in a database and updates the list of supplies needed.

[0758] Input: Supply list (category, quantity, priority)

[0759] Output: Registering the list of supplies to the database

[0760] Step 4:

[0761] Supporters use a terminal to view a list of supplies needed for disaster victims, enter information about the supplies they can provide (category, quantity), and send it to the server. The server stores this information in a database and updates the supply distribution status.

[0762] Input: Information on donated goods (category, quantity)

[0763] Output: Registration of provided material information to the database

[0764] Step 5:

[0765] Disaster victims enter information about their mental support needs (support content, preferred time) into a terminal and send it to the server. The server uses this information to match it with a list of support providers in its database and selects an appropriate supporter. Once the selection is complete, the server sends a notification to both the disaster victim and the supporter.

[0766] Input: Mental support request information (support details, preferred time)

[0767] Output: Notification to supporters and disaster victims

[0768] Step 6:

[0769] The server sets up communication links for disaster victims and supporters to chat or video call at designated times. Both parties use their devices to provide mental support.

[0770] Input: Specified time, communication link settings information

[0771] Output: Start a chat or video call

[0772] Step 7:

[0773] The server collects user support activity history and feedback and stores it in a database. This information is used for later analysis.

[0774] Input: Support activity history, feedback

[0775] Output: Recording of history and feedback to the database

[0776] Step 8:

[0777] The server inputs the collected data into a generating AI model (e.g., OpenAI GPT-4) to analyze the effectiveness and challenges of support activities. The AI ​​model processes the data and generates analysis results. Based on these results, the server proposes measures to improve future support activities.

[0778] Input: Collected data (support activity history, feedback, etc.)

[0779] Output: Analysis results and improvement suggestions

[0780] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0781] This invention combines a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies with an emotion engine that recognizes the user's emotions. The system includes user authentication means, supply support list management means, mental support matching means, data analysis means, and an emotion engine.

[0782] User authentication method

[0783] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[0784] Material support list management method

[0785] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[0786] Mental support matching method

[0787] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0788] Emotional Engine

[0789] The server uses an emotion engine to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[0790] Data analysis tools

[0791] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by including emotional data from the emotion engine in the analysis, it becomes possible to improve support activities with greater accuracy. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[0792] Specific example

[0793] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[0794] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[0795] If a disaster victim wishes to receive mental support, they use a device to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time by an emotion engine. The results are sent to the server and stored in a database.

[0796] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of an emotion engine improves the quality of support and allows for more effective psychological care of disaster victims.

[0797] The following describes the processing flow.

[0798] Detailed processing of user registration and authentication

[0799] Step 1:

[0800] The device displays a registration form to the user for entering information such as name, address, contact information, user ID, and password.

[0801] Step 2:

[0802] The user fills in the required information on the registration form and presses the submit button.

[0803] Step 3:

[0804] The terminal sends the entered information to the server.

[0805] Step 4:

[0806] The server stores the received user information in the database.

[0807] Step 5:

[0808] The server generates a registration completion message and sends it to the terminal.

[0809] Step 6:

[0810] The device displays a registration completion message to the user.

[0811] Detailed processing of the material support list management

[0812] Step 1:

[0813] The device displays a supply support list form to the affected user, allowing them to input the category, quantity, and priority of necessary supplies.

[0814] Step 2:

[0815] Disaster victims fill in the required information on the supplies support list form and press the submit button.

[0816] Step 3:

[0817] The terminal sends the entered supply list information to the server.

[0818] Step 4:

[0819] The server stores the received list of supplies in the database and updates the list of requested assistance.

[0820] Step 5:

[0821] The device displays an interface for the support user to view a list of people who need assistance.

[0822] Step 6:

[0823] Supporting users view the list of requested items, select the categories and quantities of supplies they can provide, and then press the submit button.

[0824] Step 7:

[0825] The terminal sends the selected material provision information to the server.

[0826] Step 8:

[0827] The server stores the received information about the provision of supplies in a database and updates the supply status.

[0828] Step 9:

[0829] The server notifies affected users of the status of supply provision.

[0830] Detailed processing of matching and managing mental support

[0831] Step 1:

[0832] The device displays a form for disaster victims to input information about their mental health support needs (such as the type of support they require and their preferred time).

[0833] Step 2:

[0834] Disaster victims enter information about their mental health support needs and press the submit button.

[0835] Step 3:

[0836] The terminal sends the entered mental support request information to the server.

[0837] Step 4:

[0838] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[0839] Step 5:

[0840] The server sends notifications to aid providers and disaster victims.

[0841] Step 6:

[0842] The device receives a notification and displays connection details for the disaster victim and the support provider.

[0843] Step 7:

[0844] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[0845] Detailed processing of the emotion engine

[0846] Step 1:

[0847] While the device is chatting or video-calling with disaster victims and aid providers, the emotion engine analyzes the conversation in real time.

[0848] Step 2:

[0849] The emotion engine analyzes text and audio data to recognize the user's emotional state.

[0850] Step 3:

[0851] The emotion engine sends the recognized emotion data to the server.

[0852] Step 4:

[0853] The server stores emotional data in a database.

[0854] Step 5:

[0855] The emotional engine uses the analysis results to provide feedback to support providers and adjust the support provided.

[0856] Detailed processing of data analysis

[0857] Step 1:

[0858] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[0859] Step 2:

[0860] After the device completes its support activities, it displays a feedback form to the user.

[0861] Step 3:

[0862] The user enters their opinions and feedback into the feedback form and presses the submit button.

[0863] Step 4:

[0864] The terminal sends the input feedback information to the server.

[0865] Step 5:

[0866] The server stores the feedback information it receives in the database.

[0867] Step 6:

[0868] The server uses generated AI to analyze the collected data.

[0869] Step 7:

[0870] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[0871] This allows users to receive disaster relief quickly and effectively, and enables supporters to provide appropriate assistance. Furthermore, the introduction of an emotional engine improves the quality of support and enables better psychological care.

[0872] (Example 2)

[0873] Next, we will describe Example 2. 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".

[0874] During disasters, the rapid and effective provision of supplies and mental support are essential, but traditional systems have struggled to deliver these in a timely and appropriate manner. Furthermore, there was a lack of means to provide mental health care to disaster victims, resulting in ineffective support. Moreover, methods for continuously analyzing the effectiveness and challenges of these support activities and for improvement had not been established.

[0875] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0876] In this invention, the server includes user authentication means, material support list management means, mental support matching means, emotion recognition means, and data collection and analysis means. This enables the rapid and effective provision of materials and mental support to disaster victims, as well as the ability to grasp the mental state of disaster victims in real time and improve the quality of support. Furthermore, by analyzing the effectiveness and challenges of support activities in detail, it becomes possible to effectively improve future support activities.

[0877] A "user authentication method" is a means of authenticating a user by receiving authentication information from the user and comparing that information with a database.

[0878] A "supply support list management system" is a means of receiving lists of necessary supplies from disaster-stricken users, storing them in a database, receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[0879] A "mental support matching system" is a means of receiving information on mental support requests from disaster victims, matching it with a list of support providers to select an appropriate supporter, and notifying both parties.

[0880] "Emotion recognition means" refers to a method for recognizing a user's emotional state by analyzing their statements and voice in real time through chat or video calls.

[0881] "Data collection and analysis means" refers to a method for collecting users' support activity history and emotional data, storing it in a database, and analyzing that data in detail to evaluate the effectiveness and challenges of support activities and to propose improvements for future support activities.

[0882] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system includes user authentication means, supply support list management means, mental support matching means, emotion recognition means, and data collection and analysis means.

[0883] User authentication method

[0884] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by filling out the required information on the registration form using their terminal and submitting it. The server authenticates the user when they fill out the required information on the login form and submit it. Upon successful authentication, the user can use the system.

[0885] Material support list management method

[0886] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[0887] Mental support matching method

[0888] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[0889] emotion recognition means

[0890] The server uses emotion recognition technology to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion recognition technology grasps the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[0891] Data collection and analysis means

[0892] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be reflected in future support activities. Furthermore, by including emotional data from emotion recognition devices in the analysis, it becomes possible to improve support activities with greater accuracy. The data collection and analysis devices use generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[0893] Specific example

[0894] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[0895] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[0896] If a disaster victim wishes to receive mental support, they use a terminal to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time using emotion recognition technology. The results are sent to the server and stored in a database.

[0897] Example of a prompt

[0898] "Design a system to effectively provide supplies and mental support to disaster victims during emergencies. This system should include user authentication, supply list management, mental support matching, real-time emotion recognition, and data collection and analysis capabilities."

[0899] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of emotion recognition mechanisms improves the quality of support and allows for more effective psychological care of disaster victims.

[0900] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0901] Step 1:

[0902] User Registration

[0903] The system displays a form on the user's device for them to enter necessary information such as their name, address, contact information, user ID, and password. Once the user enters the required information and clicks the "Submit" button, the device sends the entered information to the server. The server stores the received data in its database. The server then sends a registration completion message to the device, which is displayed to the user.

[0904] Input: Name, Address, Contact Information, User ID, Password

[0905] Data processing: The server receives the input information and stores it in the database.

[0906] Output: Registration complete message

[0907] Specific actions:

[0908] The device displays the form

[0909] User enters information

[0910] The server receives the information and stores it in the database.

[0911] Display a registration success message to the user.

[0912] Step 2:

[0913] User Authentication

[0914] The user enters their user ID and password into the login form on their device and clicks the "Login" button. The device sends the entered authentication information to the server. The server compares the received information with its database and performs authentication. If authentication is successful, the server sends an authentication success message to the device and displays it to the user. If authentication fails, an authentication failure message is sent.

[0915] Input: User ID, Password

[0916] Data processing: The server matches the input information against the database.

[0917] Output: Authentication success message or authentication failure message

[0918] Specific actions:

[0919] The user enters their ID and password.

[0920] The server compares with the database.

[0921] Notify the user of the authentication result.

[0922] Step 3:

[0923] Registration and management of the list of material aid.

[0924] The disaster victim enters the category, quantity, and priority of the necessary supplies into the support list form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server registers the received information in its database and updates the list of requested supplies. Supporters check the support list, which is updated in real time, on their devices, select the supplies they can provide, and click the "Submit" button. The device sends the support information to the server, which stores the received information in its database. The server then notifies the disaster victim.

[0925] Input: Information on the supplies needed by disaster victims, and information on the supplies that aid workers can provide.

[0926] Data processing: The server stores the received information in the database and updates the list.

[0927] Output: Support list update notification

[0928] Specific actions:

[0929] Disaster victims enter information about supplies.

[0930] Enter information about the supplies that supporters can provide.

[0931] The server stores each piece of information in a database and updates it in real time.

[0932] The disaster victims will be notified.

[0933] Step 4:

[0934] Mental Support Matching

[0935] The disaster victim enters the support request and desired time into the support form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server receives the support request information, matches it against the provider list, and selects an appropriate supporter. The server then sends notifications to both the supporter and the disaster victim. At the designated time, the disaster victim and supporter begin chatting or video calling through their devices.

[0936] Input: Information on support requests from disaster victims, and information on support provided by aid workers.

