System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting enrollment information by a user who participates in a volunteer activity; means for using a generative AI model that performs matching using profile information of the user and volunteer demand information; means for providing a generated volunteer recommendation to the user; means for making a reservation for the user to participate in the volunteer activity; means for providing training materials necessary for the volunteer activity; and means for collecting feedback of the volunteer activity and utilizing the feedback for a next recommendation.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The present invention relates to the recruitment and application process for volunteer activities. In particular, conventional volunteer matching systems face problems such as difficulty in appropriately matching user profiles with volunteer demand information, and inefficient sharing of information and provision of training materials necessary for volunteer activities. Another issue is that feedback after volunteer activities is not adequately collected and utilized, making it difficult to encourage future volunteer activities. The present invention aims to solve these problems and realize faster and more efficient volunteer activities. [Means for solving the problem]

[0005] In the present invention, the following measures are taken.

[0006] 1. Provide a means for users participating in volunteer activities to enter their registration information.

[0007] 2. Provide a means to use generative AI models that use user profile information and volunteer demand information to match people.

[0008] 3. Provide a means for providing the generated volunteer recommendations to the user.

[0009] 4. Provide a means for users to make reservations to participate in volunteer activities.

[0010] 5. Have a means to provide training materials necessary for volunteer activities.

[0011] 6. Provide a system that includes a means to collect feedback on volunteer activities and use it to inform future recommendations.

[0012] Furthermore, by providing a means for sending a reminder to users the day before the volunteer activity, the certainty of participation is increased. Furthermore, by providing a means for analyzing user feedback and automatically saving it in a database, more precise matching becomes possible. In this way, the present invention streamlines the entire process from volunteer activity recruitment to application, participation, and feedback, realizing a system that is beneficial to both users and those seeking volunteers.

[0013] "Volunteer activities" refer to support and service activities carried out free of charge for society, communities, or individuals.

[0014] "User" means an individual or organization that uses this system.

[0015] "Registration Information" refers to basic information such as name, email address, password, volunteer experience, areas of interest, available time, and skills that a user enters into the system.

[0016] "Profile information" refers to detailed data about a user's abilities, characteristics, and terms of use.

[0017] "Volunteer demand information" refers to data such as the type of support required and conditions provided by those in need of volunteer activities.

[0018] A "generative AI model" is an algorithm that uses artificial intelligence technology to match users based on their profile information and volunteer demand information.

[0019] "Recommendations" are suggestions for optimal volunteer activities that the system provides to users.

[0020] "Reservation" refers to the process by which a user formally applies to participate in a selected volunteer activity.

[0021] "Training Materials" means documents, videos, and other content that provide the knowledge and procedures necessary to perform volunteer activities.

[0022] "Feedback" refers to information provided by users who participate in volunteer activities by reporting their impressions of the activities and areas for improvement.

[0023] A "reminder" is a message that notifies or reminds a user about a volunteer activity that they have registered or booked. [Brief explanation of the drawings]

[0024] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0025] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0026] First, the terms used in the following description will be explained.

[0027] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0028] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0029] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0030] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0031] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0032] [First embodiment]

[0033] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0034] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0035] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0036] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0037] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0038] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0039] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0040] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0041] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0042] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0043] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0044] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0045] This invention is a system for efficiently recruiting and applying for volunteer activities, and is implemented as follows.

[0046] User registration and profile creation

[0047] User

[0048] Users first access the platform and create a new account.

[0049] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[0050] After logging in, users are directed to a profile page where they can enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[0051] Terminal

[0052] The input information is received and sent to the server.

[0053] server

[0054] The received information is stored in a database.

[0055] Send a confirmation email to confirm registration and prepare to recommend volunteer activities suitable for the user based on their profile information.

[0056] Providing volunteer information and matching

[0057] server

[0058] Get local volunteer demand information from a database or external API.

[0059] The AI ​​model analyzes user profile information and volunteer demand information to generate appropriate recommendations.

[0060] Terminal

[0061] The recommendation list sent from the server is displayed to the user.

[0062] User

[0063] Select the volunteer activity you would like to participate in from the list of recommendations provided.

[0064] Volunteer booking and training

[0065] User

[0066] After selecting your volunteer activity, click the "Participate" button to proceed to the reservation form.

[0067] Enter the required information and confirm your reservation.

[0068] Terminal

[0069] The user's selection information is received and the information required for the reservation form is sent to the server.

[0070] server

[0071] Confirm the booking and save the volunteer activity details in a database.

[0072] A confirmation of the booking will be sent back to the user, along with any training materials or video links required for the relevant volunteer activity.

[0073] Terminal

[0074] Display training materials and links to users.

[0075] User

[0076] Review the training materials provided and acquire the necessary knowledge.

[0077] Volunteer Reminders and Execution

[0078] server

[0079] Send users a reminder the day before their volunteer activity.

[0080] Terminal

[0081] Receive reminder messages and notify users.

[0082] User

[0083] Receive reminders and reconfirm your volunteering dates.

[0084] Sharing and evaluating volunteer experiences

[0085] server

[0086] After the volunteer activity is completed, a feedback form is generated and sent to the user.

[0087] Terminal

[0088] A feedback form is displayed to the user and the entered information is sent to the server.

[0089] User

[0090] Fill out the feedback form and submit it to let us know your experience with the activity and any suggestions for improvement.

[0091] server

[0092] The received feedback is analyzed and stored in a database.

[0093] This will be used to recommend the next volunteer activity, allowing for more precise matching.

[0094] Specific examples

[0095] As a specific example, if user "Ichiro Suzuki" creates an account and enters in his profile that he has emergency medical skills, the server will recommend disaster relief activities taking place this weekend in the surrounding area. Then, it will prioritize activities that "can utilize his emergency medical skills." Ichiro Suzuki selects and reserves the activity, learning the provided training materials. He receives a reminder the day before the activity, and after completing the volunteer activity, he can enter feedback that will be reflected in the next activity.

[0096] The system recommends volunteer activities that best suit the user's needs and skills, making volunteering faster and more efficient.

[0097] The processing flow will be explained below.

[0098] Step 1:

[0099] User

[0100] The user accesses the platform, clicks "New Registration," enters the required information such as name, email address, and password, and presses the "Register" button.

[0101] Step 2:

[0102] Terminal

[0103] The terminal receives the information entered by the user and transmits it to the server.

[0104] Step 3:

[0105] server

[0106] The server stores the received information in a database and sends a confirmation email to the user once the information has been saved.

[0107] Step 4:

[0108] User

[0109] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[0110] Step 5:

[0111] Terminal

[0112] The terminal transmits the profile information entered by the user to the server.

[0113] Step 6:

[0114] server

[0115] The server stores the received profile information in a database.

[0116] Step 7:

[0117] server

[0118] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it uses a generative AI model to analyze the user's profile and volunteer demand information and generate a recommendation list.

[0119] Step 8:

[0120] Terminal

[0121] The terminal displays the recommendation list received from the server to the user.

[0122] Step 9:

[0123] User

[0124] The user selects the volunteer activity they wish to participate in from the displayed list of recommendations.

[0125] Step 10:

[0126] User

[0127] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[0128] Step 11:

[0129] Terminal

[0130] The terminal transmits the reservation information entered by the user to the server.

[0131] Step 12:

[0132] server

[0133] The server receives the reservation information, stores the volunteer activity details in a database, and then sends the user a notification that the reservation is complete, along with any necessary training materials and video links.

[0134] Step 13:

[0135] Terminal

[0136] The terminal displays the provided training materials and links to the user.

[0137] Step 14:

[0138] User

[0139] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[0140] Step 15:

[0141] server

[0142] The day before the volunteer activity, the server sends a reminder to the user.

[0143] Step 16:

[0144] Terminal

[0145] The terminal receives the reminder message and notifies the user.

[0146] Step 17:

[0147] User

[0148] Users receive reminders to reconfirm their volunteering dates.

[0149] Step 18:

[0150] server

[0151] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[0152] Step 19:

[0153] Terminal

[0154] The terminal displays a feedback form to the user and transmits the entered content to the server.

[0155] Step 20:

[0156] User

[0157] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0158] Step 21:

[0159] server

[0160] The server analyzes the received feedback and stores it in a database. Based on the analysis results, the server will use them to recommend the next volunteer activity.

[0161] Through this series of steps, users can efficiently participate in volunteer activities and use the experience gained from the activities for future use.

[0162] Example 1

[0163] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0164] In conventional volunteer recruitment systems, it is difficult for users to find volunteer activities that best suit their skills and interests, and the application process is cumbersome and inefficient. Furthermore, the management of activity bookings, training, reminders, and feedback is not centralized, and an improvement in the user experience is required.

[0165] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0166] In this invention, the server includes means for a user to input registration information, means for inputting basic information and detailed profile information of the user, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for sending a registration completion confirmation email to the user, means for obtaining local volunteer demand information from a database or an external API, means for analyzing the user's profile information and volunteer demand information with an AI model, means for providing the generated volunteer recommendations to the user, means for the user to make a reservation to participate in a volunteer activity, means for sending a reservation completion confirmation email and training materials to the user, and means for collecting feedback on the volunteer activity and using it for next recommendations. This makes it possible to efficiently find volunteer activities that best suit a user's skills and interests, simplify the application process, and centralize management of training, reminders, and feedback.

[0167] "User" refers to an individual or group that registers with the system to participate in volunteer activities and inputs and operates various information.

[0168] "Registration Information" refers to basic personal information such as name, email address, and password that a User enters into the System.

[0169] "Profile Information" refers to detailed information that a User enters into the system, such as volunteer experience, areas of interest, available time, and skills.

[0170] "Server" refers to a computer system that receives, processes, and stores information sent by users in a database.

[0171] "Database" refers to a data storage system for storing user data, including registration information, profile information, volunteer demand information, and feedback information.

[0172] "Generative AI Model" refers to an artificial intelligence model used to analyze a user's profile information and volunteer demand information and generate appropriate recommendations.

[0173] "Recommendations" refers to a list of volunteer activities recommended to a user by a generative AI model.

[0174] "Training Materials" means materials and video links that a User must study before participating in a Volunteer Activity.

[0175] "Feedback" refers to the user's experience with the activity and evaluation of areas for improvement that they enter after completing the volunteer activity.

[0176] "Reminder" refers to a notification message sent to a user immediately before a volunteer activity.

[0177] "External API" refers to an application programming interface used to obtain volunteer demand information from data sources external to the System.

[0178] The present invention is a system for efficiently recruiting and applying for volunteer activities. A specific embodiment of this system will be described below.

[0179] User registration and profile creation

[0180] User

[0181] Users first access the platform using a web browser or mobile application and are redirected to a page to create a new account.

[0182] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[0183] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[0184] Terminal

[0185] The terminal transmits the basic information and profile information entered by the user to the server.

[0186] server

[0187] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[0188] Providing volunteer information and matching

[0189] server

[0190] The server retrieves local volunteer demand information from an internal database or an external API.

[0191] The server analyzes the user's profile information and the acquired volunteer demand information using a generative AI model (e.g., using TensorFlow or PyTorch) to generate a list of recommended appropriate volunteer activities.

[0192] Terminal

[0193] The terminal displays the recommendation list received from the server to the user.

[0194] User

[0195] Users select the volunteer activities they would like to participate in from the recommendation list.

[0196] Volunteer booking and training

[0197] User

[0198] Users select the volunteer activity they wish to participate in and click the "Participate" button. They then fill in the necessary information in the reservation form to confirm their reservation.

[0199] Terminal

[0200] The terminal transmits the user's reservation information to the server.

[0201] server

[0202] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials (e.g., PDFs or video links) required for the volunteer activity.

[0203] Terminal

[0204] The terminal displays training materials and video links to the user.

[0205] User

[0206] The user reviews the provided training materials and acquires the necessary knowledge.

[0207] Volunteer Reminders and Execution

[0208] server

[0209] The server sends a reminder to the user the day before the volunteer activity.

[0210] Terminal

[0211] The terminal receives the reminder message and notifies the user.

[0212] User

[0213] Users receive reminders to reconfirm their volunteering dates.

[0214] Sharing and evaluating volunteer experiences

[0215] server

[0216] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[0217] Terminal

[0218] The terminal displays a feedback form to the user and transmits the entered content to the server.

[0219] User

[0220] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0221] server

[0222] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[0223] Examples of concrete examples and prompts

[0224] As a specific example, consider the case where user "A" has emergency medical skills. The server retrieves local volunteer information from a database or external API, analyzes it using a generative AI model, and recommends the most suitable volunteer activity for "A" (for example, disaster relief activities).

[0225] An example of a prompt is as follows:

[0226] "How do users select a volunteer activity and complete a booking?"

[0227] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0228] Step 1:

[0229] User

[0230] First, users access the platform using a web browser or mobile application, and are redirected to a new account creation page where they enter basic information such as their name, email address, and password, and then click the "Register" button to create an account.

[0231] Input: Name, Email Address, Password

[0232] Output: Registration request

[0233] Specific operation: The browser will redirect to the account creation page and display the input form. When the user presses the "Register" button, the input information will be sent to the server.

[0234] Step 2:

[0235] Terminal

[0236] The terminal sends the basic information entered by the user to the server.

[0237] Input: Basic information entered by the user

[0238] Output: Registration information sent to the server

[0239] Specific operation: The terminal sends an HTTP POST request to the server.

[0240] Step 3:

[0241] server

[0242] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[0243] Input: Registration information sent to the server

[0244] Output: User registration information stored in the database, confirmation email

[0245] Specific operation: The server creates a record in the database and sends a confirmation email using the mail server.

[0246] Step 4:

[0247] User

[0248] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[0249] Input: Login information, profile information

[0250] Output: Detailed profile information

[0251] Specific operation: The browser will redirect to the profile page, and an input form will be displayed. The user will enter their information.

[0252] Step 5:

[0253] Terminal

[0254] The terminal transmits the detailed profile information entered by the user to the server.

[0255] Input: Detailed profile information

[0256] Output: Profile information sent to the server

[0257] Specific operation: The terminal sends an HTTP POST request to the server.

[0258] Step 6:

[0259] server

[0260] The server stores the received profile information in a database and retrieves local volunteer demand information from an internal database or an external API.

[0261] Input: Profile information sent to the server

[0262] Output: Profile information stored in the database, local volunteer demand information

[0263] Specific operation: The server creates a record in the database and sends an API request to retrieve volunteer demand information.

[0264] Step 7:

[0265] server

[0266] The server analyzes the user's profile information and volunteer demand information using a generative AI model to generate appropriate volunteer recommendations.

[0267] Input: User profile information, volunteer demand information

[0268] Output: Volunteer recommendation list

[0269] Specific operations: Run analysis algorithms using generative AI models (such as TensorFlow or PyTorch).

[0270] Step 8:

[0271] Terminal

[0272] The terminal displays the recommendation list received from the server to the user.

[0273] Input: Volunteer Recommendation List

[0274] Output: The recommendation list shown to the user

[0275] Specific operation: The device receives the HTTP response and renders the recommendation list in the browser.

[0276] Step 9:

[0277] User

[0278] Users select the volunteer activity they want to participate in from the recommendation list and click the "Participate" button. Then, they fill in the necessary information in the reservation form to confirm their reservation.

[0279] Input: Recommendation list, reservation information

[0280] Output: Booking request

[0281] Specific operation: A click event transitions to the next form page, and after completing the input, press the "Confirm" button.

[0282] Step 10:

[0283] Terminal

[0284] The terminal transmits the user's reservation information to the server.

[0285] Input: Reservation information

[0286] Output: Reservation information sent to the server

[0287] Specific operation: The terminal sends an HTTP POST request to the server.

[0288] Step 11:

[0289] server

[0290] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials required for the volunteer activity.

[0291] Input: Reservation information

[0292] Output: Booking information stored in a database, confirmation emails, training materials

[0293] What happens: The server saves the reservation information in a database and uses a mail server to send a confirmation email containing the training materials.

[0294] Step 12:

[0295] Terminal

[0296] The terminal displays training materials and video links to the user.

[0297] Input: Training materials

[0298] Output: The training material displayed to the user

[0299] What happens: The browser or app renders the material and displays it to the user.

[0300] Step 13:

[0301] server

[0302] The server sends a reminder to the user the day before the volunteer activity.

[0303] Input: Date information for the relevant volunteer activity

[0304] Output: Reminder message

[0305] Specific operation: The server uses the mail server to send the reminder message.

[0306] Step 14:

[0307] Terminal

[0308] The terminal receives the reminder message and notifies the user.

[0309] Input: Reminder message

[0310] Output: Reminders notified to the user

[0311] Specific behavior: The device displays a notification and alerts the user.

[0312] Step 15:

[0313] server

[0314] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[0315] Input: Volunteer activity completion information

[0316] Output: Feedback form submission

[0317] Specific operation: The server sends the feedback form using the mail server.

[0318] Step 16:

[0319] Terminal

[0320] The terminal displays a feedback form to the user and transmits the entered content to the server.

[0321] Input: Feedback Form

[0322] Output: The input feedback

[0323] What happens: The browser or app displays a feedback form, which the user fills out and then submits to the server.

[0324] Step 17:

[0325] server

[0326] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[0327] Input: Feedback

[0328] Output: Parsed feedback data, feedback information stored in a database

[0329] What happens: The analysis algorithm processes the feedback and creates a record in the database.

[0330] (Application example 1)

[0331] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0332] Conventional volunteer participation systems often make it difficult for users to find activities that match their skills and interests, resulting in inappropriate matching. Additionally, users are often unable to fully prepare for volunteer activities due to insufficient training materials and videos. Furthermore, because feedback is collected and analyzed manually, it is difficult to effectively reflect this feedback in future recommendations.

[0333] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0334] In this invention, the server includes a means for a user to input registration information, a means for using a generative AI model that performs matching using the user's profile information and volunteer demand information, a means for providing the generated volunteer recommendations to the user, a means for the user to make a reservation to participate in a volunteer activity, a means further including a means for providing training materials and videos necessary for the volunteer activity, a means for collecting feedback on the volunteer activity and using it for the next recommendation, a means for viewing the training video using a head-mounted display, and a means for sending a reminder to the user the day before the volunteer activity. This allows users to easily find the most suitable volunteer activity based on their skills and interests, allowing them to participate in the activity with sufficient preparation, and allows feedback to be effectively collected and analyzed to be reflected in the next recommendation.

[0335] "User" refers to an individual who registers with the System and provides profile information to participate in volunteer activities.

[0336] "Means for entering registration information" refers to the interface through which a user accesses the system and enters basic information such as name, email address, and password.

[0337] "Profile information" refers to information that indicates the user's characteristics and background, such as the user's volunteer experience, areas of interest, available time, and skills.

[0338] "Volunteer demand information" refers to information about the types and content of volunteers needed in specific regions or organizations.

[0339] A "generative AI model" refers to an artificial intelligence model that analyzes a user's profile information and volunteer demand information to recommend the most suitable volunteer activities for the user.

[0340] "Recommendations" refers to potential volunteer activities suggested to users by the generative AI model.

[0341] "Means for making reservations" refers to an interface that allows a user to reserve a date, time, and location for a selected volunteer activity.

[0342] "Training materials and videos" refers to written and visual content that helps users learn the knowledge and skills necessary to participate in volunteer activities.

[0343] "Head-mounted display" refers to a display device used by a user to view training videos with a 360-degree field of view.

[0344] "Reminder" refers to a notification message sent to a user the day before a volunteer activity.

[0345] "Feedback" refers to the user's experience with the activity and their opinions on areas for improvement provided after completing the volunteer activity.

[0346] In the present invention, the following means and processes are used to provide a system that allows users to efficiently participate in volunteer activities.

[0347] 1. User registration and profile creation

[0348] A user accesses the system and creates a new account. The user enters basic information such as name, email address, and password, and presses the "Register" button, which sends the information to the server.

[0349] The server receives this and stores it in a database. After the user logs in, they go to their profile page and enter detailed profile information such as their volunteer experience, areas of interest, available time, skills, etc. This is also sent to the server and stored in the database.

[0350] 2. Providing volunteer information and matching

[0351] The server retrieves local volunteer demand information from a database or external API. Using a generative AI model, it analyzes the user's profile information and volunteer demand information to generate appropriate recommendations. These are sent to the user's device and displayed as a recommendation list.

[0352] Specifically, the following prompt sentences are input into the generative AI model, which then recommends the most suitable volunteer activity for the user:

[0353] User Profile:

[0354] Name: Ichiro Suzuki

[0355] Volunteer experience: Emergency medical technician

[0356] Area of ​​interest: Disaster relief

[0357] Available times: Weekends

[0358] Volunteer activities offered:

[0359] 1. Disaster support activities A

[0360] 2. Disaster relief activities B

[0361] 3. Community cleanup activities

[0362] Please choose one activity to recommend.

[0363] 3. Volunteer booking and training

[0364] The user selects the volunteer activity they wish to participate in from the recommended list. After making their selection, they click the "Participate" button and proceed to the reservation form. They then enter the required information and confirm their reservation.

[0365] The server receives the request, confirms the reservation, stores the volunteer activity details in a database, and returns a confirmation of the reservation to the user along with relevant training materials and video links that can be viewed on the user's smartphone or head-mounted display.

[0366] 4. Volunteer Reminders and Execution

[0367] The server sends a reminder to the user the day before the volunteer activity.

[0368] The terminal receives the reminder message and notifies the user.

[0369] The user checks this and reconfirms the schedule for volunteer activities.

[0370] 5. Sharing and evaluating volunteer experiences

[0371] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[0372] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0373] The server receives this, stores it in a database, and uses it to recommend volunteer activities for the next time.

[0374] The system configuration utilizes the following hardware and software:

[0375] Smartphone: iOS or Android compatible.

[0376] Head-mounted display: VR compatible display.

[0377] Server side: Uses AWS (Amazon Web Services).

[0378] AI model: Use Amazon SageMaker, etc.

[0379] Database: MySQL or PostgreSQL.

[0380] This allows users to easily find the best volunteer activities based on their skills and interests, allows them to participate in activities well prepared, and effectively collect and analyze feedback to reflect in future recommendations.

[0381] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0382] Step 1:

[0383] The user enters registration information

[0384] input:

[0385] The user enters basic information such as name, email address, and password.

[0386] Data processing / calculation:

[0387] The terminal organizes the input information and sends it to the server.

[0388] output:

[0389] The server sends a confirmation email to the user and stores the information in a database.

[0390] Step 2:

[0391] User enters profile information

[0392] input:

[0393] Users enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[0394] Data processing / calculation:

[0395] The terminal organizes the entered information and sends it to the server.

[0396] output:

[0397] The server saves the profile information to a database and notifies the user that the information has been saved.

[0398] Step 3:

[0399] Acquisition and analysis of volunteer demand information

[0400] input:

[0401] The server retrieves local volunteer demand information from a database or external API.

[0402] Data processing / calculation:

[0403] The server analyzes the acquired volunteer demand information and user profile information, and generates appropriate recommendations using a generative AI model.

[0404] output:

[0405] Send the recommendation list to the user.

[0406] Step 4:

[0407] User selects volunteer activity and makes reservation

[0408] input:

[0409] The user selects the volunteer activity they want to participate in from the recommended list and clicks "Participate." They then enter the required information and confirm their reservation.

[0410] Data processing / calculation:

[0411] The terminal transmits the input information to the server.

[0412] output:

[0413] The server stores the reservation information in a database and sends the user details, training materials and video links.

[0414] Step 5:

[0415] Watch training videos required for volunteer work

[0416] input:

[0417] The user receives the training materials and video links sent to them and begins watching them.

[0418] Data processing / calculation:

[0419] The device plays the video link on the head-mounted display or smartphone.