[0937] Data processing: The server verifies and matches the information.

[0938] Output: Notification to supporters and disaster victims

[0939] Specific actions:

[0940] Disaster victims enter the type of support they need and their preferred time.

[0941] The server selects supporters and sends notifications.

[0942] Disaster victims and aid workers communicate at the designated time.

[0943] Step 5:

[0944] Emotion recognition by means of emotion recognition

[0945] During mental support sessions, the server monitors chats and video calls and analyzes the user's emotions in real time using emotion recognition technology. This technology performs text and voice analysis to recognize the user's emotional state. The server stores the analysis results in a database and provides feedback to the support provider.

[0946] Input: Text and audio data from chats and video calls

[0947] Data processing: Text and speech analysis using emotion recognition methods.

[0948] Output: Sentiment analysis results, feedback

[0949] Specific actions:

[0950] The server performs sentiment analysis through chat and video calls.

[0951] The emotion analysis results are stored in the database.

[0952] Providing feedback to supporters

[0953] Step 6:

[0954] Data collection and analysis

[0955] The server continuously collects user support activity history and feedback and stores it in a database. Periodically, the server uses generated AI to analyze this data in detail and evaluate the effectiveness and challenges of the support activities. Based on the analysis results, it proposes measures to improve future support activities.

[0956] Input: Support activity history, feedback, emotional data

[0957] Data processing: Data collection and generation by servers, followed by analysis by AI.

[0958] Output: Evaluation report of support activities, improvement suggestions

[0959] Specific actions:

[0960] The server collects support history and sentiment data.

[0961] Stored in the database

[0962] Data analysis using generative AI

[0963] Generate a report proposing improvement measures.

[0964] The above series of processing steps enables rapid and effective support during disasters.

[0965] (Application Example 2)

[0966] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0967] During disasters, it is difficult for victims to receive prompt and appropriate supplies and mental support. Furthermore, there is a lack of means to properly understand the psychological state of victims and enhance the effectiveness of support activities. Therefore, a system is needed that accurately grasps the material needs and mental support needs of victims, monitors their emotional state, and provides appropriate support.

[0968] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0969] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data analysis means, real-time emotion recognition means, and support activity presentation means. This enables user authentication, management of material provision status, mental support matching, data analysis, real-time emotion recognition, and effective presentation of support activities.

[0970] A "user authentication method" is a means of authenticating a user by comparing authentication information sent by the user with a database.

[0971] A "supply support list management system" is a means of receiving lists of necessary supplies sent by disaster victims and storing them in a database, while also receiving information on supplies that can be provided by supporters and managing the status of supply provision.

[0972] A "mental support matching method" is a system that receives information on the mental support needs of disaster victims, matches them with appropriate support providers, and notifies both parties.

[0973] "Data analysis methods" refer to methods for collecting and analyzing users' support activity history and emotional data to evaluate the effectiveness and challenges of support activities and propose improvement measures.

[0974] A "real-time emotion recognition method" is a means of analyzing text and audio during communication between disaster victims and supporters to recognize the emotional state of the user in real time.

[0975] A "support activity presentation method" is a means of proposing and presenting effective support activities to users based on analysis results.

[0976] Modes for carrying out the invention

[0977] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies. This system includes the following means:

[0978] User authentication method:

[0979] The server receives authentication information (user ID, password) sent by the user and authenticates the user by comparing it with the database. This authentication process is performed using Firebase Authentication. Users register by filling out the required information in the registration form using their smartphone and submitting it. Similarly, users authenticate themselves by filling out the required information in the login form and submitting it. Upon successful authentication, the user can begin using the system.

[0980] Specific example:

[0981] When a user registers, they enter their name, address, contact information, user ID, password, etc. into a registration form and submit it. The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[0982] Methods for managing the list of supplies provided:

[0983] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in the Firebase Realtime Database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[0984] Specific example:

[0985] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and submit it. The server registers the received list of supplies in the Firebase Realtime Database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and submit them. The server registers the information about the supplies provided in the database and notifies the disaster victims.

[0986] Mental support matching method:

[0987] The server receives information from disaster victims regarding their requests for mental support (support content, desired time) and uses the Firebase Realtime Database to match it with a list of support providers and select an appropriate supporter. This process utilizes the Twilio API to provide mental support via chat or video call. At the designated time, the disaster victim and support provider use chat or video call via their devices to provide mental support.

[0988] Specific example:

[0989] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental health support via chat or video call.

[0990] Real-time emotion recognition method:

[0991] The server uses IBM Watson to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in the Firebase Realtime Database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[0992] Specific example:

[0993] During mental support, an emotion engine is used to recognize the user's emotions in real time, and the results are sent to a server and stored in a database.

[0994] Data analysis methods:

[0995] The server collects user support activity history and feedback, and analyzes the data using TensorFlow. This allows for evaluation of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by using a generative AI model, emotional data from the emotion engine is also included in the analysis, enabling more accurate improvements to support activities.

[0996] Specific example:

[0997] Based on the collected data, the server analyzes the effectiveness and challenges of support activities and proposes appropriate improvement measures using a generative AI model.

[0998] Example of a prompt:

[0999] 1. "Patient A, please enter the information required for registration. Please enter your name, address, contact information, user ID, and password."

[1000] 2. "Victim B, please list the supplies you need. Please include the category, quantity, and priority."

[1001] 3. "Victim C, please fill in the details of the mental support you require and your preferred time."

[1002] 4. "The emotion engine recognizes your emotional state in real time."

[1003] This system allows disaster victims to quickly receive necessary supplies and mental support, and enables aid providers to deliver assistance smoothly and effectively. Real-time emotion recognition improves the quality of assistance and enables better relief efforts.

[1004] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1005] Step 1:

[1006] User registration process

[1007] Input: The user uses their device to enter their name, address, contact information, user ID, and password into the new registration form and submit it.

[1008] Data processing: The device sends the entered information to the Firebase Authentication server.

[1009] Output: The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[1010] Specific operation: The user enters information into a form, presses the submit button, the server receives the data, saves it to the database, and sends a completion message to the terminal.

[1011] Step 2:

[1012] User authentication process

[1013] Input: The user uses their device to enter their user ID and password into the login form and submit it.

[1014] Data processing: The device sends the transmitted authentication information to the Firebase Authentication server.

[1015] Output: The server verifies the authentication information against the database and, if authentication is successful, logs the user into the system. If authentication fails, it returns an error message.

[1016] Specific operation: The user enters their ID and password into the login form, the server authenticates them, and if successful, logs them into the system.

[1017] Step 3:

[1018] Create a list of supplies to be provided.

[1019] Input: Disaster victims use a terminal to input the necessary supplies (category, quantity, priority) and submit the information.

[1020] Data processing: The terminal sends the entered supply list information to the server.

[1021] Output: The server stores the received supply list information in the Firebase Realtime Database and updates the list of requested assistance.

[1022] Specific operation: Disaster victims enter information about supplies on a terminal, press the send button, and the server stores the information in the database and updates the list.

[1023] Step 4:

[1024] Registration of supporter's material donation information

[1025] Input: Supporters enter the available supplies (category, quantity) on their devices and submit the information.

[1026] Data processing: The terminal sends the entered material provision information to the server.

[1027] Output: The server stores the received information about the provision of supplies in the Firebase Realtime Database and notifies the disaster victims.

[1028] Specific operation: Supporters enter information about supplies on a terminal, press the send button, the server stores the information in the database, and notifies the disaster victims.

[1029] Step 5:

[1030] Submit information requesting mental support

[1031] Input: The disaster victim uses a device to enter the details of the mental support they need and their preferred time, then submits the form.

[1032] Data processing: The terminal sends the entered desired information to the server.

[1033] Output: The server stores the received information in Firebase Realtime Database, selects the appropriate supporter, and notifies both parties.

[1034] Specific operation: The disaster victim enters the type of support needed and their preferred time, presses the submit button, and the server selects an appropriate supporter and sends a notification.

[1035] Step 6:

[1036] Real-time emotion recognition

[1037] Input: Disaster victims and aid workers begin communicating via chat or video call.

[1038] Data processing: The server uses IBM Watson to analyze speech and text and recognize emotional states.

[1039] Output: The server stores the recognized emotion data in the Firebase Realtime Database and returns feedback to the supporter.

[1040] Specific operation: Analyzes voice and text data during communication, recognizes emotional states in real time, and stores them in a database.

[1041] Step 7:

[1042] Data Analysis

[1043] Input: User support activity history and sentiment data.

[1044] Data processing: The server performs data analysis using TensorFlow.

[1045] Output: The server evaluates the effectiveness and challenges of the support activities and proposes improvement measures.

[1046] Specific operation: The server analyzes and evaluates collected historical and sentiment data, and proposes improvement measures using a generative AI model.

[1047] This system enables the rapid and smooth delivery of necessary supplies and mental support to disaster victims, maximizing the effectiveness of relief efforts.

[1048] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1049] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1050] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1051] [Third Embodiment]

[1052] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1053] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1054] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1055] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1056] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1057] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1058] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1059] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1060] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1061] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1062] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1063] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1064] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. This system includes user authentication means, supply support list management means, mental support matching means, and data analysis means.

[1065] User authentication method

[1066] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[1067] Material support list management method

[1068] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1069] Mental support matching method

[1070] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1071] Data analysis tools

[1072] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[1073] Specific example

[1074] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[1075] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[1076] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental health support via chat or video call.

[1077] This system allows users to receive disaster relief quickly and effectively, and enables support providers to deliver appropriate assistance.

[1078] The following describes the processing flow.

[1079] User registration and authentication process

[1080] Step 1:

[1081] The device displays a registration form to the user for entering information such as name, address, contact information, user ID, and password.

[1082] Step 2:

[1083] The user fills in the required information on the registration form and presses the submit button.

[1084] Step 3:

[1085] The terminal sends the entered information to the server.

[1086] Step 4:

[1087] The server stores the received user information in the database.

[1088] Step 5:

[1089] The server generates a registration completion message and sends it to the terminal.

[1090] Step 6:

[1091] The device displays a registration completion message to the user.

[1092] Processing the list of material aid recipients.

[1093] Step 1:

[1094] The device displays a supply support list form to the affected user, allowing them to input the category, quantity, and priority of necessary supplies.

[1095] Step 2:

[1096] Disaster victims fill in the required information on the supplies support list form and press the submit button.

[1097] Step 3:

[1098] The terminal sends the entered supply list information to the server.

[1099] Step 4:

[1100] The server stores the received list of supplies in the database and updates the list of requested assistance.

[1101] Step 5:

[1102] The device displays an interface for the support user to view a list of people who need assistance.

[1103] Step 6:

[1104] Supporting users view the list of requested items, select the categories and quantities of supplies they can provide, and then press the submit button.

[1105] Step 7:

[1106] The terminal sends the selected material provision information to the server.

[1107] Step 8:

[1108] The server stores the received information about the provision of supplies in a database and updates the supply status.

[1109] Step 9:

[1110] The server notifies affected users of the status of supply provision.

[1111] Processing of mental support matching and management

[1112] Step 1:

[1113] The device displays a form for disaster victims to input information about their mental health support needs (such as the type of support they require and their preferred time).