[0420] output:

[0421] Users watch training videos and acquire the necessary knowledge.

[0422] Step 6:

[0423] Volunteer Reminders

[0424] input:

[0425] The server sets a reminder the day before the volunteer activity.

[0426] Data processing / calculation:

[0427] The server generates a reminder message and sends it to the terminal.

[0428] output:

[0429] The terminal notifies the user of the reminder message.

[0430] Step 7:

[0431] Collecting feedback after volunteering

[0432] input:

[0433] After completing the activity, users enter their experience and suggestions for improvement in a feedback form submitted.

[0434] Data processing / calculation:

[0435] The device sends feedback information to the server, which analyzes it and stores it in a database.

[0436] output:

[0437] The server will incorporate the feedback into its next recommendations.

[0438] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0439] This invention is a system for efficiently recruiting and applying for volunteer activities, and in particular, it combines a function for recognizing a user's emotions and selecting activities. It is implemented through the following specific process.

[0440] User registration and profile creation

[0441] User

[0442] First, users access the platform and click "Sign Up." They then enter the required information, such as their name, email address, and password, and press the "Register" button to create an account.

[0443] Terminal

[0444] The terminal receives the information entered by the user and transmits it to the server.

[0445] server

[0446] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[0447] User

[0448] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[0449] Terminal

[0450] The terminal transmits the profile information entered by the user to the server.

[0451] server

[0452] The server stores the received profile information in a database and uses an emotion engine to analyze the emotions expressed by the user when they input their information. Based on the analysis results, the server prepares to generate a more accurate recommendation list.

[0453] Providing volunteer information and matching

[0454] server

[0455] The server retrieves local volunteer demand information from a database or external API, and analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model, thereby generating appropriate recommendations based on the user's emotional state.

[0456] Terminal

[0457] The terminal displays the recommendation list sent from the server to the user.

[0458] User

[0459] The user selects the most suitable volunteer activity based on their emotional state from the presented recommendation list.

[0460] Volunteer booking and training

[0461] User

[0462] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[0463] Terminal

[0464] The terminal transmits the reservation information entered by the user to the server.

[0465] server

[0466] The server receives the reservation information, stores the volunteer activity details in a database, and then sends a notification to the user that the reservation is complete, along with any necessary training materials and video links.

[0467] Terminal

[0468] The terminal displays the provided training materials and links to the user.

[0469] User

[0470] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[0471] Volunteer Reminders and Execution

[0472] server

[0473] The day before the volunteer activity, the server sends a reminder to the user.

[0474] Terminal

[0475] The terminal receives the reminder message and notifies the user.

[0476] User

[0477] Users receive reminders to reconfirm their volunteering dates.

[0478] Sharing and evaluating volunteer experiences

[0479] server

[0480] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[0481] Terminal

[0482] The terminal displays a feedback form to the user and transmits the entered content to the server.

[0483] User

[0484] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0485] server

[0486] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The results of this analysis are stored in a database and reflected in the next volunteer activity recommendation.

[0487] Specific examples

[0488] As a concrete example, suppose a user creates an account and participates in disaster relief activities last week. The user reviews the training materials, receives reminders, and participates in the activities. After completing the activities, the user enters "I was very happy and grateful" in the feedback form. The emotion engine classifies this emotion as "joy" and uses it to recommend activities for the next time. In this way, volunteer activities based on the user's emotions can be recommended, improving the user's experience.

[0489] This system analyzes the user's emotions and recommends volunteer activities based on those emotions, thereby achieving effective volunteer activities with high user satisfaction.

[0490] The processing flow will be explained below.

[0491] Step 1:

[0492] User

[0493] Users access the platform, click "Sign Up," enter the required information such as name, email address, and password, and then press the "Register" button to create an account.

[0494] Step 2:

[0495] Terminal

[0496] The terminal receives the information entered by the user and transmits it to the server.

[0497] Step 3:

[0498] server

[0499] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[0500] Step 4:

[0501] User

[0502] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[0503] Step 5:

[0504] Terminal

[0505] The terminal transmits the profile information entered by the user to the server.

[0506] Step 6:

[0507] server

[0508] The server stores the received profile information in a database. It also uses an emotion engine to analyze the user's emotions when they input their information, and adds the analysis results to the profile information.

[0509] Step 7:

[0510] server

[0511] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model.

[0512] Step 8:

[0513] server

[0514] The server generates a recommendation list based on the analysis results and lists the most suitable volunteer activities taking into account the user's emotional state.

[0515] Step 9:

[0516] Terminal

[0517] The terminal displays the recommendation list sent from the server to the user.

[0518] Step 10:

[0519] User

[0520] The user selects the volunteer activity they would like to participate in from the recommended list and clicks the "Participate" button to confirm their selection.

[0521] Step 11:

[0522] Terminal

[0523] The terminal transmits the user's selection information to the server.

[0524] Step 12:

[0525] server

[0526] The server stores the received selection information in a database, confirms the reservation, records the volunteer activity details, notifies the user of the reservation completion, and provides the necessary training materials and video links to the device.

[0527] Step 13:

[0528] Terminal

[0529] The terminal displays the provided training materials and video links to the user.

[0530] Step 14:

[0531] User

[0532] Users review the training materials and videos provided to them and acquire the necessary knowledge.

[0533] Step 15:

[0534] server

[0535] The day before the volunteer activity, the server sends a reminder to the user.

[0536] Step 16:

[0537] Terminal

[0538] The terminal receives the reminder message and notifies the user.

[0539] Step 17:

[0540] User

[0541] The user checks the reminder and reconfirms the volunteering date.

[0542] Step 18:

[0543] server

[0544] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[0545] Step 19:

[0546] Terminal

[0547] The terminal displays a feedback form to the user and transmits the entered content to the server.

[0548] Step 20:

[0549] User

[0550] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0551] Step 21:

[0552] server

[0553] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The analysis results are stored in a database and reflected in the next volunteer activity recommendation.

[0554] Step 22:

[0555] server

[0556] The next time the server generates recommendations, it will take into account the collected feedback and the results of sentiment analysis to suggest volunteer activities that are more suitable for the user.

[0557] This system analyzes users' emotions and recommends volunteer activities, thereby achieving high user satisfaction and effective volunteer activities.

[0558] Example 2

[0559] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0560] Conventional volunteer activity matching systems have difficulty recommending volunteer activities based on user emotions, which makes it difficult to increase user satisfaction. Furthermore, systems for efficiently collecting user feedback and utilizing it for next-time recommendations are lacking. Furthermore, systems for providing reminders before volunteer activities and necessary training materials are insufficient. To solve these issues, an advanced matching system that includes user emotion analysis is needed.

[0561] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0562] In this invention, the server includes: a means for users to input registration information; a means for saving user profile information in a database; a means including an emotion analysis engine for analyzing user emotions; a means for using a generative AI model to perform matching using volunteer demand information, user profile information, and emotion analysis results; a means for providing the generated volunteer recommendations to the user; a means for users to make reservations for volunteer activities; a means for providing training materials necessary for volunteer activities; a means for collecting feedback on volunteer activities and using it to make recommendations for the next activity; a means for sending a reminder to the user the day before the volunteer activity; and a means for analyzing the user's feedback using the emotion analysis engine and automatically saving the feedback in a database. This makes it possible to recommend optimal volunteer activities based on the user's emotions and increase user satisfaction. Furthermore, by reflecting the feedback analysis in the next recommendation, more effective volunteer activities can be realized.

[0563] "User" refers to an individual who accesses the System and participates in volunteer activities.

[0564] "Registration Information" refers to the necessary data, such as name, email address, and password, entered by a User when registering with the System.

[0565] "Profile Information" refers to detailed data entered by a user, such as volunteer experience, areas of interest, available time, and skills.

[0566] "Database" means a digital storage device for storing user registration and profile information.

[0567] "Emotion analysis engine" refers to an algorithm or software that analyzes a user's emotional state from their input.

[0568] "Volunteer demand information" refers to data on volunteer activities provided by local communities and organizations.

[0569] "Generative AI model" refers to an artificial intelligence model that recommends optimal volunteer activities based on a user's profile information and sentiment analysis results.

[0570] "Recommendations" refers to suggestions for volunteer activities suitable for the user, generated by a generative AI model.

[0571] "Reservation information" refers to detailed data such as the date, time, and location that a user enters to participate in a volunteer activity.

[0572] "Training Materials" means materials and video links that enable Users to acquire the necessary knowledge and skills before participating in a Volunteer Activity.

[0573] "Feedback" refers to information about the volunteer experience and areas for improvement provided by the user after completing the volunteer activity.

[0574] "Reminder" refers to a notification message sent to a user the day before a volunteer activity.

[0575] This invention provides a system that analyzes a user's emotions and recommends volunteer activities based on the results, thereby increasing user satisfaction and enabling effective volunteer activities. This system includes the following processes:

[0576] User registration and profile creation

[0577] User:

[0578] A user accesses the platform and registers, entering the required information (name, email address, password, etc.) to create an account.

[0579] Device:

[0580] The terminal receives the registration information entered by the user and transmits it to the server.

[0581] server:

[0582] The server stores the received information in a database and sends the user a confirmation email of the completed registration.

[0583] User:

[0584] A user logs in and goes to their profile page, where they enter details such as volunteer experience, areas of interest, available time, and skills.

[0585] Device:

[0586] The terminal transmits the profile information entered by the user to the server.

[0587] server:

[0588] The server stores the received profile information in a database and analyzes the user's input emotions using a sentiment analysis engine. Based on the analysis results, it prepares to generate a highly accurate recommendation list.

[0589] Providing volunteer information and matching

[0590] server:

[0591] The server retrieves information about local volunteer demand from a database or external API. It then uses the retrieved information, the user's profile information, and the results of emotion analysis to analyze the information using a generative AI model, generating appropriate recommendations based on the user's emotional state.

[0592] Device:

[0593] The terminal displays the recommendation list sent from the server to the user.

[0594] User:

[0595] The user selects the most suitable volunteer activity from the presented recommendation list according to their emotional state.

[0596] Volunteer booking and training

[0597] User:

[0598] The user clicks the "Participate" button and proceeds to the reservation form, where they enter the required information to confirm the reservation.

[0599] Device:

[0600] The terminal transmits the input reservation information to the server.

[0601] server:

[0602] The server saves the reservation information in a database and sends the user a notification that the reservation is complete, along with any necessary training materials and video links.

[0603] Device:

[0604] The terminal displays the provided training materials and video links to the user.

[0605] User:

[0606] Users review training materials and videos to gain the necessary knowledge.

[0607] Volunteer Reminders and Execution

[0608] server:

[0609] The day before the volunteer activity, the server sends a reminder email to the user.

[0610] Device:

[0611] The terminal receives the reminder message and notifies the user.

[0612] User:

[0613] Users receive reminders to reconfirm their volunteering dates.

[0614] Sharing and evaluating volunteer experiences

[0615] server:

[0616] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[0617] Device:

[0618] The terminal displays the feedback form to the user and transmits the entered content to the server.

[0619] User:

[0620] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0621] server:

[0622] The server analyzes the received feedback using a sentiment analysis engine to determine the user's sentiment. The analysis results are stored in a database and used to improve the quality of future recommendations.

[0623] Specific examples

[0624] As a concrete example, consider a case where a user created an account and participated in disaster relief activities last week. The user reviewed the training materials, received reminders, and participated in the activities. After completing the activities, the user entered "I was very happy and grateful" in the feedback form. The sentiment analysis engine classifies this emotion as "joy" and uses it to recommend activities for the next time. In this way, volunteer activities based on the user's emotions are recommended, improving the user's experience.

[0625] Prompt Sentence Examples

[0626] "Build a system that analyzes users' emotional data and volunteer demand information to recommend appropriate volunteer activities. This system combines an emotion analysis engine and a generative AI model, and takes into account users' emotions such as joy and sadness."

[0627] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0628] Step 1:

[0629] User

[0630] A user accesses the platform and clicks "New Registration." They enter the required information (name, email address, password, etc.) and clicks "Register."

[0631] Input: User's name, email address, and password

[0632] Output: Registration information is sent to the device

[0633] Step 2:

[0634] Terminal

[0635] The terminal transmits the registration information entered by the user to the server.

[0636] Input: User registration information

[0637] Output: Registration information sent to the server

[0638] Step 3:

[0639] server

[0640] The server stores the received registration information in a database and automatically generates and sends a confirmation email to confirm that registration is complete.

[0641] Input: Registration information

[0642] Data processing / data calculation: Saving registration information in a database, generating confirmation emails

[0643] Output: Send confirmation email

[0644] Step 4:

[0645] User

[0646] A user logs in, visits their profile page, and enters detailed profile information (volunteer experience, areas of interest, available hours, skills, etc.).

[0647] Input: Profile information

[0648] Output: Profile information is sent to the device

[0649] Step 5:

[0650] Terminal

[0651] The terminal transmits the profile information entered by the user to the server.

[0652] Input: User profile information

[0653] Output: Profile information sent to the server

[0654] Step 6:

[0655] server

[0656] The server stores the received profile information in a database, launches a sentiment analysis engine to analyze the user's input sentiment, saves the analysis results, and prepares recommendations.

[0657] Input: Profile information

[0658] Data processing / data calculation: saving profile information in a database, analyzing using a sentiment analysis engine, and saving the analysis results

[0659] Output: Save the analysis results

[0660] Step 7:

[0661] server

[0662] The server retrieves local volunteer demand information from a database or external API. Using this information, it analyzes the user's profile information and sentiment analysis results using a generative AI model to generate recommendations.

[0663] Input: Volunteer demand information, user profile information, sentiment analysis results

[0664] Data processing / data calculation: Analysis and recommendation generation using generative AI models

[0665] Output: Generate a recommendation list

[0666] Step 8:

[0667] Terminal

[0668] The terminal displays the recommendation list sent from the server to the user.

[0669] Input: Recommendation list

[0670] Output: Display of recommendation list

[0671] Step 9:

[0672] User

[0673] The user selects the most suitable volunteer activity from the list of recommendations provided and clicks "Participate." Next, the user fills in the necessary information in the reservation form to confirm the reservation.

[0674] Input: Reservation information

[0675] Output: Reservation information is sent to the terminal

[0676] Step 10:

[0677] Terminal

[0678] The terminal transmits the input reservation information to the server.

[0679] Input: Reservation information

[0680] Output: Reservation information sent to the server

[0681] Step 11:

[0682] server

[0683] The server saves the reservation information in a database, notifies the user of the completion of the reservation, and simultaneously generates the necessary training materials and video links and sends them to the terminal.

[0684] Input: Reservation information

[0685] Data processing / data calculation: storing reservation information in a database, generating notifications, generating training materials and links

[0686] Output: Notification of reservation completion, sending of training materials and video links

[0687] Step 12:

[0688] Terminal

[0689] The terminal displays the provided training materials and video links to the user.

[0690] Input: Training materials, video links

[0691] Output: Display of training materials and video links

[0692] Step 13:

[0693] User

[0694] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[0695] Input: Training materials, videos

[0696] Output: Training completed

[0697] Step 14:

[0698] server

[0699] The day before the volunteer activity, the server sends a reminder email to the user.

[0700] Input: Reservation information

[0701] Data processing / data calculation: generating and sending reminder emails

[0702] Output: Send reminder email

[0703] Step 15:

[0704] Terminal

[0705] The terminal receives the reminder message and notifies the user.

[0706] Input: Reminder message

[0707] Output: Reminder message notification

[0708] Step 16:

[0709] User

[0710] Users receive reminders to reconfirm their volunteering dates.

[0711] Enter: Reminder

[0712] Output: Reconfirm date

[0713] Step 17:

[0714] server

[0715] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[0716] Input: Reservation information, activity information

[0717] Data processing / data calculation: feedback form generation and submission

[0718] Output: Feedback form submission

[0719] Step 18:

[0720] Terminal

[0721] The terminal displays the feedback form to the user and transmits the entered content to the server.

[0722] Input: Feedback

[0723] Output: Feedback sent to the server

[0724] Step 19:

[0725] User

[0726] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0727] Input: Feedback

[0728] Output: Feedback sent

[0729] Step 20:

[0730] server

[0731] The server analyzes the received feedback using a sentiment analysis engine to determine the user's emotions, and stores the analysis results in a database to be used to improve the quality of future recommendations.

[0732] Input: Feedback

[0733] Data processing / data calculation: Analysis using the sentiment analysis engine, saving the analysis results

[0734] Output: Save the analysis results

[0735] (Application example 2)

[0736] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0737] Conventional volunteer activity participation systems only match users based on their profile information and volunteer demand information, without considering their emotions. This results in low user satisfaction and compatibility, and often results in users not actually participating in activities. Furthermore, they are unable to fully utilize user feedback, making continuous improvement difficult. There is a need to solve these issues and provide more accurate recommendations that reflect users' emotions.

[0738] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a generative AI model that performs matching using user profile information and volunteer demand information, means for analyzing user emotions and selecting activities, and means for collecting user emotional data in real time when the user visits the store and reflecting this data in recommendations. This makes it possible to recommend appropriate volunteer activities based on the user's emotions.

[0739] "User" refers to an individual who registers with the system and wishes to participate in volunteer activities.

[0740] "Profile Information" refers to basic information such as a user's name, email address, and password, as well as detailed information such as volunteer experience, areas of interest, available time, and skills.

[0741] "Volunteer demand information" refers to information such as the type of volunteer activities desired by local communities and organizations, the skills required, the dates and times of activities, and the location.

[0742] A "generative AI model" is a type of artificial intelligence that analyzes a user's profile information and volunteer demand information to recommend the most appropriate volunteer activities.

[0743] "Means for analyzing emotions" refers to technologies for recognizing and analyzing a user's emotional state in real time, such as emotion engines and emotion analysis algorithms.

[0744] "Recommendations" refers to a list of volunteer activities and services suggested by the system based on the user's attributes and status.

[0745] "Training Materials" means written, video, or other educational materials containing the information necessary for a User to properly perform a particular Volunteer Activity.

[0746] "Feedback" refers to impressions and opinions, including experiences and suggestions for improvement, provided by users after volunteering.

[0747] "Database" refers to a system for storing and managing user information, activity history, feedback, etc.

[0748] "Means for making reservations" refers to a function that allows users to reserve a date, time, and location online to participate in volunteer activities.

[0749] A "reminder" is a message sent to the user the day before an activity to remind them of their plans.

[0750] "Emotional data" refers to information that expresses the emotional state obtained from the user's facial expressions, actions, words, etc. in numerical or categorical form.

[0751] "Means of collecting data in real time" refers to technology that allows users to instantly collect their behavior and emotions on the spot and record them as data.

[0752] The present invention provides a system that streamlines the process for users to participate in volunteer activities and, in particular, provides more accurate recommendations by incorporating sentiment analysis. Specific embodiments are described below.

[0753] 1. User registration and profile creation

[0754] A user first accesses the platform, clicks "New Registration," and enters the required information, such as name, email address, and password. Once the information is entered, the device receives the information and sends it to the server. The server stores the received information in a database and sends the user a confirmation email of successful registration. The user then goes to the profile page and enters detailed information, such as volunteer experience, areas of interest, available time, and skills, which is then sent to the server via the device. The server stores this detailed profile information in a database and prepares it for analyzing the user's emotions.

[0755] 2. Providing volunteer information and matching

[0756] The server retrieves local volunteer demand information from a database or external API, compares this information with the user's profile information, analyzes the user's current emotional state using an emotion engine, and recommends optimal volunteer activities using a generative AI model. The device displays the recommendation list sent from the server to the user.

[0757] 3. Volunteer booking and training

[0758] The user selects the volunteer activity they want from the displayed recommendation list and clicks the "Participate" button to proceed to the reservation form. After entering the required information and confirming the reservation, the device sends this information to the server. The server receives the reservation information, stores the volunteer activity details in a database, and notifies the user that the reservation is complete. It also provides the necessary training materials and video links.

[0759] 4. Volunteer Reminders and Execution

[0760] The day before the volunteer activity, the server sends a reminder message to the user. The device receives this reminder message and notifies the user. The user receives the notification and reconfirms the activity schedule.

[0761] 5. Sharing and evaluating volunteer experiences

[0762] After the volunteer activity is completed, the server generates and sends a feedback form to the user. The terminal displays the feedback form to the user, who then enters their experience and suggestions for improvement and submits it. The server then analyzes the received feedback using an emotion engine to determine the user's emotional state. The results are stored in a database and reflected in the next recommendation.

[0763] Examples of concrete examples and prompts

[0764] Examples:

[0765] A user comes into the store, and the camera recognizes their smile and classifies it as "happy."

[0766] Based on the emotional state of "joy," the system refers to past profile information and purchase history to recommend refreshing products (flowers, aroma goods, etc.).

[0767] The user follows the recommendation, purchases the product, and enters feedback such as "It was very refreshing."

[0768] The next time you visit, we will use this feedback to provide you with even more accurate recommendations.

[0769] Example prompt sentence:

[0770] Recommend the best products and services to users based on the following data:

[0771] 1. User basic information (name, gender, age, interests)

[0772] 2. The user's emotional state (happiness, sadness, anger, etc.)

[0773] 3. User purchase history

[0774] For example, "User name: Tanaka Taro," "Gender: Male," "Age: 35," "Interests: Outdoors, gardening," "Emotional state: Joy," "Purchase history: Outdoor goods, houseplants," etc.

[0775] Prompt: Recommendation if you see a girl smiling: "Recommend a refreshing product, such as flowers or aromatherapy products."

[0776] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0777] Step 1:

[0778] A user accesses the platform and clicks "New Registration." They enter the required information, such as their name, email address, and password. Once the information is entered, the device receives it and sends it to the server. The entered data is sent to the server, which then stores it in a database.

[0779] input:

[0780] User basic information (name, email address, password)

[0781] output:

[0782] User information stored in a database

[0783] Specific behavior:

[0784] The user enters basic information into the on-screen form and clicks the submit button. The device transmits the information to the server, which stores it in a database.

[0785] Step 2:

[0786] The server sends the user a confirmation email to confirm the registration. The user receives the confirmation email and accesses the platform again to log in. After logging in, the user goes to the profile page and enters details such as volunteer experience, areas of interest, available time, skills, etc. The device then sends these details to the server.

[0787] input:

[0788] Detailed user profile information (activity experience, interests, available time, skills)

[0789] output:

[0790] Detailed profile information stored in a database

[0791] Specific behavior:

[0792] The user clicks on the link in the confirmation email and logs back into the platform. They enter their details on the profile page and click the submit button. The device transmits the information to the server, which stores it in a database.

[0793] Step 3:

[0794] The server retrieves information about local volunteer demand from a database or external API. It compares this information with the user's profile information and uses an emotion engine to analyze the user's current emotional state. It then uses a generative AI model to generate recommendations for optimal volunteer activities.

[0795] input:

[0796] User profile information, local volunteer demand information, emotional data

[0797] output:

[0798] Recommendation List

[0799] Specific behavior:

[0800] The server periodically updates and stores local volunteer demand data in a database. The generative AI model analyzes this data and user profiles to generate recommendations for optimal volunteer activities.

[0801] Step 4:

[0802] The terminal displays the recommendation list sent from the server to the user, who then selects a volunteer activity from the displayed recommendation list.

[0803] input:

[0804] Recommendation List

[0805] output:

[0806] User-selected volunteer activities

[0807] Specific behavior:

[0808] The server sends the generated recommendation list to the terminal, which displays it to the user. The user selects a preferred activity and sends the selection information.

[0809] Step 5:

[0810] The user clicks the "Participate" button to proceed to the reservation form. They enter the required information and confirm the reservation. The device sends this information to the server. The server receives the reservation information, stores the volunteer activity details in a database, and sends a notification to the user that the reservation is complete.