[1114] Step 2:

[1115] Disaster victims enter information about their mental health support needs and press the submit button.

[1116] Step 3:

[1117] The terminal sends the entered mental support request information to the server.

[1118] Step 4:

[1119] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[1120] Step 5:

[1121] The server sends notifications to both aid providers and disaster victims.

[1122] Step 6:

[1123] The device receives a notification and displays connection details for the disaster victim and the support provider.

[1124] Step 7:

[1125] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[1126] Data analysis processing

[1127] Step 1:

[1128] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[1129] Step 2:

[1130] After the device completes its support activities, it displays a feedback form to the user.

[1131] Step 3:

[1132] The user enters their opinions and feedback into the feedback form and presses the submit button.

[1133] Step 4:

[1134] The terminal sends the input feedback information to the server.

[1135] Step 5:

[1136] The server stores the feedback information it receives in the database.

[1137] Step 6:

[1138] The server uses generated AI to analyze the collected data.

[1139] Step 7:

[1140] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[1141] In this way, the system of the present invention sequentially carries out processes for effectively providing supplies and mental support in disaster-stricken areas.

[1142] (Example 1)

[1143] Next, we will describe Example 1. 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."

[1144] There is a need for a system that enables the rapid and effective provision of supplies and mental support between disaster victims and aid workers. However, current systems have several problems, including time lags in user authentication, the complexity of managing supply lists, inaccuracies in matching mental support, and the effort required to analyze the effectiveness and challenges of support activities. A system is needed that can solve these problems and provide the support that disaster victims need quickly and effectively.

[1145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1146] In this invention, the server includes user authentication means, material support list management means, mental support matching means, and data analysis means. This enables the rapid and appropriate provision of support based on support requests from disaster victims, efficient support activities based on the analysis of the user's support activity history and feedback, and effective mental support through appropriate matching of supporters.

[1147] A "user authentication means" is a device or program that has the function of authenticating a user by receiving authentication information from the user and comparing it with a database.

[1148] A "supply support list management system" is a device or program that has the function of receiving a list of necessary supplies from disaster-stricken users, storing it in a database, and receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[1149] A "mental support matching system" is a device or program that receives information requesting mental support from disaster victims, matches it with a list of support providers to select an appropriate supporter, and notifies both parties.

[1150] "Data analysis means" refers to a device or program that has the function of collecting the history and feedback of user support activities, storing it in a database, analyzing it using a generated AI model, and proposing appropriate improvement measures.

[1151] A "server" is a central computer system that receives, processes, stores, and transmits data.

[1152] A "terminal" is a device that a user uses to access a system and send input information.

[1153] A "user" refers to an individual or group of disaster victims or supporters who use this system.

[1154] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system consists of a user authentication means, a supplies support list management means, a mental support matching means, and a data analysis means.

[1155] User authentication method

[1156] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by entering the required information (e.g., name, address, contact information, user ID, password) into a registration form using their device and submitting it. Alternatively, users can authenticate themselves by entering the required information into a login form and submitting it. Upon successful authentication, the user can begin using the system.

[1157] Material support list management method

[1158] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1159] Mental support matching method

[1160] The server receives information from disaster victims regarding their requests for mental support (support content, preferred time), matches it with a list of support providers, and selects appropriate supporters. The server matches the disaster victims' support requests with available support information and notifies both the disaster victims and the supporters. At the designated time, the disaster victims and supporters use chat or video calls via their devices to provide mental support.

[1161] Data analysis tools

[1162] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis tool uses a generative AI model to analyze the collected data in detail and propose appropriate improvement measures.

[1163] Specific example

[1164] 1. When a user registers for a new account

[1165] The user uses their device to enter their name, address, contact information, user ID, password, etc., into the registration form and submits it. The server stores the received information in its database and sends a registration completion message to the user.

[1166] 2. When disaster victims request material assistance

[1167] Disaster victims use a terminal to enter a list of necessary supplies and submit it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and submit them. The server registers the information about the donated supplies in its database and notifies the disaster victims.

[1168] 3. When disaster victims request mental health support

[1169] The disaster victim uses a device to input the type of support they need and their preferred time, then submits the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental support through chat or video call.

[1170] 4. When using generative AI models

[1171] The server collects past support activity data and analyzes it using a generative AI model. Based on the analysis results, it proposes measures to improve support activities and provides feedback to supporters.

[1172] Examples of prompts to input into a generative AI model

[1173] "Please describe the components of a system necessary to provide rapid assistance during a disaster. Also, please include the system's operating procedures and specific usage examples."

[1174] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance.

[1175] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1176] Step 1:

[1177] User Registration

[1178] The user uses their device to enter required information such as name, address, contact information, user ID, and password into the registration form and submits it. The entered data is sent to the server as information for each field.

[1179] The server analyzes the received information and stores it in a database. Then, it generates a registration completion message and sends it to the user via the terminal.

[1180] Input: User information (name, address, contact information, user ID, password)

[1181] Output: Messages confirming registration to the database and user registration.

[1182] Step 2:

[1183] User Login

[1184] The user opens the login form on their device and enters their user ID and password.

[1185] The terminal sends the entered information to the server.

[1186] The server compares the received user ID and password with the authentication information in the database and returns the authentication result to the terminal.

[1187] Authentication successful: Generate and send a message to the user granting permission to access the system.

[1188] Authentication failed: Generate an error message and send it to the user.

[1189] Input: User ID, Password

[1190] Output: Authentication result (success or failure), access permission message or error message.

[1191] Step 3:

[1192] Request for material assistance

[1193] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and submit it.

[1194] The terminal sends the input information to the server.

[1195] The server analyzes the received list of supplies and stores it in a database. It then updates the list of people needing assistance and sends notifications to those affected by the disaster.

[1196] Input: List of required supplies (category, quantity, priority)

[1197] Output: Store the list of needed supplies in the database, update the list of people requesting assistance, and notify disaster victims.

[1198] Step 4:

[1199] Registration of information on the provision of supplies

[1200] Supporters use a terminal to enter information about the supplies they can provide (category, quantity) and submit it.

[1201] The terminal sends the input information to the server.

[1202] The server analyzes the received information about the provision of supplies and stores it in a database. It then sends notifications to the affected people.

[1203] Input: Information on available supplies (category, quantity)

[1204] Output: Storage of information on the provision of supplies in the database, notification to disaster victims.

[1205] Step 5:

[1206] Request for mental support

[1207] Disaster victims use a device to input the type of mental support they want and their preferred time, then submit the information.

[1208] The terminal sends the input information to the server.

[1209] The server stores the received information requesting assistance in a database, compares it with a list of assistance providers to select appropriate helpers, and sends notifications to both the disaster victims and the assistance providers.

[1210] Input: Mental support request information (content, preferred time)

[1211] Output: Store information requesting assistance in the database, compare with the list of assistance providers, notify disaster victims, and notify assistance providers.

[1212] Step 6:

[1213] Providing mental support

[1214] Disaster victims and aid providers will initiate chat or video calls via their devices at a designated time.

[1215] The server monitors the connection initiation and provides assistance as needed.

[1216] Input: Chat or video call connection request

[1217] Output: Start of mental support session, session log data

[1218] Step 7:

[1219] Collection and analysis of support activity data

[1220] The server collects historical data on support activities and user feedback, and stores it in a database.

[1221] The server uses a generative AI model to analyze the data in detail, identify the effectiveness and challenges of support activities, and propose solutions for improvement.

[1222] Input: Support activity history data, feedback data

[1223] Output: Analysis results of effects and challenges, and proposed improvement measures.

[1224] Step 8:

[1225] Provide feedback

[1226] The server generates a feedback report based on the analysis results and improvement suggestions, and provides it to the supporter.

[1227] Supporters will use the feedback report to inform their next support activities.

[1228] Input: Analysis results, improvement suggestions

[1229] Output: Generation and provision of feedback reports

[1230] (Application Example 1)

[1231] Next, we will explain Application Example 1. In the following explanation, 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."

[1232] In times of disaster, it is currently difficult for victims to receive necessary material support and mental health support quickly and effectively. Furthermore, there is a lack of systems to accumulate and analyze the effectiveness of these support activities as data and use it to improve future support activities.

[1233] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1234] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data collection means, and data analysis means using a generative AI model. This enables the rapid and effective provision of material support and mental support between disaster victims and supporters, and the improvement of future support activities through data analysis of support activities.

[1235] "User authentication means" refers to a function that verifies the user's identity by comparing authentication information provided by the user with a database.

[1236] A "supply support list management system" is a function that receives lists of necessary supplies from disaster victims, stores them in a database, and manages information on supplies that can be provided by supporters.

[1237] A "mental support matching system" is a function that matches disaster victims with appropriate support providers based on the type of mental support they desire and their preferred time.

[1238] "Data collection means" refers to a function that collects the history and feedback of users' support activities and stores them in a database.

[1239] "Data analysis method using generative AI models" refers to a function that analyzes collected support activity data using generative AI models and proposes appropriate improvement measures.

[1240] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during a disaster, and includes the following means:

[1241] User authentication method

[1242] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. The user registers by entering the required information (name, address, contact information, user ID, password, etc.) into a registration form using their device and submitting it. The server stores the received information in the database and sends a registration completion message to the user. Similarly, when logging in, the user enters the required information into a login form and submits it. The server then authenticates the user, and if authentication is successful, the user can begin using the system.

[1243] Material support list management method

[1244] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1245] Mental support matching method

[1246] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1247] Data acquisition methods

[1248] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be used to improve future support activities.

[1249] Data analysis methods using generative AI models

[1250] The server uses the collected data to perform a detailed analysis using a generative AI model (e.g., OpenAI GPT-4) and proposes appropriate improvement measures. The analysis results are notified to the user by the server and used to improve future support activities.

[1251] Specific example

[1252] When a user registers using the app, they enter their name, address, contact information, user ID, and password and submit them. The server stores this information in its database and returns a registration completion message.

[1253] Disaster victims input and submit a list of necessary supplies. The server receives this information and registers it in a database. Relief workers can view the registered list of supplies, register any supplies they can provide, and submit them.

[1254] If a disaster victim wishes to receive mental health support, they enter and submit the desired support content and duration. The server receives this information, matches them with an appropriate support provider, and notifies them. Support is provided via chat or video call through their device at the designated time.

[1255] Example of a prompt

[1256] Based on the following user data, please analyze the effectiveness and challenges of your support activities and propose improvements:

[1257] User ID: user123

[1258] Support details: Psychological support

[1259] Support provider: provider456

[1260] Feedback: Very satisfied

[1261] Support history: ..."

[1262] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1263] Step 1:

[1264] The user uses their device to enter the required information (name, address, contact information, user ID, password) into the registration form and submits it to the server. The server receives this information and stores it in its database. This completes the registration of the new user.

[1265] Input: User information (Name, Address, Contact Information, User ID, Password)

[1266] Output: Registration of user information to the database

[1267] Step 2:

[1268] The user enters their user ID and password into the login form and submits it to the server. The server compares this authentication information with the database, and if they match, authenticates the user. Once authentication is successful, the user can begin using the system.

[1269] Input: Login information (User ID, Password)

[1270] Output: User authentication success / failure

[1271] Step 3:

[1272] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and send it to the server. The server stores this information in a database and updates the list of supplies needed.

[1273] Input: Supply list (category, quantity, priority)

[1274] Output: Registering the list of supplies to the database

[1275] Step 4:

[1276] Supporters use a terminal to view a list of supplies needed for disaster victims, enter information about the supplies they can provide (category, quantity), and send it to the server. The server stores this information in a database and updates the supply distribution status.

[1277] Input: Information on donated goods (category, quantity)

[1278] Output: Registration of provided material information to the database

[1279] Step 5:

[1280] Disaster victims enter information about their mental support needs (support content, preferred time) into a terminal and send it to the server. The server uses this information to match it with a list of support providers in its database and selects an appropriate supporter. Once the selection is complete, the server sends a notification to both the disaster victim and the supporter.

[1281] Input: Mental support request information (support details, preferred time)

[1282] Output: Notification to supporters and disaster victims

[1283] Step 6:

[1284] The server sets up communication links for disaster victims and supporters to chat or video call at designated times. Both parties use their devices to provide mental support.

[1285] Input: Specified time, communication link settings information

[1286] Output: Start a chat or video call

[1287] Step 7:

[1288] The server collects user support activity history and feedback and stores it in a database. This information is used for later analysis.

[1289] Input: Support activity history, feedback

[1290] Output: Recording of history and feedback to the database

[1291] Step 8:

[1292] The server inputs the collected data into a generating AI model (e.g., OpenAI GPT-4) to analyze the effectiveness and challenges of support activities. The AI ​​model processes the data and generates analysis results. Based on these results, the server proposes measures to improve future support activities.

[1293] Input: Collected data (support activity history, feedback, etc.)

[1294] Output: Analysis results and improvement suggestions

[1295] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1296] This invention combines a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies with an emotion engine that recognizes the user's emotions. The system includes user authentication means, supply support list management means, mental support matching means, data analysis means, and an emotion engine.

[1297] User authentication method

[1298] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[1299] Material support list management method

[1300] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1301] Mental support matching method

[1302] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1303] Emotional Engine

[1304] The server uses an emotion engine to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[1305] Data analysis tools

[1306] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by including emotional data from the emotion engine in the analysis, it becomes possible to improve support activities with greater accuracy. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[1307] Specific example

[1308] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[1309] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[1310] If a disaster victim wishes to receive mental support, they use a device to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time by an emotion engine. The results are sent to the server and stored in a database.

[1311] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of an emotion engine improves the quality of support and allows for more effective psychological care of disaster victims.

[1312] The following describes the processing flow.

[1313] Detailed processing of user registration and authentication

[1314] Step 1:

[1315] The device displays a registration form to the user for entering information such as name, address, contact information, user ID, and password.

[1316] Step 2:

[1317] The user fills in the required information on the registration form and presses the submit button.

[1318] Step 3:

[1319] The terminal sends the entered information to the server.

[1320] Step 4:

[1321] The server stores the received user information in the database.

[1322] Step 5:

[1323] The server generates a registration completion message and sends it to the terminal.

[1324] Step 6:

[1325] The device displays a registration completion message to the user.

[1326] Detailed processing of the material support list management

[1327] Step 1:

[1328] The device displays a supply support list form to the affected user, allowing them to input the category, quantity, and priority of necessary supplies.

[1329] Step 2:

[1330] Disaster victims fill in the required information on the supplies support list form and press the submit button.

[1331] Step 3:

[1332] The terminal sends the entered supply list information to the server.

[1333] Step 4:

[1334] The server stores the received list of supplies in the database and updates the list of requested assistance.

[1335] Step 5:

[1336] The device displays an interface for the support user to view a list of people who need assistance.

[1337] Step 6:

[1338] Supporting users view the list of requested items, select the categories and quantities of supplies they can provide, and then press the submit button.

[1339] Step 7:

[1340] The terminal sends the selected material provision information to the server.

[1341] Step 8:

[1342] The server stores the received information about the provision of supplies in a database and updates the supply status.

[1343] Step 9:

[1344] The server notifies affected users of the status of supply provision.

[1345] Detailed processing of matching and managing mental support

[1346] Step 1:

[1347] The device displays a form for disaster victims to input information about their mental support needs (such as the type of support they require and their preferred time).

[1348] Step 2:

[1349] Disaster victims enter information about their mental health support needs and press the submit button.

[1350] Step 3:

[1351] The terminal sends the entered mental support request information to the server.

[1352] Step 4:

[1353] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[1354] Step 5:

[1355] The server sends notifications to aid providers and disaster victims.

[1356] Step 6:

[1357] The device receives a notification and displays connection details for the disaster victim and the support provider.

[1358] Step 7:

[1359] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[1360] Detailed processing of the emotion engine

[1361] Step 1:

[1362] While the device is chatting or video-calling with disaster victims and aid providers, the emotion engine analyzes the conversation in real time.

[1363] Step 2:

[1364] The emotion engine analyzes text and audio data to recognize the user's emotional state.

[1365] Step 3:

[1366] The emotion engine sends the recognized emotion data to the server.

[1367] Step 4:

[1368] The server stores emotional data in a database.

[1369] Step 5:

[1370] The emotional engine uses the analysis results to provide feedback to support providers and adjust the support provided.

[1371] Detailed processing of data analysis

[1372] Step 1:

[1373] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[1374] Step 2:

[1375] After the device completes its support activities, it displays a feedback form to the user.

[1376] Step 3:

[1377] The user enters their opinions and feedback into the feedback form and presses the submit button.

[1378] Step 4:

[1379] The terminal sends the input feedback information to the server.

[1380] Step 5:

[1381] The server stores the feedback information it receives in the database.

[1382] Step 6:

[1383] The server uses generated AI to analyze the collected data.

[1384] Step 7:

[1385] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[1386] This allows users to receive disaster relief quickly and effectively, and enables supporters to provide appropriate assistance. Furthermore, the introduction of an emotional engine improves the quality of support and enables better psychological care.

[1387] (Example 2)

[1388] Next, we will describe Example 2. 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."

[1389] During disasters, the rapid and effective provision of supplies and mental support are essential, but traditional systems have struggled to deliver these in a timely and appropriate manner. Furthermore, there was a lack of means to provide mental health care to disaster victims, resulting in ineffective support. Moreover, methods for continuously analyzing the effectiveness and challenges of these support activities and for improvement had not been established.

[1390] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1391] In this invention, the server includes user authentication means, material support list management means, mental support matching means, emotion recognition means, and data collection and analysis means. This enables the rapid and effective provision of materials and mental support to disaster victims, as well as the ability to grasp the mental state of disaster victims in real time and improve the quality of support. Furthermore, by analyzing the effectiveness and challenges of support activities in detail, it becomes possible to effectively improve future support activities.

[1392] A "user authentication method" is a means of authenticating a user by receiving authentication information from the user and comparing that information with a database.

[1393] A "supply support list management system" is a means of receiving lists of necessary supplies from disaster-stricken users, storing them in a database, receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[1394] A "mental support matching system" is a means of receiving information on mental support requests from disaster victims, matching it with a list of support providers to select an appropriate supporter, and notifying both parties.

[1395] "Emotion recognition means" refers to a method for recognizing a user's emotional state by analyzing their statements and voice in real time through chat or video calls.

[1396] "Data collection and analysis means" refers to a method for collecting users' support activity history and emotional data, storing it in a database, and analyzing that data in detail to evaluate the effectiveness and challenges of support activities and to propose improvements for future support activities.

[1397] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system includes user authentication means, supply support list management means, mental support matching means, emotion recognition means, and data collection and analysis means.

[1398] User authentication method

[1399] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by filling out the required information on the registration form using their terminal and submitting it. The server authenticates the user when they fill out the required information on the login form and submit it. Upon successful authentication, the user can use the system.

[1400] Material support list management method

[1401] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[1402] Mental support matching method

[1403] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1404] emotion recognition means

[1405] The server uses emotion recognition technology to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion recognition technology grasps the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[1406] Data collection and analysis means

[1407] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be reflected in future support activities. Furthermore, by including emotional data from emotion recognition devices in the analysis, it becomes possible to improve support activities with greater accuracy. The data collection and analysis devices use generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[1408] Specific example

[1409] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[1410] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[1411] If a disaster victim wishes to receive mental support, they use a terminal to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time using emotion recognition technology. The results are sent to the server and stored in a database.

[1412] Example of a prompt

[1413] "Design a system to effectively provide supplies and mental support to disaster victims during emergencies. This system should include user authentication, supply list management, mental support matching, real-time emotion recognition, and data collection and analysis capabilities."

[1414] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of emotion recognition mechanisms improves the quality of support and allows for more effective psychological care of disaster victims.

[1415] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1416] Step 1:

[1417] User Registration

[1418] The system displays a form on the user's device for them to enter necessary information such as their name, address, contact information, user ID, and password. Once the user enters the required information and clicks the "Submit" button, the device sends the entered information to the server. The server stores the received data in its database. The server then sends a registration completion message to the device, which is displayed to the user.

[1419] Input: Name, Address, Contact Information, User ID, Password

[1420] Data processing: The server receives the input information and stores it in the database.

[1421] Output: Registration complete message

[1422] Specific actions:

[1423] The device displays the form

[1424] User enters information

[1425] The server receives the information and stores it in the database.

[1426] Display a registration success message to the user.

[1427] Step 2:

[1428] User Authentication

[1429] The user enters their user ID and password into the login form on their device and clicks the "Login" button. The device sends the entered authentication information to the server. The server compares the received information with its database and performs authentication. If authentication is successful, the server sends an authentication success message to the device and displays it to the user. If authentication fails, an authentication failure message is sent.

[1430] Input: User ID, Password

[1431] Data processing: The server matches the input information against the database.

[1432] Output: Authentication success message or authentication failure message

[1433] Specific actions:

[1434] The user enters their ID and password.

[1435] The server compares with the database.

[1436] Notify the user of the authentication result.

[1437] Step 3:

[1438] Registration and management of the list of material aid.

[1439] The disaster victim enters the category, quantity, and priority of the necessary supplies into the support list form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server registers the received information in its database and updates the list of requested supplies. Supporters check the support list, which is updated in real time, on their devices, select the supplies they can provide, and click the "Submit" button. The device sends the support information to the server, which stores the received information in its database. The server then notifies the disaster victim.

[1440] Input: Information on the supplies needed by disaster victims, and information on the supplies that aid workers can provide.

[1441] Data processing: The server stores the received information in the database and updates the list.

[1442] Output: Support list update notification

[1443] Specific actions:

[1444] Disaster victims enter information about supplies.

[1445] Enter information about the supplies that supporters can provide.

[1446] The server stores each piece of information in a database and updates it in real time.

[1447] The disaster victims will be notified.

[1448] Step 4:

[1449] Mental Support Matching

[1450] The disaster victim enters the support request and desired time into the support form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server receives the support request information, matches it against the provider list, and selects an appropriate supporter. The server then sends notifications to both the supporter and the disaster victim. At the designated time, the disaster victim and supporter begin chatting or video calling through their devices.