[0811] input:

[0812] Reservation information (date, time, location, contact information, etc.)

[0813] output:

[0814] Reservation information stored in the database, reservation completion notification

[0815] Specific behavior:

[0816] The user enters the necessary information into the reservation form and clicks the submit button. The terminal transmits the information to the server, which stores it in a database and sends a confirmation email.

[0817] Step 6:

[0818] The server provides the user with the necessary training materials and video links, and the terminal displays these training materials to the user, who then reviews them and acquires the necessary knowledge.

[0819] input:

[0820] Training materials, video links

[0821] output:

[0822] User learning progress

[0823] Specific behavior:

[0824] The server generates a training material link and sends it to the terminal, which displays it to the user, who then checks the material.

[0825] Step 7:

[0826] The server sends a reminder message to the user the day before the volunteer activity. The device receives the reminder message and notifies the user. The user receives the notification and reconfirms the activity date.

[0827] input:

[0828] Reminder Information

[0829] output:

[0830] Reminders

[0831] Specific behavior:

[0832] The server generates a reminder message at the set date and time and sends it to the device, which then displays the reminder to the user.

[0833] Step 8:

[0834] After the volunteer activity is completed, the server generates and sends a feedback form to the user. The terminal displays the feedback form to the user, who then enters their experience and suggestions for improvement and submits it. The server then analyzes the received feedback using an emotion engine to determine the user's emotional state. The results are stored in a database and reflected in the next recommendation.

[0835] input:

[0836] Feedback content

[0837] output:

[0838] Analyzed emotion data, feedback stored in database

[0839] Specific behavior:

[0840] The server generates a feedback form and sends it to the device. The user enters their experience and suggestions for improvement into the form and clicks the submit button. The device transmits the information to the server, which analyzes it using an emotion engine and stores it in a database.

[0841] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0842] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0843] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0844] [Second embodiment]

[0845] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0846] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0847] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0848] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0849] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0850] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0851] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0852] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0853] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0854] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0855] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0856] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0857] This invention is a system for efficiently recruiting and applying for volunteer activities, and is implemented as follows.

[0858] User registration and profile creation

[0859] User

[0860] Users first access the platform and create a new account.

[0861] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[0862] After logging in, users are directed to a profile page where they can enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[0863] Terminal

[0864] The input information is received and sent to the server.

[0865] server

[0866] The received information is stored in a database.

[0867] Send a confirmation email to confirm registration and prepare to recommend volunteer activities suitable for the user based on their profile information.

[0868] Providing volunteer information and matching

[0869] server

[0870] Get local volunteer demand information from a database or external API.

[0871] The AI ​​model analyzes user profile information and volunteer demand information to generate appropriate recommendations.

[0872] Terminal

[0873] The recommendation list sent from the server is displayed to the user.

[0874] User

[0875] Select the volunteer activity you would like to participate in from the list of recommendations provided.

[0876] Volunteer booking and training

[0877] User

[0878] After selecting your volunteer activity, click the "Participate" button to proceed to the reservation form.

[0879] Enter the required information and confirm your reservation.

[0880] Terminal

[0881] The user's selection information is received and the information required for the reservation form is sent to the server.

[0882] server

[0883] Confirm the booking and save the volunteer activity details in a database.

[0884] A confirmation of the booking will be sent back to the user, along with any training materials or video links required for the relevant volunteer activity.

[0885] Terminal

[0886] Display training materials and links to users.

[0887] User

[0888] Review the training materials provided and acquire the necessary knowledge.

[0889] Volunteer Reminders and Execution

[0890] server

[0891] Send users a reminder the day before their volunteer activity.

[0892] Terminal

[0893] Receive reminder messages and notify users.

[0894] User

[0895] Receive reminders and reconfirm your volunteering dates.

[0896] Sharing and evaluating volunteer experiences

[0897] server

[0898] After the volunteer activity is completed, a feedback form is generated and sent to the user.

[0899] Terminal

[0900] A feedback form is displayed to the user and the entered information is sent to the server.

[0901] User

[0902] Fill out the feedback form and submit it to let us know your experience with the activity and any suggestions for improvement.

[0903] server

[0904] The received feedback is analyzed and stored in a database.

[0905] This will be used to recommend the next volunteer activity, allowing for more precise matching.

[0906] Specific examples

[0907] As a specific example, if user "Ichiro Suzuki" creates an account and enters in his profile that he has emergency medical skills, the server will recommend disaster relief activities taking place this weekend in the surrounding area. Then, it will prioritize activities that "can utilize his emergency medical skills." Ichiro Suzuki selects and reserves the activity, learning the provided training materials. He receives a reminder the day before the activity, and after completing the volunteer activity, he can enter feedback that will be reflected in the next activity.

[0908] The system recommends volunteer activities that best suit the user's needs and skills, making volunteering faster and more efficient.

[0909] The processing flow will be explained below.

[0910] Step 1:

[0911] User

[0912] The user accesses the platform, clicks "New Registration," enters the required information such as name, email address, and password, and presses the "Register" button.

[0913] Step 2:

[0914] Terminal

[0915] The terminal receives the information entered by the user and transmits it to the server.

[0916] Step 3:

[0917] server

[0918] The server stores the received information in a database and sends a confirmation email to the user once the information has been saved.

[0919] Step 4:

[0920] User

[0921] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[0922] Step 5:

[0923] Terminal

[0924] The terminal transmits the profile information entered by the user to the server.

[0925] Step 6:

[0926] server

[0927] The server stores the received profile information in a database.

[0928] Step 7:

[0929] server

[0930] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it uses a generative AI model to analyze the user's profile and volunteer demand information and generate a recommendation list.

[0931] Step 8:

[0932] Terminal

[0933] The terminal displays the recommendation list received from the server to the user.

[0934] Step 9:

[0935] User

[0936] The user selects the volunteer activity they wish to participate in from the displayed list of recommendations.

[0937] Step 10:

[0938] User

[0939] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[0940] Step 11:

[0941] Terminal

[0942] The terminal transmits the reservation information entered by the user to the server.

[0943] Step 12:

[0944] server

[0945] The server receives the reservation information, stores the volunteer activity details in a database, and then sends the user a notification that the reservation is complete, along with any necessary training materials and video links.

[0946] Step 13:

[0947] Terminal

[0948] The terminal displays the provided training materials and links to the user.

[0949] Step 14:

[0950] User

[0951] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[0952] Step 15:

[0953] server

[0954] The day before the volunteer activity, the server sends a reminder to the user.

[0955] Step 16:

[0956] Terminal

[0957] The terminal receives the reminder message and notifies the user.

[0958] Step 17:

[0959] User

[0960] Users receive reminders to reconfirm their volunteering dates.

[0961] Step 18:

[0962] server

[0963] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[0964] Step 19:

[0965] Terminal

[0966] The terminal displays a feedback form to the user and transmits the entered content to the server.

[0967] Step 20:

[0968] User

[0969] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[0970] Step 21:

[0971] server

[0972] The server analyzes the received feedback and stores it in a database. Based on the analysis results, the server will use them to recommend the next volunteer activity.

[0973] Through this series of steps, users can efficiently participate in volunteer activities and use the experience gained from the activities for future use.

[0974] Example 1

[0975] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0976] In conventional volunteer recruitment systems, it is difficult for users to find volunteer activities that best suit their skills and interests, and the application process is cumbersome and inefficient. Furthermore, the management of activity bookings, training, reminders, and feedback is not centralized, and an improvement in the user experience is required.

[0977] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0978] In this invention, the server includes means for a user to input registration information, means for inputting basic information and detailed profile information of the user, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for sending a registration completion confirmation email to the user, means for obtaining local volunteer demand information from a database or an external API, means for analyzing the user's profile information and volunteer demand information with an AI model, means for providing the generated volunteer recommendations to the user, means for the user to make a reservation to participate in a volunteer activity, means for sending a reservation completion confirmation email and training materials to the user, and means for collecting feedback on the volunteer activity and using it for next recommendations. This makes it possible to efficiently find volunteer activities that best suit a user's skills and interests, simplify the application process, and centralize management of training, reminders, and feedback.

[0979] "User" refers to an individual or group that registers with the system to participate in volunteer activities and inputs and operates various information.

[0980] "Registration Information" refers to basic personal information such as name, email address, and password that a User enters into the System.

[0981] "Profile Information" refers to detailed information that a User enters into the system, such as volunteer experience, areas of interest, available time, and skills.

[0982] "Server" refers to a computer system that receives, processes, and stores information sent by users in a database.

[0983] "Database" refers to a data storage system for storing user data, including registration information, profile information, volunteer demand information, and feedback information.

[0984] "Generative AI Model" refers to an artificial intelligence model used to analyze a user's profile information and volunteer demand information and generate appropriate recommendations.

[0985] "Recommendations" refers to a list of volunteer activities recommended to a user by a generative AI model.

[0986] "Training Materials" means materials and video links that a User must study before participating in a Volunteer Activity.

[0987] "Feedback" refers to the user's experience with the activity and evaluation of areas for improvement that they enter after completing the volunteer activity.

[0988] "Reminder" refers to a notification message sent to a user immediately before a volunteer activity.

[0989] "External API" refers to an application programming interface used to obtain volunteer demand information from data sources external to the System.

[0990] The present invention is a system for efficiently recruiting and applying for volunteer activities. A specific embodiment of this system will be described below.

[0991] User registration and profile creation

[0992] User

[0993] Users first access the platform using a web browser or mobile application and are redirected to a page to create a new account.

[0994] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[0995] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[0996] Terminal

[0997] The terminal transmits the basic information and profile information entered by the user to the server.

[0998] server

[0999] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[1000] Providing volunteer information and matching

[1001] server

[1002] The server retrieves local volunteer demand information from an internal database or an external API.

[1003] The server analyzes the user's profile information and the acquired volunteer demand information using a generative AI model (e.g., using TensorFlow or PyTorch) to generate a list of recommended appropriate volunteer activities.

[1004] Terminal

[1005] The terminal displays the recommendation list received from the server to the user.

[1006] User

[1007] Users select the volunteer activities they would like to participate in from the recommendation list.

[1008] Volunteer booking and training

[1009] User

[1010] Users select the volunteer activity they wish to participate in and click the "Participate" button. They then fill in the necessary information in the reservation form to confirm their reservation.

[1011] Terminal

[1012] The terminal transmits the user's reservation information to the server.

[1013] server

[1014] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials (e.g., PDFs or video links) required for the volunteer activity.

[1015] Terminal

[1016] The terminal displays training materials and video links to the user.

[1017] User

[1018] The user reviews the provided training materials and acquires the necessary knowledge.

[1019] Volunteer Reminders and Execution

[1020] server

[1021] The server sends a reminder to the user the day before the volunteer activity.

[1022] Terminal

[1023] The terminal receives the reminder message and notifies the user.

[1024] User

[1025] Users receive reminders to reconfirm their volunteering dates.

[1026] Sharing and evaluating volunteer experiences

[1027] server

[1028] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[1029] Terminal

[1030] The terminal displays a feedback form to the user and transmits the entered content to the server.

[1031] User

[1032] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1033] server

[1034] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[1035] Examples of concrete examples and prompts

[1036] As a specific example, consider the case where user "A" has emergency medical skills. The server retrieves local volunteer information from a database or external API, analyzes it using a generative AI model, and recommends the most suitable volunteer activity for "A" (for example, disaster relief activities).

[1037] An example of a prompt is as follows:

[1038] "How do users select a volunteer activity and complete a booking?"

[1039] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1040] Step 1:

[1041] User

[1042] First, users access the platform using a web browser or mobile application, and are redirected to a new account creation page where they enter basic information such as their name, email address, and password, and then click the "Register" button to create an account.

[1043] Input: Name, Email Address, Password

[1044] Output: Registration request

[1045] Specific operation: The browser will redirect to the account creation page and display the input form. When the user presses the "Register" button, the input information will be sent to the server.