[1451] Input: Information on support requests from disaster victims, and information on support provided by aid workers.

[1452] Data processing: The server verifies and matches the information.

[1453] Output: Notification to supporters and disaster victims

[1454] Specific actions:

[1455] Disaster victims enter the type of support they need and their preferred time.

[1456] The server selects supporters and sends notifications.

[1457] Disaster victims and aid workers communicate at the designated time.

[1458] Step 5:

[1459] Emotion recognition by means of emotion recognition

[1460] During mental support sessions, the server monitors chats and video calls and analyzes the user's emotions in real time using emotion recognition technology. This technology performs text and voice analysis to recognize the user's emotional state. The server stores the analysis results in a database and provides feedback to the support provider.

[1461] Input: Text and audio data from chats and video calls

[1462] Data processing: Text and speech analysis using emotion recognition methods.

[1463] Output: Sentiment analysis results, feedback

[1464] Specific actions:

[1465] The server performs sentiment analysis through chat and video calls.

[1466] The emotion analysis results are stored in the database.

[1467] Providing feedback to supporters

[1468] Step 6:

[1469] Data collection and analysis

[1470] The server continuously collects user support activity history and feedback and stores it in a database. Periodically, the server uses generated AI to analyze this data in detail and evaluate the effectiveness and challenges of the support activities. Based on the analysis results, it proposes measures to improve future support activities.

[1471] Input: Support activity history, feedback, emotional data

[1472] Data processing: Data collection and generation by servers, followed by analysis by AI.

[1473] Output: Evaluation report of support activities, improvement suggestions

[1474] Specific actions:

[1475] The server collects support history and sentiment data.

[1476] Stored in the database

[1477] Data analysis using generative AI

[1478] Generate a report proposing improvement measures.

[1479] The above series of processing steps enables rapid and effective support during disasters.

[1480] (Application Example 2)

[1481] Next, we will explain application example 2. In the following explanation, 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."

[1482] During disasters, it is difficult for victims to receive prompt and appropriate supplies and mental support. Furthermore, there is a lack of means to properly understand the psychological state of victims and enhance the effectiveness of support activities. Therefore, a system is needed that accurately grasps the material needs and mental support needs of victims, monitors their emotional state, and provides appropriate support.

[1483] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1484] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data analysis means, real-time emotion recognition means, and support activity presentation means. This enables user authentication, management of material provision status, mental support matching, data analysis, real-time emotion recognition, and effective presentation of support activities.

[1485] A "user authentication method" is a means of authenticating a user by comparing authentication information sent by the user with a database.

[1486] A "supply support list management system" is a means of receiving lists of necessary supplies sent by disaster victims and storing them in a database, while also receiving information on supplies that can be provided by supporters and managing the status of supply provision.

[1487] A "mental support matching method" is a system that receives information on the mental support needs of disaster victims, matches them with appropriate support providers, and notifies both parties.

[1488] "Data analysis methods" refer to methods for collecting and analyzing users' support activity history and emotional data to evaluate the effectiveness and challenges of support activities and propose improvement measures.

[1489] A "real-time emotion recognition method" is a means of analyzing text and audio during communication between disaster victims and supporters to recognize the emotional state of the user in real time.

[1490] A "support activity presentation method" is a means of proposing and presenting effective support activities to users based on analysis results.

[1491] Modes for carrying out the invention

[1492] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies. This system includes the following means:

[1493] User authentication method:

[1494] The server receives authentication information (user ID, password) sent by the user and authenticates the user by comparing it with the database. This authentication process is performed using Firebase Authentication. Users register by filling out the required information in the registration form using their smartphone and submitting it. Similarly, users authenticate themselves by filling out the required information in the login form and submitting it. Upon successful authentication, the user can begin using the system.

[1495] Specific example:

[1496] When a user registers, they enter their name, address, contact information, user ID, password, etc. into a registration form and submit it. The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[1497] Methods for managing the list of supplies provided:

[1498] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in the Firebase Realtime Database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[1499] Specific example:

[1500] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and submit it. The server registers the received list of supplies in the Firebase Realtime Database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and submit them. The server registers the information about the supplies provided in the database and notifies the disaster victims.

[1501] Mental support matching method:

[1502] The server receives information from disaster victims regarding their requests for mental support (support content, desired time) and uses the Firebase Realtime Database to match it with a list of support providers and select an appropriate supporter. This process utilizes the Twilio API to provide mental support via chat or video call. At the designated time, the disaster victim and support provider use chat or video call via their devices to provide mental support.

[1503] Specific example:

[1504] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental health support via chat or video call.

[1505] Real-time emotion recognition method:

[1506] The server uses IBM Watson to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in the Firebase Realtime Database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[1507] Specific example:

[1508] During mental support, an emotion engine is used to recognize the user's emotions in real time, and the results are sent to a server and stored in a database.

[1509] Data analysis methods:

[1510] The server collects user support activity history and feedback, and analyzes the data using TensorFlow. This allows for evaluation of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by using a generative AI model, emotional data from the emotion engine is also included in the analysis, enabling more accurate improvements to support activities.

[1511] Specific example:

[1512] Based on the collected data, the server analyzes the effectiveness and challenges of support activities and proposes appropriate improvement measures using a generative AI model.

[1513] Example of a prompt:

[1514] 1. "Patient A, please enter the information required for registration. Please enter your name, address, contact information, user ID, and password."

[1515] 2. "Victim B, please list the supplies you need. Please include the category, quantity, and priority."

[1516] 3. "Victim C, please fill in the details of the mental support you require and your preferred time."

[1517] 4. "The emotion engine recognizes your emotional state in real time."

[1518] This system allows disaster victims to quickly receive necessary supplies and mental support, and enables aid providers to deliver assistance smoothly and effectively. Real-time emotion recognition improves the quality of assistance and enables better relief efforts.

[1519] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1520] Step 1:

[1521] User registration process

[1522] Input: The user uses their device to enter their name, address, contact information, user ID, and password into the new registration form and submit it.

[1523] Data processing: The device sends the entered information to the Firebase Authentication server.

[1524] Output: The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[1525] Specific operation: The user enters information into a form, presses the submit button, the server receives the data, saves it to the database, and sends a completion message to the terminal.

[1526] Step 2:

[1527] User authentication process

[1528] Input: The user uses their device to enter their user ID and password into the login form and submit it.

[1529] Data processing: The device sends the transmitted authentication information to the Firebase Authentication server.

[1530] Output: The server verifies the authentication information against the database and, if authentication is successful, logs the user into the system. If authentication fails, it returns an error message.

[1531] Specific operation: The user enters their ID and password into the login form, the server authenticates them, and if successful, logs them into the system.

[1532] Step 3:

[1533] Create a list of supplies to be provided.

[1534] Input: Disaster victims use a terminal to input the necessary supplies (category, quantity, priority) and submit the information.

[1535] Data processing: The terminal sends the entered supply list information to the server.

[1536] Output: The server stores the received supply list information in the Firebase Realtime Database and updates the list of requested assistance.

[1537] Specific operation: Disaster victims enter information about supplies on a terminal, press the send button, and the server stores the information in the database and updates the list.

[1538] Step 4:

[1539] Registration of supporter's material donation information

[1540] Input: Supporters enter the available supplies (category, quantity) on their devices and submit the information.

[1541] Data processing: The terminal sends the entered material provision information to the server.

[1542] Output: The server stores the received information about the provision of supplies in the Firebase Realtime Database and notifies the disaster victims.

[1543] Specific operation: Supporters enter information about supplies on a terminal, press the send button, the server stores the information in the database, and notifies the disaster victims.

[1544] Step 5:

[1545] Submit information requesting mental support

[1546] Input: The disaster victim uses a device to enter the details of the mental support they need and their preferred time, then submits the form.

[1547] Data processing: The terminal sends the entered desired information to the server.

[1548] Output: The server stores the received information in Firebase Realtime Database, selects the appropriate supporter, and notifies both parties.

[1549] Specific operation: The disaster victim enters the type of support needed and their preferred time, presses the submit button, and the server selects an appropriate supporter and sends a notification.

[1550] Step 6:

[1551] Real-time emotion recognition

[1552] Input: Disaster victims and aid workers begin communicating via chat or video call.

[1553] Data processing: The server uses IBM Watson to analyze speech and text and recognize emotional states.

[1554] Output: The server stores the recognized emotion data in the Firebase Realtime Database and returns feedback to the supporter.

[1555] Specific operation: Analyzes voice and text data during communication, recognizes emotional states in real time, and stores them in a database.

[1556] Step 7:

[1557] Data Analysis

[1558] Input: User support activity history and sentiment data.

[1559] Data processing: The server performs data analysis using TensorFlow.

[1560] Output: The server evaluates the effectiveness and challenges of the support activities and proposes improvement measures.

[1561] Specific operation: The server analyzes and evaluates collected historical and sentiment data, and proposes improvement measures using a generative AI model.

[1562] This system enables the rapid and smooth delivery of necessary supplies and mental support to disaster victims, maximizing the effectiveness of relief efforts.

[1563] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1564] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1565] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1566] [Fourth Embodiment]

[1567] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1568] As shown in Figure 7, the 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.

[1569] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1570] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1571] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1572] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1573] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1574] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1575] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1576] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1577] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1578] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1579] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1580] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. This system includes user authentication means, supply support list management means, mental support matching means, and data analysis means.

[1581] User authentication method

[1582] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[1583] Material support list management method

[1584] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1585] Mental support matching method

[1586] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1587] Data analysis tools

[1588] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[1589] Specific example

[1590] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[1591] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[1592] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental health support via chat or video call.

[1593] This system allows users to receive disaster relief quickly and effectively, and enables support providers to deliver appropriate assistance.

[1594] The following describes the processing flow.

[1595] User registration and authentication process

[1596] Step 1:

[1597] The device displays a registration form to the user for entering information such as name, address, contact information, user ID, and password.

[1598] Step 2:

[1599] The user fills in the required information on the registration form and presses the submit button.

[1600] Step 3:

[1601] The terminal sends the entered information to the server.

[1602] Step 4:

[1603] The server stores the received user information in the database.

[1604] Step 5:

[1605] The server generates a registration completion message and sends it to the terminal.

[1606] Step 6:

[1607] The device displays a registration completion message to the user.

[1608] Processing the list of material aid recipients.

[1609] Step 1:

[1610] The device displays a supply support list form to the affected user, allowing them to input the category, quantity, and priority of necessary supplies.

[1611] Step 2:

[1612] Disaster victims fill in the required information on the supplies support list form and press the submit button.

[1613] Step 3:

[1614] The terminal sends the entered supply list information to the server.

[1615] Step 4:

[1616] The server stores the received list of supplies in the database and updates the list of requested assistance.

[1617] Step 5:

[1618] The device displays an interface for the support user to view a list of people who need assistance.

[1619] Step 6:

[1620] Supporting users view the list of requested items, select the categories and quantities of supplies they can provide, and then press the submit button.

[1621] Step 7:

[1622] The terminal sends the selected material provision information to the server.

[1623] Step 8:

[1624] The server stores the received information about the provision of supplies in a database and updates the supply status.

[1625] Step 9:

[1626] The server notifies affected users of the status of supply provision.

[1627] Processing of mental support matching and management

[1628] Step 1:

[1629] The device displays a form for disaster victims to input information about their mental health support needs (such as the type of support they require and their preferred time).

[1630] Step 2:

[1631] Disaster victims enter information about their mental health support needs and press the submit button.

[1632] Step 3:

[1633] The terminal sends the entered mental support request information to the server.

[1634] Step 4:

[1635] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[1636] Step 5:

[1637] The server sends notifications to both aid providers and disaster victims.

[1638] Step 6:

[1639] The device receives a notification and displays connection details for the disaster victim and the support provider.

[1640] Step 7:

[1641] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[1642] Data analysis processing

[1643] Step 1:

[1644] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[1645] Step 2:

[1646] After the device completes its support activities, it displays a feedback form to the user.

[1647] Step 3:

[1648] The user enters their opinions and feedback into the feedback form and presses the submit button.

[1649] Step 4:

[1650] The terminal sends the input feedback information to the server.

[1651] Step 5:

[1652] The server stores the feedback information it receives in the database.

[1653] Step 6:

[1654] The server uses generated AI to analyze the collected data.

[1655] Step 7:

[1656] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[1657] In this way, the system of the present invention sequentially carries out processes for effectively providing supplies and mental support in disaster-stricken areas.

[1658] (Example 1)

[1659] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1660] There is a need for a system that enables the rapid and effective provision of supplies and mental support between disaster victims and aid workers. However, current systems have several problems, including time lags in user authentication, the complexity of managing supply lists, inaccuracies in matching mental support, and the effort required to analyze the effectiveness and challenges of support activities. A system is needed that can solve these problems and provide the support that disaster victims need quickly and effectively.

[1661] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1662] In this invention, the server includes user authentication means, material support list management means, mental support matching means, and data analysis means. This enables the rapid and appropriate provision of support based on support requests from disaster victims, efficient support activities based on the analysis of the user's support activity history and feedback, and effective mental support through appropriate matching of supporters.

[1663] A "user authentication means" is a device or program that has the function of authenticating a user by receiving authentication information from the user and comparing it with a database.

[1664] A "supply support list management system" is a device or program that has the function of receiving a list of necessary supplies from disaster-stricken users, storing it in a database, and receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[1665] A "mental support matching system" is a device or program that receives information requesting mental support from disaster victims, matches it with a list of support providers to select an appropriate supporter, and notifies both parties.

[1666] "Data analysis means" refers to a device or program that has the function of collecting the history and feedback of user support activities, storing them in a database, analyzing them using a generated AI model, and proposing appropriate improvement measures.

[1667] A "server" is a central computer system that receives, processes, stores, and transmits data.

[1668] A "terminal" is a device that a user uses to access a system and send input information.

[1669] A "user" refers to an individual or group of disaster victims or supporters who use this system.

[1670] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system consists of a user authentication means, a supplies support list management means, a mental support matching means, and a data analysis means.

[1671] User authentication method

[1672] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by entering the required information (e.g., name, address, contact information, user ID, password) into a registration form using their device and submitting it. Alternatively, users can authenticate themselves by entering the required information into a login form and submitting it. Upon successful authentication, the user can begin using the system.

[1673] Material support list management method

[1674] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1675] Mental support matching method

[1676] The server receives information from disaster victims regarding their requests for mental support (support content, preferred time), matches it with a list of support providers, and selects appropriate supporters. The server matches the disaster victims' support requests with available support information and notifies both the disaster victims and the supporters. At the designated time, the disaster victims and supporters use chat or video calls via their devices to provide mental support.

[1677] Data analysis tools

[1678] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. The data analysis tool uses a generative AI model to analyze the collected data in detail and propose appropriate improvement measures.

[1679] Specific example

[1680] 1. When a user registers for a new account

[1681] The user uses their device to enter their name, address, contact information, user ID, password, etc., into the registration form and submits it. The server stores the received information in its database and sends a registration completion message to the user.

[1682] 2. When disaster victims request material assistance

[1683] Disaster victims use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[1684] 3. When disaster victims request mental health support

[1685] The disaster victim uses a device to input the type of support they need and their preferred time, then submits the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the disaster victim and the support provider provide mental support through chat or video call.

[1686] 4. When using generative AI models

[1687] The server collects past support activity data and analyzes it using a generative AI model. Based on the analysis results, it proposes measures to improve support activities and provides feedback to supporters.

[1688] Examples of prompts to input into a generative AI model

[1689] "Please describe the components of a system necessary to provide rapid assistance during a disaster. Also, please include the system's operating procedures and specific usage examples."

[1690] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance.

[1691] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1692] Step 1:

[1693] User Registration

[1694] The user uses their device to enter required information such as name, address, contact information, user ID, and password into the registration form and submits it. The entered data is sent to the server as information for each field.

[1695] The server analyzes the received information and stores it in a database. Then, it generates a registration completion message and sends it to the user via the terminal.

[1696] Input: User information (name, address, contact information, user ID, password)

[1697] Output: Messages confirming registration to the database and user registration.

[1698] Step 2:

[1699] User Login

[1700] The user opens the login form on their device and enters their user ID and password.

[1701] The terminal sends the entered information to the server.

[1702] The server compares the received user ID and password with the authentication information in the database and returns the authentication result to the terminal.

[1703] Authentication successful: Generate and send a message to the user granting permission to access the system.

[1704] Authentication failed: Generate an error message and send it to the user.

[1705] Input: User ID, Password

[1706] Output: Authentication result (success or failure), access permission message or error message.

[1707] Step 3:

[1708] Request for material assistance

[1709] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and submit it.

[1710] The terminal sends the input information to the server.

[1711] The server analyzes the received list of supplies and stores it in a database. It then updates the list of people needing assistance and sends notifications to those affected by the disaster.

[1712] Input: List of required supplies (category, quantity, priority)

[1713] Output: Store the list of needed supplies in the database, update the list of people requesting assistance, and notify disaster victims.

[1714] Step 4:

[1715] Registration of information on the provision of supplies

[1716] Supporters use a terminal to enter information about the supplies they can provide (category, quantity) and submit it.

[1717] The terminal sends the input information to the server.

[1718] The server analyzes the received information about the provision of supplies and stores it in a database. It then sends notifications to the affected people.

[1719] Input: Information on available supplies (category, quantity)

[1720] Output: Storage of information on the provision of supplies in the database, notification to disaster victims.

[1721] Step 5:

[1722] Request for mental support

[1723] Disaster victims use a device to input the type of mental support they want and their preferred time, then submit the information.

[1724] The terminal sends the input information to the server.

[1725] The server stores the received information requesting assistance in a database, compares it with a list of assistance providers to select appropriate helpers, and sends notifications to both the disaster victims and the assistance providers.

[1726] Input: Mental support request information (content, preferred time)

[1727] Output: Store information requesting assistance in the database, compare with the list of assistance providers, notify disaster victims, and notify assistance providers.

[1728] Step 6:

[1729] Providing mental support

[1730] Disaster victims and aid providers will initiate chat or video calls via their devices at a designated time.

[1731] The server monitors the connection initiation and provides assistance as needed.

[1732] Input: Chat or video call connection request

[1733] Output: Start of mental support session, session log data

[1734] Step 7:

[1735] Collection and analysis of support activity data

[1736] The server collects historical data on support activities and user feedback, and stores it in a database.

[1737] The server uses a generative AI model to analyze the data in detail, identify the effectiveness and challenges of support activities, and propose solutions for improvement.

[1738] Input: Support activity history data, feedback data

[1739] Output: Analysis results of effects and challenges, and proposed improvement measures.

[1740] Step 8:

[1741] Provide feedback

[1742] The server generates a feedback report based on the analysis results and improvement suggestions, and provides it to the supporter.

[1743] Supporters will use the feedback report to inform their next support activities.

[1744] Input: Analysis results, improvement suggestions

[1745] Output: Generation and provision of feedback reports

[1746] (Application Example 1)

[1747] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1748] In times of disaster, it is currently difficult for victims to receive necessary material support and mental health support quickly and effectively. Furthermore, there is a lack of systems to accumulate and analyze the effectiveness of these support activities as data and use it to improve future support efforts.

[1749] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1750] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data collection means, and data analysis means using a generative AI model. This enables the rapid and effective provision of material support and mental support between disaster victims and supporters, and the improvement of future support activities through data analysis of support activities.

[1751] "User authentication means" refers to a function that verifies the user's identity by comparing authentication information provided by the user with a database.

[1752] A "supply support list management system" is a function that receives lists of necessary supplies from disaster victims, stores them in a database, and manages information on supplies that can be provided by supporters.

[1753] A "mental support matching system" is a function that matches disaster victims with appropriate support providers based on the type of mental support they desire and their preferred time.

[1754] "Data collection means" refers to a function that collects the history and feedback of users' support activities and stores them in a database.

[1755] "Data analysis method using generative AI models" refers to a function that analyzes collected support activity data using generative AI models and proposes appropriate improvement measures.

[1756] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during a disaster, and includes the following means:

[1757] User authentication method

[1758] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. The user registers by entering the required information (name, address, contact information, user ID, password, etc.) into a registration form using their device and submitting it. The server stores the received information in the database and sends a registration completion message to the user. Similarly, when logging in, the user enters the required information into a login form and submits it. The server then authenticates the user, and if authentication is successful, the user can begin using the system.

[1759] Material support list management method

[1760] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1761] Mental support matching method

[1762] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1763] Data acquisition methods

[1764] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be used to improve future support activities.

[1765] Data analysis methods using generative AI models

[1766] The server uses the collected data to perform a detailed analysis using a generative AI model (e.g., OpenAI GPT-4) and proposes appropriate improvement measures. The analysis results are notified to the user by the server and used to improve future support activities.

[1767] Specific example

[1768] When a user registers using the app, they enter their name, address, contact information, user ID, and password and submit them. The server stores this information in its database and returns a registration completion message.

[1769] Disaster victims input and submit a list of necessary supplies. The server receives this information and registers it in a database. Relief workers can view the registered list of supplies, register any supplies they can provide, and submit them.

[1770] If a disaster victim wishes to receive mental health support, they enter and submit the desired support content and duration. The server receives this information, matches them with an appropriate support provider, and notifies them. Support is provided via chat or video call through their device at the designated time.

[1771] Example of a prompt

[1772] Based on the following user data, please analyze the effectiveness and challenges of your support activities and propose improvements:

[1773] User ID: user123

[1774] Support details: Psychological support

[1775] Support provider: provider456

[1776] Feedback: Very satisfied

[1777] Support history: ..."

[1778] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1779] Step 1:

[1780] The user uses their device to enter the required information (name, address, contact information, user ID, password) into the registration form and submits it to the server. The server receives this information and stores it in its database. This completes the registration of the new user.

[1781] Input: User information (Name, Address, Contact Information, User ID, Password)

[1782] Output: Registration of user information to the database

[1783] Step 2:

[1784] The user enters their user ID and password into the login form and submits it to the server. The server compares this authentication information with the database, and if they match, authenticates the user. Once authentication is successful, the user can begin using the system.