[1046] Step 2:

[1047] Terminal

[1048] The terminal sends the basic information entered by the user to the server.

[1049] Input: Basic information entered by the user

[1050] Output: Registration information sent to the server

[1051] Specific operation: The terminal sends an HTTP POST request to the server.

[1052] Step 3:

[1053] server

[1054] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[1055] Input: Registration information sent to the server

[1056] Output: User registration information stored in the database, confirmation email

[1057] Specific operation: The server creates a record in the database and sends a confirmation email using the mail server.

[1058] Step 4:

[1059] User

[1060] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[1061] Input: Login information, profile information

[1062] Output: Detailed profile information

[1063] Specific operation: The browser will redirect to the profile page, and an input form will be displayed. The user will enter their information.

[1064] Step 5:

[1065] Terminal

[1066] The terminal transmits the detailed profile information entered by the user to the server.

[1067] Input: Detailed profile information

[1068] Output: Profile information sent to the server

[1069] Specific operation: The terminal sends an HTTP POST request to the server.

[1070] Step 6:

[1071] server

[1072] The server stores the received profile information in a database and retrieves local volunteer demand information from an internal database or an external API.

[1073] Input: Profile information sent to the server

[1074] Output: Profile information stored in the database, local volunteer demand information

[1075] Specific operation: The server creates a record in the database and sends an API request to retrieve volunteer demand information.

[1076] Step 7:

[1077] server

[1078] The server analyzes the user's profile information and volunteer demand information using a generative AI model to generate appropriate volunteer recommendations.

[1079] Input: User profile information, volunteer demand information

[1080] Output: Volunteer recommendation list

[1081] Specific operations: Run analysis algorithms using generative AI models (such as TensorFlow or PyTorch).

[1082] Step 8:

[1083] Terminal

[1084] The terminal displays the recommendation list received from the server to the user.

[1085] Input: Volunteer Recommendation List

[1086] Output: The recommendation list shown to the user

[1087] Specific operation: The device receives the HTTP response and renders the recommendation list in the browser.

[1088] Step 9:

[1089] User

[1090] Users select the volunteer activity they want to participate in from the recommendation list and click the "Participate" button. Then, they fill in the necessary information in the reservation form to confirm their reservation.

[1091] Input: Recommendation list, reservation information

[1092] Output: Booking request

[1093] Specific operation: A click event transitions to the next form page, and after completing the input, press the "Confirm" button.

[1094] Step 10:

[1095] Terminal

[1096] The terminal transmits the user's reservation information to the server.

[1097] Input: Reservation information

[1098] Output: Reservation information sent to the server

[1099] Specific operation: The terminal sends an HTTP POST request to the server.

[1100] Step 11:

[1101] server

[1102] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials required for the volunteer activity.

[1103] Input: Reservation information

[1104] Output: Booking information stored in a database, confirmation emails, training materials

[1105] What happens: The server saves the reservation information in a database and uses a mail server to send a confirmation email containing the training materials.

[1106] Step 12:

[1107] Terminal

[1108] The terminal displays training materials and video links to the user.

[1109] Input: Training materials

[1110] Output: The training material displayed to the user

[1111] What happens: The browser or app renders the material and displays it to the user.

[1112] Step 13:

[1113] server

[1114] The server sends a reminder to the user the day before the volunteer activity.

[1115] Input: Date information for the relevant volunteer activity

[1116] Output: Reminder message

[1117] Specific operation: The server uses the mail server to send the reminder message.

[1118] Step 14:

[1119] Terminal

[1120] The terminal receives the reminder message and notifies the user.

[1121] Input: Reminder message

[1122] Output: Reminders notified to the user

[1123] Specific behavior: The device displays a notification and alerts the user.

[1124] Step 15:

[1125] server

[1126] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[1127] Input: Volunteer activity completion information

[1128] Output: Feedback form submission

[1129] Specific operation: The server sends the feedback form using the mail server.

[1130] Step 16:

[1131] Terminal

[1132] The terminal displays a feedback form to the user and transmits the entered content to the server.

[1133] Input: Feedback Form

[1134] Output: The input feedback

[1135] What happens: The browser or app displays a feedback form, which the user fills out and then submits to the server.

[1136] Step 17:

[1137] server

[1138] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[1139] Input: Feedback

[1140] Output: Parsed feedback data, feedback information stored in a database

[1141] What happens: The analysis algorithm processes the feedback and creates a record in the database.

[1142] (Application example 1)

[1143] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1144] Conventional volunteer participation systems often make it difficult for users to find activities that match their skills and interests, resulting in inappropriate matching. Additionally, users are often unable to fully prepare for volunteer activities due to insufficient training materials and videos. Furthermore, because feedback is collected and analyzed manually, it is difficult to effectively reflect this feedback in future recommendations.

[1145] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1146] In this invention, the server includes a means for a user to input registration information, a means for using a generative AI model that performs matching using the user's profile information and volunteer demand information, a means for providing the generated volunteer recommendations to the user, a means for the user to make a reservation to participate in a volunteer activity, a means further including a means for providing training materials and videos necessary for the volunteer activity, a means for collecting feedback on the volunteer activity and using it for the next recommendation, a means for viewing the training video using a head-mounted display, and a means for sending a reminder to the user the day before the volunteer activity. This allows users to easily find the most suitable volunteer activity based on their skills and interests, allowing them to participate in the activity with sufficient preparation, and allows feedback to be effectively collected and analyzed to be reflected in the next recommendation.

[1147] "User" refers to an individual who registers with the System and provides profile information to participate in volunteer activities.

[1148] "Means for entering registration information" refers to the interface through which a user accesses the system and enters basic information such as name, email address, and password.

[1149] "Profile information" refers to information that indicates the user's characteristics and background, such as the user's volunteer experience, areas of interest, available time, and skills.

[1150] "Volunteer demand information" refers to information about the types and content of volunteers needed in specific regions or organizations.

[1151] A "generative AI model" refers to an artificial intelligence model that analyzes a user's profile information and volunteer demand information to recommend the most suitable volunteer activities for the user.

[1152] "Recommendations" refers to potential volunteer activities suggested to users by the generative AI model.

[1153] "Means for making reservations" refers to an interface that allows a user to reserve a date, time, and location for a selected volunteer activity.

[1154] "Training materials and videos" refers to written and visual content that helps users learn the knowledge and skills necessary to participate in volunteer activities.

[1155] "Head-mounted display" refers to a display device used by a user to view training videos with a 360-degree field of view.

[1156] "Reminder" refers to a notification message sent to a user the day before a volunteer activity.

[1157] "Feedback" refers to the user's experience with the activity and their opinions on areas for improvement provided after completing the volunteer activity.

[1158] In the present invention, the following means and processes are used to provide a system that allows users to efficiently participate in volunteer activities.

[1159] 1. User registration and profile creation

[1160] A user accesses the system and creates a new account. The user enters basic information such as name, email address, and password, and presses the "Register" button, which sends the information to the server.

[1161] The server receives this and stores it in a database. After the user logs in, they go to their profile page and enter detailed profile information such as their volunteer experience, areas of interest, available time, skills, etc. This is also sent to the server and stored in the database.

[1162] 2. Providing volunteer information and matching

[1163] The server retrieves local volunteer demand information from a database or external API. Using a generative AI model, it analyzes the user's profile information and volunteer demand information to generate appropriate recommendations. These are sent to the user's device and displayed as a recommendation list.

[1164] Specifically, the following prompt sentences are input into the generative AI model, which then recommends the most suitable volunteer activity for the user:

[1165] User Profile:

[1166] Name: Ichiro Suzuki

[1167] Volunteer experience: Emergency medical technician

[1168] Area of ​​interest: Disaster relief

[1169] Available times: Weekends

[1170] Volunteer activities offered:

[1171] 1. Disaster support activities A

[1172] 2. Disaster relief activities B

[1173] 3. Community cleanup activities

[1174] Please choose one activity to recommend.

[1175] 3. Volunteer booking and training

[1176] The user selects the volunteer activity they wish to participate in from the recommended list. After making their selection, they click the "Participate" button and proceed to the reservation form. They then enter the required information and confirm their reservation.

[1177] The server receives the request, confirms the reservation, stores the volunteer activity details in a database, and returns a confirmation of the reservation to the user along with relevant training materials and video links that can be viewed on the user's smartphone or head-mounted display.

[1178] 4. Volunteer Reminders and Execution

[1179] The server sends a reminder to the user the day before the volunteer activity.

[1180] The terminal receives the reminder message and notifies the user.

[1181] The user checks this and reconfirms the schedule for volunteer activities.

[1182] 5. Sharing and evaluating volunteer experiences

[1183] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[1184] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1185] The server receives this, stores it in a database, and uses it to recommend volunteer activities for the next time.

[1186] The system configuration utilizes the following hardware and software:

[1187] Smartphone: iOS or Android compatible.

[1188] Head-mounted display: VR compatible display.

[1189] Server side: Uses AWS (Amazon Web Services).

[1190] AI model: Use Amazon SageMaker, etc.

[1191] Database: MySQL or PostgreSQL.

[1192] This allows users to easily find the best volunteer activities based on their skills and interests, allows them to participate in activities well prepared, and effectively collect and analyze feedback to reflect in future recommendations.

[1193] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1194] Step 1:

[1195] The user enters registration information

[1196] input:

[1197] The user enters basic information such as name, email address, and password.

[1198] Data processing / calculation:

[1199] The terminal organizes the input information and sends it to the server.

[1200] output:

[1201] The server sends a confirmation email to the user and stores the information in a database.

[1202] Step 2:

[1203] User enters profile information

[1204] input:

[1205] Users enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[1206] Data processing / calculation:

[1207] The terminal organizes the entered information and sends it to the server.

[1208] output:

[1209] The server saves the profile information to a database and notifies the user that the information has been saved.

[1210] Step 3:

[1211] Acquisition and analysis of volunteer demand information

[1212] input:

[1213] The server retrieves local volunteer demand information from a database or external API.

[1214] Data processing / calculation:

[1215] The server analyzes the acquired volunteer demand information and user profile information, and generates appropriate recommendations using a generative AI model.

[1216] output:

[1217] Send the recommendation list to the user.

[1218] Step 4:

[1219] User selects volunteer activity and makes reservation

[1220] input:

[1221] The user selects the volunteer activity they want to participate in from the recommended list and clicks "Participate." They then enter the required information and confirm their reservation.

[1222] Data processing / calculation:

[1223] The terminal transmits the input information to the server.

[1224] output:

[1225] The server stores the reservation information in a database and sends the user details, training materials and video links.

[1226] Step 5:

[1227] Watch training videos required for volunteer work

[1228] input:

[1229] The user receives the training materials and video links sent to them and begins watching them.

[1230] Data processing / calculation:

[1231] The device plays the video link on the head-mounted display or smartphone.

[1232] output:

[1233] Users watch training videos and acquire the necessary knowledge.

[1234] Step 6:

[1235] Volunteer Reminders

[1236] input:

[1237] The server sets a reminder the day before the volunteer activity.

[1238] Data processing / calculation:

[1239] The server generates a reminder message and sends it to the terminal.

[1240] output:

[1241] The terminal notifies the user of the reminder message.

[1242] Step 7:

[1243] Collecting feedback after volunteering

[1244] input:

[1245] After completing the activity, users enter their experience and suggestions for improvement in a feedback form submitted.

[1246] Data processing / calculation:

[1247] The device sends feedback information to the server, which analyzes it and stores it in a database.

[1248] output:

[1249] The server will incorporate the feedback into its next recommendations.

[1250] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1251] This invention is a system for efficiently recruiting and applying for volunteer activities, and in particular, it combines a function for recognizing a user's emotions and selecting activities. It is implemented through the following specific process.

[1252] User registration and profile creation

[1253] User

[1254] First, users access the platform and click "Sign Up." They then enter the required information, such as their name, email address, and password, and press the "Register" button to create an account.

[1255] Terminal

[1256] The terminal receives the information entered by the user and transmits it to the server.