[1785] Input: Login information (User ID, Password)

[1786] Output: User authentication success / failure

[1787] Step 3:

[1788] Disaster victims use a terminal to enter a list of necessary supplies (category, quantity, priority) and send it to the server. The server stores this information in a database and updates the list of supplies needed.

[1789] Input: Supplies list (category, quantity, priority)

[1790] Output: Registering the list of supplies to the database

[1791] Step 4:

[1792] Supporters use a terminal to view a list of supplies needed for disaster victims, enter information about the supplies they can provide (category, quantity), and send it to the server. The server stores this information in a database and updates the supply distribution status.

[1793] Input: Information on donated goods (category, quantity)

[1794] Output: Registration of provided supplies information to the database

[1795] Step 5:

[1796] Disaster victims enter information about their mental support needs (support content, preferred time) into a terminal and send it to the server. The server uses this information to compare with a list of support providers in its database and selects an appropriate supporter. Once the selection is complete, the server sends a notification to both the disaster victim and the supporter.

[1797] Input: Mental support request information (support details, preferred time)

[1798] Output: Notification to supporters and disaster victims

[1799] Step 6:

[1800] The server sets up communication links for disaster victims and supporters to chat or video call at designated times. Both parties use their devices to provide mental support.

[1801] Input: Specified time, communication link settings information

[1802] Output: Start a chat or video call

[1803] Step 7:

[1804] The server collects user support activity history and feedback and stores it in a database. This information is used for later analysis.

[1805] Input: Support activity history, feedback

[1806] Output: Recording of history and feedback to the database

[1807] Step 8:

[1808] The server inputs the collected data into a generating AI model (e.g., OpenAI GPT-4) to analyze the effectiveness and challenges of support activities. The AI ​​model processes the data and generates analysis results. Based on these results, the server proposes improvements to future support activities.

[1809] Input: Collected data (support activity history, feedback, etc.)

[1810] Output: Analysis results and improvement suggestions

[1811] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1812] This invention combines a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies with an emotion engine that recognizes the user's emotions. The system includes user authentication means, supply support list management means, mental support matching means, data analysis means, and an emotion engine.

[1813] User authentication method

[1814] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. New registration is performed when the user enters the required information into the registration form on their device and submits it. Similarly, the server authenticates the user when they enter the required information into the login form and submit it. Upon successful authentication, the user can begin using the system.

[1815] Material support list management method

[1816] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time to ensure smooth receipt and delivery of supplies.

[1817] Mental support matching method

[1818] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1819] Emotional Engine

[1820] The server uses an emotion engine to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[1821] Data analysis tools

[1822] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by including emotional data from the emotion engine in the analysis, it becomes possible to improve support activities with greater accuracy. The data analysis method uses generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[1823] Specific example

[1824] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[1825] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[1826] If a disaster victim wishes to receive mental support, they use a device to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time by an emotion engine. The results are sent to the server and stored in a database.

[1827] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of an emotion engine improves the quality of support and allows for more effective psychological care of disaster victims.

[1828] The following describes the processing flow.

[1829] Detailed processing of user registration and authentication

[1830] Step 1:

[1831] The device displays a registration form to the user for entering information such as name, address, contact information, user ID, and password.

[1832] Step 2:

[1833] The user fills in the required information on the registration form and presses the submit button.

[1834] Step 3:

[1835] The terminal sends the entered information to the server.

[1836] Step 4:

[1837] The server stores the received user information in the database.

[1838] Step 5:

[1839] The server generates a registration completion message and sends it to the terminal.

[1840] Step 6:

[1841] The device displays a registration completion message to the user.

[1842] Detailed processing of the material support list management

[1843] Step 1:

[1844] The device displays a supply support list form to the affected user, allowing them to input the category, quantity, and priority of necessary supplies.

[1845] Step 2:

[1846] Disaster victims fill in the required information on the supplies support list form and press the submit button.

[1847] Step 3:

[1848] The terminal sends the entered supply list information to the server.

[1849] Step 4:

[1850] The server stores the received list of supplies in the database and updates the list of requested assistance.

[1851] Step 5:

[1852] The device displays an interface for the support user to view a list of people who need assistance.

[1853] Step 6:

[1854] Supporting users view the list of requested items, select the categories and quantities of supplies they can provide, and then press the submit button.

[1855] Step 7:

[1856] The terminal sends the selected material provision information to the server.

[1857] Step 8:

[1858] The server stores the received information about the provision of supplies in a database and updates the supply status.

[1859] Step 9:

[1860] The server notifies affected users of the status of supply provision.

[1861] Detailed processing of matching and managing mental support

[1862] Step 1:

[1863] The device displays a form for disaster victims to input information about their mental health support needs (such as the type of support they require and their preferred time).

[1864] Step 2:

[1865] Disaster victims enter information about their mental health support needs and press the submit button.

[1866] Step 3:

[1867] The terminal sends the entered mental support request information to the server.

[1868] Step 4:

[1869] The server stores the received mental support request information in a database and compares it with a list of support providers to select an appropriate support provider.

[1870] Step 5:

[1871] The server sends notifications to both aid providers and disaster victims.

[1872] Step 6:

[1873] The device receives a notification and displays connection details for the disaster victim and the support provider.

[1874] Step 7:

[1875] At the designated time, the device will display a chat or video call interface, connecting disaster victims and support providers.

[1876] Detailed processing of the emotion engine

[1877] Step 1:

[1878] While the device is chatting or video-calling with disaster victims and aid providers, the emotion engine analyzes the conversation in real time.

[1879] Step 2:

[1880] The emotion engine analyzes text and audio data to recognize the user's emotional state.

[1881] Step 3:

[1882] The emotion engine sends the recognized emotion data to the server.

[1883] Step 4:

[1884] The server stores emotional data in a database.

[1885] Step 5:

[1886] The emotional engine uses the analysis results to provide feedback to support providers and adjust the support provided.

[1887] Detailed processing of data analysis

[1888] Step 1:

[1889] The server collects chat and video call history, as well as material donation history, and stores it in a database.

[1890] Step 2:

[1891] After the device completes its support activities, it displays a feedback form to the user.

[1892] Step 3:

[1893] The user enters their opinions and feedback into the feedback form and presses the submit button.

[1894] Step 4:

[1895] The terminal sends the input feedback information to the server.

[1896] Step 5:

[1897] The server stores the feedback information it receives in the database.

[1898] Step 6:

[1899] The server uses generated AI to analyze the collected data.

[1900] Step 7:

[1901] Based on the analysis results, the server extracts the effectiveness and challenges of the support activities and incorporates them into future support activities.

[1902] This allows users to receive disaster relief quickly and effectively, and enables supporters to provide appropriate assistance. Furthermore, the introduction of an emotional engine improves the quality of support and enables better psychological care.

[1903] (Example 2)

[1904] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1905] During disasters, the rapid and effective provision of supplies and mental support are essential, but traditional systems have struggled to deliver these in a timely and appropriate manner. Furthermore, there was a lack of means to provide mental health care to disaster victims, resulting in ineffective support. Moreover, methods for continuously analyzing the effectiveness and challenges of these support activities and for improvement had not been established.

[1906] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1907] In this invention, the server includes user authentication means, material support list management means, mental support matching means, emotion recognition means, and data collection and analysis means. This enables the rapid and effective provision of materials and mental support to disaster victims, as well as the ability to grasp the mental state of disaster victims in real time and improve the quality of support. Furthermore, by analyzing the effectiveness and challenges of support activities in detail, it becomes possible to effectively improve future support activities.

[1908] A "user authentication method" is a means of authenticating a user by receiving authentication information from the user and comparing that information with a database.

[1909] A "supply support list management system" is a means of receiving lists of necessary supplies from disaster-stricken users, storing them in a database, receiving information on supplies that can be provided from support users, and managing the status of supply provision.

[1910] A "mental support matching system" is a means of receiving information on mental support requests from disaster victims, matching it with a list of support providers to select an appropriate supporter, and notifying both parties.

[1911] An "emotion recognition method" is a means of analyzing a user's statements and voice in real time through chat or video calls to recognize the user's emotional state.

[1912] "Data collection and analysis means" refers to a method for collecting users' support activity history and emotional data, storing it in a database, and analyzing that data in detail to evaluate the effectiveness and challenges of support activities and propose improvements for future support activities.

[1913] This invention is a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during times of disaster. The system includes user authentication means, supply support list management means, mental support matching means, emotion recognition means, and data collection and analysis means.

[1914] User authentication method

[1915] The server authenticates the user by comparing the authentication information (user ID, password) sent by the user with the database. Users register by filling out the required information on the registration form using their terminal and submitting it. The server authenticates the user when they fill out the required information on the login form and submit it. Upon successful authentication, the user can use the system.

[1916] Material support list management method

[1917] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in a database. This allows for the management of what supplies disaster victims need. It also receives information on supplies available from donors (categories and quantities) and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[1918] Mental support matching method

[1919] The server receives information from disaster victims requesting mental support (support content, preferred time), matches it with a list of support providers, and selects an appropriate supporter. At this time, it matches the requested support information with available support information and notifies both parties. Disaster victims and support providers then use chat or video calls via their devices to provide mental support at the designated time.

[1920] emotion recognition means

[1921] The server uses emotion recognition technology to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion recognition technology grasps the user's emotional state through text and voice analysis and stores it in a database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[1922] Data collection and analysis means

[1923] The server collects user support activity history and feedback and stores it in a database. This allows for analysis of the effectiveness and challenges of support activities, and the results can be reflected in future support activities. Furthermore, by including emotional data from emotion recognition devices in the analysis, it becomes possible to improve support activities with greater accuracy. The data collection and analysis devices use generative AI to analyze the collected data in detail and propose appropriate improvement measures.

[1924] Specific example

[1925] When a user registers, they use their device to enter their name, address, contact information, user ID, password, etc., into a registration form and submit it. The server stores the received information in a database and sends a registration completion message to the user.

[1926] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and send it. The server registers the received list of supplies in its database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and send them. The server registers the information about the supplies provided in its database and notifies the disaster victims.

[1927] If a disaster victim wishes to receive mental support, they use a terminal to input the type of support they need and their preferred time, and then submit the information. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental support via chat or video call, and the user's emotions are analyzed in real time using emotion recognition technology. The results are sent to the server and stored in a database.

[1928] Example of a prompt

[1929] "Design a system to effectively provide supplies and mental support to disaster victims during emergencies. This system should include user authentication, supply list management, mental support matching, real-time emotion recognition, and data collection and analysis capabilities."

[1930] This system allows users to receive disaster relief quickly and effectively, and enables aid providers to deliver appropriate assistance. Furthermore, the introduction of emotion recognition mechanisms improves the quality of support and allows for more effective psychological care of disaster victims.

[1931] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1932] Step 1:

[1933] User Registration

[1934] The system displays a form on the user's device for them to enter necessary information such as their name, address, contact information, user ID, and password. Once the user enters the required information and clicks the "Submit" button, the device sends the entered information to the server. The server stores the received data in its database. The server then sends a registration completion message to the device, which is displayed to the user.

[1935] Input: Name, Address, Contact Information, User ID, Password

[1936] Data processing: The server receives the input information and stores it in the database.

[1937] Output: Registration complete message

[1938] Specific actions:

[1939] The device displays the form

[1940] User enters information

[1941] The server receives the information and stores it in the database.

[1942] Display a registration success message to the user.

[1943] Step 2:

[1944] User Authentication

[1945] The user enters their user ID and password into the login form on their device and clicks the "Login" button. The device sends the entered authentication information to the server. The server compares the received information with its database and performs authentication. If authentication is successful, the server sends an authentication success message to the device and displays it to the user. If authentication fails, an authentication failure message is sent.

[1946] Input: User ID, Password

[1947] Data processing: The server matches the input information against the database.

[1948] Output: Authentication success message or authentication failure message

[1949] Specific actions:

[1950] The user enters their ID and password.

[1951] The server compares with the database.

[1952] Notify the user of the authentication result.

[1953] Step 3:

[1954] Registration and management of the list of material aid.

[1955] The disaster victim enters the category, quantity, and priority of the necessary supplies into the support list form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server registers the received information in its database and updates the list of requested supplies. Supporters check the support list, which is updated in real time, on their devices, select the supplies they can provide, and click the "Submit" button. The device sends the support information to the server, which stores the received information in its database. The server then notifies the disaster victim.

[1956] Input: Information on the supplies needed by disaster victims, and information on the supplies that aid workers can provide.

[1957] Data processing: The server stores the received information in the database and updates the list.

[1958] Output: Support list update notification

[1959] Specific actions:

[1960] Disaster victims enter information about supplies.

[1961] Enter information about the supplies that supporters can provide.

[1962] The server stores each piece of information in a database and updates it in real time.

[1963] The disaster victims will be notified.

[1964] Step 4:

[1965] Mental Support Matching

[1966] The disaster victim enters the support request and desired time into the support form on their device and clicks the "Submit" button. The device sends the entered information to the server. The server receives the support request information, matches it against the provider list, and selects an appropriate supporter. The server then sends notifications to both the supporter and the disaster victim. At the designated time, the disaster victim and supporter begin chatting or video calling through their devices.

[1967] Input: Information on support requests from disaster victims, and information on support provided by aid workers.

[1968] Data processing: The server verifies and matches the information.

[1969] Output: Notification to supporters and disaster victims

[1970] Specific actions:

[1971] Disaster victims enter the type of support they need and their preferred time.

[1972] The server selects supporters and sends notifications.

[1973] Disaster victims and aid workers communicate at the designated time.

[1974] Step 5:

[1975] Emotion recognition by means of emotion recognition

[1976] During mental support sessions, the server monitors chats and video calls and analyzes the user's emotions in real time using emotion recognition technology. This technology performs text and voice analysis to recognize the user's emotional state. The server stores the analysis results in a database and provides feedback to the support provider.

[1977] Input: Text and audio data from chats and video calls

[1978] Data processing: Text and speech analysis using emotion recognition methods.

[1979] Output: Sentiment analysis results, feedback

[1980] Specific actions:

[1981] The server performs sentiment analysis through chat and video calls.

[1982] The emotion analysis results are stored in the database.

[1983] Providing feedback to supporters

[1984] Step 6:

[1985] Data collection and analysis

[1986] The server continuously collects user support activity history and feedback and stores it in a database. Periodically, the server uses generated AI to analyze this data in detail and evaluate the effectiveness and challenges of the support activities. Based on the analysis results, it proposes measures to improve future support activities.

[1987] Input: Support activity history, feedback, emotional data

[1988] Data processing: Data collection and generation by servers, followed by analysis by AI.

[1989] Output: Evaluation report of support activities, improvement suggestions

[1990] Specific actions:

[1991] The server collects support history and sentiment data.

[1992] Stored in the database

[1993] Data analysis using generative AI

[1994] Generate a report proposing improvement measures.

[1995] The above series of processing steps enables rapid and effective support during disasters.

[1996] (Application Example 2)

[1997] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1998] During disasters, it is difficult for victims to receive prompt and appropriate supplies and mental support. Furthermore, there is a lack of means to properly understand the psychological state of victims and enhance the effectiveness of support activities. Therefore, a system is needed that accurately grasps the material needs and mental support needs of victims, monitors their emotional state, and provides appropriate support.

[1999] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[2000] In this invention, the server includes user authentication means, material support list management means, mental support matching means, data analysis means, real-time emotion recognition means, and support activity presentation means. This enables user authentication, management of material provision status, mental support matching, data analysis, real-time emotion recognition, and effective presentation of support activities.

[2001] A "user authentication method" is a means of authenticating a user by comparing authentication information sent by the user with a database.

[2002] A "supply support list management system" is a means of receiving lists of necessary supplies sent by disaster victims and storing them in a database, while also receiving information on supplies that can be provided by supporters and managing the status of supply provision.

[2003] A "mental support matching method" is a system that receives information on the mental support needs of disaster victims, matches them with appropriate support providers, and notifies both parties.

[2004] "Data analysis methods" refer to methods for collecting and analyzing users' support activity history and emotional data to evaluate the effectiveness and challenges of support activities and propose improvement measures.

[2005] A "real-time emotion recognition method" is a means of analyzing text and audio during communication between disaster victims and supporters to recognize the emotional state of the user in real time.

[2006] A "support activity presentation method" is a means of proposing and presenting effective support activities to users based on analysis results.

[2007] Modes for carrying out the invention

[2008] This invention provides a system for facilitating the rapid and effective provision of supplies and mental support between disaster victims and aid workers during emergencies. This system includes the following means:

[2009] User authentication method:

[2010] The server receives authentication information (user ID, password) sent by the user and authenticates the user by comparing it with the database. This authentication process is performed using Firebase Authentication. Users register by filling out the required information in the registration form using their smartphone and submitting it. Similarly, users authenticate themselves by filling out the required information in the login form and submitting it. Upon successful authentication, the user can begin using the system.

[2011] Specific example:

[2012] When a user registers, they enter their name, address, contact information, user ID, password, etc. into a registration form and submit it. The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[2013] Methods for managing the list of supplies provided:

[2014] The server receives lists of supplies sent by disaster victims (categories, quantities, and priorities of needed supplies) and stores them in the Firebase Realtime Database. This allows for the management of what supplies disaster victims need. It also receives information on available supplies (categories and quantities) from donors and stores this information in the database to manage the status of supply distribution. Information on disaster victims and donors is updated in real time, ensuring smooth receipt and delivery of supplies.

[2015] Specific example:

[2016] When disaster victims request material assistance, they use a terminal to enter a list of necessary supplies and submit it. The server registers the received list of supplies in the Firebase Realtime Database and updates the list of requested assistance. Supporters view the list of requested assistance, select the supplies they can provide, and submit them. The server registers the information about the supplies provided in the database and notifies the disaster victims.

[2017] Mental support matching method:

[2018] The server receives information from disaster victims regarding their requests for mental support (support content, desired time) and uses the Firebase Realtime Database to match it with a list of support providers and select an appropriate supporter. This process utilizes the Twilio API to provide mental support via chat or video call. At the designated time, the disaster victim and support provider use chat or video call via their devices to provide mental support.

[2019] Specific example:

[2020] If a disaster victim wishes to receive mental health support, they use a device to input the type of support they need and their preferred time, then submit the request. The server selects an appropriate support provider based on the received information and sends notifications to both parties. At the designated time, the victim and the support provider provide mental health support via chat or video call.

[2021] Real-time emotion recognition method:

[2022] The server uses IBM Watson to recognize emotions in real time during chats and video calls with disaster victims and supporters. This emotion engine understands the user's emotional state through text and voice analysis and stores it in the Firebase Realtime Database. Furthermore, it can provide feedback to mental support providers and appropriately adjust the support provided.

[2023] Specific example:

[2024] During mental support, an emotion engine is used to recognize the user's emotions in real time, and the results are sent to a server and stored in a database.

[2025] Data analysis methods:

[2026] The server collects user support activity history and feedback, and analyzes the data using TensorFlow. This allows for evaluation of the effectiveness and challenges of support activities, and the results are reflected in future support activities. Furthermore, by using a generative AI model, emotional data from the emotion engine is also included in the analysis, enabling more accurate improvements to support activities.

[2027] Specific example:

[2028] Based on the collected data, the server analyzes the effectiveness and challenges of support activities and proposes appropriate improvement measures using a generative AI model.

[2029] Example of a prompt:

[2030] 1. "Patient A, please enter the information required for registration. Please enter your name, address, contact information, user ID, and password."

[2031] 2. "Victim B, please list the supplies you need. Please include the category, quantity, and priority."

[2032] 3. "Victim C, please fill in the details of the mental support you require and your preferred time."

[2033] 4. "The emotion engine recognizes your emotional state in real time."

[2034] This system allows disaster victims to quickly receive necessary supplies and mental support, and enables aid providers to deliver assistance smoothly and effectively. Real-time emotion recognition improves the quality of assistance and enables better relief efforts.

[2035] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2036] Step 1:

[2037] User registration process

[2038] Input: The user uses their device to enter their name, address, contact information, user ID, and password into the new registration form and submit it.

[2039] Data processing: The device sends the entered information to the Firebase Authentication server.

[2040] Output: The server stores the received information in the Firebase Realtime Database and sends a registration completion message to the user.

[2041] Specific operation: The user enters information into a form, presses the submit button, the server receives the data, saves it to the database, and sends a completion message to the terminal.

[2042] Step 2:

[2043] User authentication process

[2044] Input: The user uses their device to enter their user ID and password into the login form and submit it.

[2045] Data processing: The device sends the transmitted authentication information to the Firebase Authentication server.

[2046] Output: The server verifies the authentication information against the database and, if authentication is successful, logs the user into the system. If authentication fails, it returns an error message.

[2047] Specific operation: The user enters their ID and password into the login form, the server authenticates them, and if successful, logs them into the system.

[2048] Step 3:

[2049] Create a list of supplies to be provided.

[2050] Input: Disaster victims use a terminal to input the necessary supplies (category, quantity, priority) and submit the information.

[2051] Data processing: The terminal sends the entered supply list information to the server.

[2052] Output: The server stores the received supply list information in the Firebase Realtime Database and updates the list of requested assistance.

[2053] Specific operation: Disaster victims enter information about supplies on a terminal, press the send button, and the server stores the information in the database and updates the list.

[2054] Step 4:

[2055] Registration of supporter's material donation information

[2056] Input: Supporters enter the available supplies (category, quantity) on their devices and submit the information.

[2057] Data processing: The terminal sends the entered material provision information to the server.

[2058] Output:...

Claims

[Claim 1] A user authentication method that receives authentication information from the user and authenticates the user by comparing it with a database, A supply support list management system that receives a list of necessary supplies from disaster-stricken users, stores it in a database, receives information on supplies that can be provided from support users, and manages the status of supply provision. A mental support matching system that receives information on mental support requests from disaster-stricken users, matches it with a list of support providers, and selects appropriate support providers, A system that includes data analysis tools to collect and analyze the history and feedback of users' support activities, extract the effectiveness and challenges of those activities, and reflect them in future support activities.

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