[1257] server

[1258] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[1259] User

[1260] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[1261] Terminal

[1262] The terminal transmits the profile information entered by the user to the server.

[1263] server

[1264] The server stores the received profile information in a database and uses an emotion engine to analyze the emotions expressed by the user when they input their information. Based on the analysis results, the server prepares to generate a more accurate recommendation list.

[1265] Providing volunteer information and matching

[1266] server

[1267] The server retrieves local volunteer demand information from a database or external API, and analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model, thereby generating appropriate recommendations based on the user's emotional state.

[1268] Terminal

[1269] The terminal displays the recommendation list sent from the server to the user.

[1270] User

[1271] The user selects the most suitable volunteer activity based on their emotional state from the presented recommendation list.

[1272] Volunteer booking and training

[1273] User

[1274] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[1275] Terminal

[1276] The terminal transmits the reservation information entered by the user to the server.

[1277] server

[1278] The server receives the reservation information, stores the volunteer activity details in a database, and then sends a notification to the user that the reservation is complete, along with any necessary training materials and video links.

[1279] Terminal

[1280] The terminal displays the provided training materials and links to the user.

[1281] User

[1282] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[1283] Volunteer Reminders and Execution

[1284] server

[1285] The day before the volunteer activity, the server sends a reminder to the user.

[1286] Terminal

[1287] The terminal receives the reminder message and notifies the user.

[1288] User

[1289] Users receive reminders to reconfirm their volunteering dates.

[1290] Sharing and evaluating volunteer experiences

[1291] server

[1292] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[1293] Terminal

[1294] The terminal displays a feedback form to the user and transmits the entered content to the server.

[1295] User

[1296] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1297] server

[1298] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The results of this analysis are stored in a database and reflected in the next volunteer activity recommendation.

[1299] Specific examples

[1300] As a concrete example, suppose a user creates an account and participates in disaster relief activities last week. The user reviews the training materials, receives reminders, and participates in the activities. After completing the activities, the user enters "I was very happy and grateful" in the feedback form. The emotion engine classifies this emotion as "joy" and uses it to recommend activities for the next time. In this way, volunteer activities based on the user's emotions can be recommended, improving the user's experience.

[1301] This system analyzes the user's emotions and recommends volunteer activities based on those emotions, thereby achieving effective volunteer activities with high user satisfaction.

[1302] The processing flow will be explained below.

[1303] Step 1:

[1304] User

[1305] Users access the platform, click "Sign Up," enter the required information such as name, email address, and password, and then press the "Register" button to create an account.

[1306] Step 2:

[1307] Terminal

[1308] The terminal receives the information entered by the user and transmits it to the server.

[1309] Step 3:

[1310] server

[1311] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[1312] Step 4:

[1313] User

[1314] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[1315] Step 5:

[1316] Terminal

[1317] The terminal transmits the profile information entered by the user to the server.

[1318] Step 6:

[1319] server

[1320] The server stores the received profile information in a database. It also uses an emotion engine to analyze the user's emotions when they input their information, and adds the analysis results to the profile information.

[1321] Step 7:

[1322] server

[1323] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model.

[1324] Step 8:

[1325] server

[1326] The server generates a recommendation list based on the analysis results and lists the most suitable volunteer activities taking into account the user's emotional state.

[1327] Step 9:

[1328] Terminal

[1329] The terminal displays the recommendation list sent from the server to the user.

[1330] Step 10:

[1331] User

[1332] The user selects the volunteer activity they would like to participate in from the recommended list and clicks the "Participate" button to confirm their selection.

[1333] Step 11:

[1334] Terminal

[1335] The terminal transmits the user's selection information to the server.

[1336] Step 12:

[1337] server

[1338] The server stores the received selection information in a database, confirms the reservation, records the volunteer activity details, notifies the user of the reservation completion, and provides the necessary training materials and video links to the device.

[1339] Step 13:

[1340] Terminal

[1341] The terminal displays the provided training materials and video links to the user.

[1342] Step 14:

[1343] User

[1344] Users review the training materials and videos provided to them and acquire the necessary knowledge.

[1345] Step 15:

[1346] server

[1347] The day before the volunteer activity, the server sends a reminder to the user.

[1348] Step 16:

[1349] Terminal

[1350] The terminal receives the reminder message and notifies the user.

[1351] Step 17:

[1352] User

[1353] The user checks the reminder and reconfirms the volunteering date.

[1354] Step 18:

[1355] server

[1356] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[1357] Step 19:

[1358] Terminal

[1359] The terminal displays a feedback form to the user and transmits the entered content to the server.

[1360] Step 20:

[1361] User

[1362] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1363] Step 21:

[1364] server

[1365] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The analysis results are stored in a database and reflected in the next volunteer activity recommendation.

[1366] Step 22:

[1367] server

[1368] The next time the server generates recommendations, it will take into account the collected feedback and the results of sentiment analysis to suggest volunteer activities that are more suitable for the user.

[1369] This system analyzes users' emotions and recommends volunteer activities, thereby achieving high user satisfaction and effective volunteer activities.

[1370] Example 2

[1371] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1372] Conventional volunteer activity matching systems have difficulty recommending volunteer activities based on user emotions, which makes it difficult to increase user satisfaction. Furthermore, systems for efficiently collecting user feedback and utilizing it for next-time recommendations are lacking. Furthermore, systems for providing reminders before volunteer activities and necessary training materials are insufficient. To solve these issues, an advanced matching system that includes user emotion analysis is needed.

[1373] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1374] In this invention, the server includes: a means for users to input registration information; a means for saving user profile information in a database; a means including an emotion analysis engine for analyzing user emotions; a means for using a generative AI model to perform matching using volunteer demand information, user profile information, and emotion analysis results; a means for providing the generated volunteer recommendations to the user; a means for users to make reservations for volunteer activities; a means for providing training materials necessary for volunteer activities; a means for collecting feedback on volunteer activities and using it to make recommendations for the next activity; a means for sending a reminder to the user the day before the volunteer activity; and a means for analyzing the user's feedback using the emotion analysis engine and automatically saving the feedback in a database. This makes it possible to recommend optimal volunteer activities based on the user's emotions and increase user satisfaction. Furthermore, by reflecting the feedback analysis in the next recommendation, more effective volunteer activities can be realized.

[1375] "User" refers to an individual who accesses the System and participates in volunteer activities.

[1376] "Registration Information" refers to the necessary data, such as name, email address, and password, entered by a User when registering with the System.

[1377] "Profile Information" refers to detailed data entered by a user, such as volunteer experience, areas of interest, available time, and skills.

[1378] "Database" means a digital storage device for storing user registration and profile information.

[1379] "Emotion analysis engine" refers to an algorithm or software that analyzes a user's emotional state from their input.

[1380] "Volunteer demand information" refers to data on volunteer activities provided by local communities and organizations.

[1381] "Generative AI model" refers to an artificial intelligence model that recommends optimal volunteer activities based on a user's profile information and sentiment analysis results.

[1382] "Recommendations" refers to suggestions for volunteer activities suitable for the user, generated by a generative AI model.

[1383] "Reservation information" refers to detailed data such as the date, time, and location that a user enters to participate in a volunteer activity.

[1384] "Training Materials" means materials and video links that enable Users to acquire the necessary knowledge and skills before participating in a Volunteer Activity.

[1385] "Feedback" refers to information about the volunteer experience and areas for improvement provided by the user after completing the volunteer activity.

[1386] "Reminder" refers to a notification message sent to a user the day before a volunteer activity.

[1387] This invention provides a system that analyzes a user's emotions and recommends volunteer activities based on the results, thereby increasing user satisfaction and enabling effective volunteer activities. This system includes the following processes:

[1388] User registration and profile creation

[1389] User:

[1390] A user accesses the platform and registers, entering the required information (name, email address, password, etc.) to create an account.

[1391] Device:

[1392] The terminal receives the registration information entered by the user and transmits it to the server.

[1393] server:

[1394] The server stores the received information in a database and sends the user a confirmation email of the completed registration.

[1395] User:

[1396] A user logs in and goes to their profile page, where they enter details such as volunteer experience, areas of interest, available time, and skills.

[1397] Device:

[1398] The terminal transmits the profile information entered by the user to the server.

[1399] server:

[1400] The server stores the received profile information in a database and analyzes the user's input emotions using a sentiment analysis engine. Based on the analysis results, it prepares to generate a highly accurate recommendation list.

[1401] Providing volunteer information and matching

[1402] server:

[1403] The server retrieves information about local volunteer demand from a database or external API. It then uses the retrieved information, the user's profile information, and the results of emotion analysis to analyze the information using a generative AI model, generating appropriate recommendations based on the user's emotional state.

[1404] Device:

[1405] The terminal displays the recommendation list sent from the server to the user.

[1406] User:

[1407] The user selects the most suitable volunteer activity from the presented recommendation list according to their emotional state.

[1408] Volunteer booking and training

[1409] User:

[1410] The user clicks the "Participate" button and proceeds to the reservation form, where they enter the required information to confirm the reservation.

[1411] Device:

[1412] The terminal transmits the input reservation information to the server.

[1413] server:

[1414] The server saves the reservation information in a database and sends the user a notification that the reservation is complete, along with any necessary training materials and video links.

[1415] Device:

[1416] The terminal displays the provided training materials and video links to the user.

[1417] User:

[1418] Users review training materials and videos to gain the necessary knowledge.

[1419] Volunteer Reminders and Execution

[1420] server:

[1421] The day before the volunteer activity, the server sends a reminder email to the user.

[1422] Device:

[1423] The terminal receives the reminder message and notifies the user.

[1424] User:

[1425] Users receive reminders to reconfirm their volunteering dates.

[1426] Sharing and evaluating volunteer experiences

[1427] server:

[1428] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[1429] Device:

[1430] The terminal displays the feedback form to the user and transmits the entered content to the server.

[1431] User:

[1432] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1433] server:

[1434] The server analyzes the received feedback using a sentiment analysis engine to determine the user's sentiment. The analysis results are stored in a database and used to improve the quality of future recommendations.

[1435] Specific examples

[1436] As a concrete example, consider a case where a user created an account and participated in disaster relief activities last week. The user reviewed the training materials, received reminders, and participated in the activities. After completing the activities, the user entered "I was very happy and grateful" in the feedback form. The sentiment analysis engine classifies this emotion as "joy" and uses it to recommend activities for the next time. In this way, volunteer activities based on the user's emotions are recommended, improving the user's experience.

[1437] Prompt Sentence Examples

[1438] "Build a system that analyzes users' emotional data and volunteer demand information to recommend appropriate volunteer activities. This system combines an emotion analysis engine and a generative AI model, and takes into account users' emotions such as joy and sadness."

[1439] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1440] Step 1:

[1441] User

[1442] A user accesses the platform and clicks "New Registration." They enter the required information (name, email address, password, etc.) and clicks "Register."

[1443] Input: User's name, email address, and password

[1444] Output: Registration information is sent to the device

[1445] Step 2:

[1446] Terminal

[1447] The terminal transmits the registration information entered by the user to the server.

[1448] Input: User registration information

[1449] Output: Registration information sent to the server

[1450] Step 3:

[1451] server

[1452] The server stores the received registration information in a database and automatically generates and sends a confirmation email to confirm that registration is complete.

[1453] Input: Registration information

[1454] Data processing / data calculation: Saving registration information in a database, generating confirmation emails

[1455] Output: Send confirmation email

[1456] Step 4:

[1457] User

[1458] A user logs in, visits their profile page, and enters detailed profile information (volunteer experience, areas of interest, available hours, skills, etc.).

[1459] Input: Profile information

[1460] Output: Profile information is sent to the device

[1461] Step 5:

[1462] Terminal

[1463] The terminal transmits the profile information entered by the user to the server.

[1464] Input: User profile information

[1465] Output: Profile information sent to the server

[1466] Step 6:

[1467] server

[1468] The server stores the received profile information in a database, launches a sentiment analysis engine to analyze the user's input sentiment, saves the analysis results, and prepares recommendations.

[1469] Input: Profile information

[1470] Data processing / data calculation: saving profile information in a database, analyzing using a sentiment analysis engine, and saving the analysis results

[1471] Output: Save the analysis results

[1472] Step 7:

[1473] server

[1474] The server retrieves local volunteer demand information from a database or external API. Using this information, it analyzes the user's profile information and sentiment analysis results using a generative AI model to generate recommendations.

[1475] Input: Volunteer demand information, user profile information, sentiment analysis results

[1476] Data processing / data calculation: Analysis and recommendation generation using generative AI models

[1477] Output: Generate a recommendation list

[1478] Step 8:

[1479] Terminal

[1480] The terminal displays the recommendation list sent from the server to the user.

[1481] Input: Recommendation list

[1482] Output: Display of recommendation list

[1483] Step 9:

[1484] User

[1485] The user selects the most suitable volunteer activity from the list of recommendations provided and clicks "Participate." Next, the user fills in the necessary information in the reservation form to confirm the reservation.

[1486] Input: Reservation information

[1487] Output: Reservation information is sent to the terminal

[1488] Step 10:

[1489] Terminal

[1490] The terminal transmits the input reservation information to the server.

[1491] Input: Reservation information

[1492] Output: Reservation information sent to the server

[1493] Step 11:

[1494] server

[1495] The server saves the reservation information in a database, notifies the user of the completion of the reservation, and simultaneously generates the necessary training materials and video links and sends them to the terminal.

[1496] Input: Reservation information

[1497] Data processing / data calculation: storing reservation information in a database, generating notifications, generating training materials and links

[1498] Output: Notification of reservation completion, sending of training materials and video links

[1499] Step 12:

[1500] Terminal

[1501] The terminal displays the provided training materials and video links to the user.

[1502] Input: Training materials, video links

[1503] Output: Display of training materials and video links

[1504] Step 13:

[1505] User

[1506] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[1507] Input: Training materials, videos

[1508] Output: Training completed

[1509] Step 14:

[1510] server

[1511] The day before the volunteer activity, the server sends a reminder email to the user.

[1512] Input: Reservation information

[1513] Data processing / data calculation: generating and sending reminder emails

[1514] Output: Send reminder email

[1515] Step 15:

[1516] Terminal

[1517] The terminal receives the reminder message and notifies the user.

[1518] Input: Reminder message

[1519] Output: Reminder message notification

[1520] Step 16:

[1521] User

[1522] Users receive reminders to reconfirm their volunteering dates.

[1523] Enter: Reminder

[1524] Output: Reconfirm date

[1525] Step 17:

[1526] server

[1527] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[1528] Input: Reservation information, activity information

[1529] Data processing / data calculation: feedback form generation and submission

[1530] Output: Feedback form submission

[1531] Step 18:

[1532] Terminal

[1533] The terminal displays the feedback form to the user and transmits the entered content to the server.

[1534] Input: Feedback

[1535] Output: Feedback sent to the server

[1536] Step 19:

[1537] User

[1538] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1539] Input: Feedback

[1540] Output: Feedback sent

[1541] Step 20:

[1542] server

[1543] The server analyzes the received feedback using a sentiment analysis engine to determine the user's emotions, and stores the analysis results in a database to be used to improve the quality of future recommendations.

[1544] Input: Feedback

[1545] Data processing / data calculation: Analysis using the sentiment analysis engine, saving the analysis results

[1546] Output: Save the analysis results

[1547] (Application example 2)

[1548] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1549] Conventional volunteer activity participation systems only match users based on their profile information and volunteer demand information, without considering their emotions. This results in low user satisfaction and compatibility, and often results in users not actually participating in activities. Furthermore, they are unable to fully utilize user feedback, making continuous improvement difficult. There is a need to solve these issues and provide more accurate recommendations that reflect users' emotions.

[1550] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a generative AI model that performs matching using user profile information and volunteer demand information, means for analyzing user emotions and selecting activities, and means for collecting user emotional data in real time when the user visits the store and reflecting this data in recommendations. This makes it possible to recommend appropriate volunteer activities based on the user's emotions.

[1551] "User" refers to an individual who registers with the system and wishes to participate in volunteer activities.

[1552] "Profile Information" refers to basic information such as a user's name, email address, and password, as well as detailed information such as volunteer experience, areas of interest, available time, and skills.

[1553] "Volunteer demand information" refers to information such as the type of volunteer activities desired by local communities and organizations, the skills required, the dates and times of activities, and the location.

[1554] A "generative AI model" is a type of artificial intelligence that analyzes a user's profile information and volunteer demand information to recommend the most appropriate volunteer activities.

[1555] "Means for analyzing emotions" refers to technologies for recognizing and analyzing a user's emotional state in real time, such as emotion engines and emotion analysis algorithms.

[1556] "Recommendations" refers to a list of volunteer activities and services suggested by the system based on the user's attributes and status.

[1557] "Training Materials" means written, video, or other educational materials containing the information necessary for a User to properly perform a particular Volunteer Activity.

[1558] "Feedback" refers to impressions and opinions, including experiences and suggestions for improvement, provided by users after volunteering.

[1559] "Database" refers to a system for storing and managing user information, activity history, feedback, etc.

[1560] "Means for making reservations" refers to a function that allows users to reserve a date, time, and location online to participate in volunteer activities.

[1561] A "reminder" is a message sent to the user the day before an activity to remind them of their plans.

[1562] "Emotional data" refers to information that expresses the emotional state obtained from the user's facial expressions, actions, words, etc. in numerical or categorical form.

[1563] "Means of collecting data in real time" refers to technology that allows users to instantly collect their behavior and emotions on the spot and record them as data.

[1564] The present invention provides a system that streamlines the process for users to participate in volunteer activities and, in particular, provides more accurate recommendations by incorporating sentiment analysis. Specific embodiments are described below.

[1565] 1. User registration and profile creation

[1566] A user first accesses the platform, clicks "New Registration," and enters the required information, such as name, email address, and password. Once the information is entered, the device receives the information and sends it to the server. The server stores the received information in a database and sends the user a confirmation email of successful registration. The user then goes to the profile page and enters detailed information, such as volunteer experience, areas of interest, available time, and skills, which is then sent to the server via the device. The server stores this detailed profile information in a database and prepares it for analyzing the user's emotions.

[1567] 2. Providing volunteer information and matching

[1568] The server retrieves local volunteer demand information from a database or external API, compares this information with the user's profile information, analyzes the user's current emotional state using an emotion engine, and recommends optimal volunteer activities using a generative AI model. The device displays the recommendation list sent from the server to the user.

[1569] 3. Volunteer booking and training

[1570] The user selects the volunteer activity they want from the displayed recommendation list and clicks the "Participate" button to proceed to the reservation form. After entering the required information and confirming the reservation, the device sends this information to the server. The server receives the reservation information, stores the volunteer activity details in a database, and notifies the user that the reservation is complete. It also provides the necessary training materials and video links.

[1571] 4. Volunteer Reminders and Execution

[1572] The day before the volunteer activity, the server sends a reminder message to the user. The device receives this reminder message and notifies the user. The user receives the notification and reconfirms the activity schedule.

[1573] 5. Sharing and evaluating volunteer experiences

[1574] After the volunteer activity is completed, the server generates and sends a feedback form to the user. The terminal displays the feedback form to the user, who then enters their experience and suggestions for improvement and submits it. The server then analyzes the received feedback using an emotion engine to determine the user's emotional state. The results are stored in a database and reflected in the next recommendation.

[1575] Examples of concrete examples and prompts

[1576] Examples:

[1577] A user comes into the store, and the camera recognizes their smile and classifies it as "happy."

[1578] Based on the emotional state of "joy," the system refers to past profile information and purchase history to recommend refreshing products (flowers, aroma goods, etc.).

[1579] The user follows the recommendation, purchases the product, and enters feedback such as "It was very refreshing."

[1580] The next time you visit, we will use this feedback to provide you with even more accurate recommendations.

[1581] Example prompt sentence:

[1582] Recommend the best products and services to users based on the following data:

[1583] 1. User basic information (name, gender, age, interests)

[1584] 2. The user's emotional state (happiness, sadness, anger, etc.)

[1585] 3. User purchase history

[1586] For example, "User name: Tanaka Taro," "Gender: Male," "Age: 35," "Interests: Outdoors, gardening," "Emotional state: Joy," "Purchase history: Outdoor goods, houseplants," etc.

[1587] Prompt: Recommendation if you see a girl smiling: "Recommend a refreshing product, such as flowers or aromatherapy products."

[1588] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1589] Step 1:

[1590] A user accesses the platform and clicks "New Registration." They enter the required information, such as their name, email address, and password. Once the information is entered, the device receives it and sends it to the server. The entered data is sent to the server, which then stores it in a database.

[1591] input:

[1592] User basic information (name, email address, password)

[1593] output:

[1594] User information stored in a database

[1595] Specific behavior:

[1596] The user enters basic information into the on-screen form and clicks the submit button. The device transmits the information to the server, which stores it in a database.

[1597] Step 2:

[1598] The server sends the user a confirmation email to confirm the registration. The user receives the confirmation email and accesses the platform again to log in. After logging in, the user goes to the profile page and enters details such as volunteer experience, areas of interest, available time, skills, etc. The device then sends these details to the server.

[1599] input:

[1600] Detailed user profile information (activity experience, interests, available time, skills)

[1601] output:

[1602] Detailed profile information stored in a database

[1603] Specific behavior:

[1604] The user clicks on the link in the confirmation email and logs back into the platform. They enter their details on the profile page and click the submit button. The device transmits the information to the server, which stores it in a database.

[1605] Step 3:

[1606] The server retrieves information about local volunteer demand from a database or external API. It compares this information with the user's profile information and uses an emotion engine to analyze the user's current emotional state. It then uses a generative AI model to generate recommendations for optimal volunteer activities.

[1607] input:

[1608] User profile information, local volunteer demand information, emotional data

[1609] output:

[1610] Recommendation List

[1611] Specific behavior:

[1612] The server periodically updates and stores local volunteer demand data in a database. The generative AI model analyzes this data and user profiles to generate recommendations for optimal volunteer activities.

[1613] Step 4:

[1614] The terminal displays the recommendation list sent from the server to the user, who then selects a volunteer activity from the displayed recommendation list.

[1615] input:

[1616] Recommendation List

[1617] output:

[1618] User-selected volunteer activities

[1619] Specific behavior:

[1620] The server sends the generated recommendation list to the terminal, which displays it to the user. The user selects a preferred activity and sends the selection information.

[1621] Step 5:

[1622] The user clicks the "Participate" button to proceed to the reservation form. They enter the required information and confirm the reservation. The device sends this information to the server. The server receives the reservation information, stores the volunteer activity details in a database, and sends a notification to the user that the reservation is complete.

[1623] input:

[1624] Reservation information (date, time, location, contact information, etc.)

[1625] output:

[1626] Reservation information stored in the database, reservation completion notification

[1627] Specific behavior:

[1628] The user enters the necessary information into the reservation form and clicks the submit button. The terminal transmits the information to the server, which stores it in a database and sends a confirmation email.

[1629] Step 6:

[1630] The server provides the user with the necessary training materials and video links, and the terminal displays these training materials to the user, who then reviews them and acquires the necessary knowledge.

[1631] input:

[1632] Training materials, video links

[1633] output:

[1634] User learning progress

[1635] Specific behavior:

[1636] The server generates a training material link and sends it to the terminal, which displays it to the user, who then checks the material.

[1637] Step 7:

[1638] The server sends a reminder message to the user the day before the volunteer activity. The device receives the reminder message and notifies the user. The user receives the notification and reconfirms the activity date.

[1639] input:

[1640] Reminder Information

[1641] output:

[1642] Reminders

[1643] Specific behavior:

[1644] The server generates a reminder message at the set date and time and sends it to the device, which then displays the reminder to the user.

[1645] Step 8:

[1646] After the volunteer activity is completed, the server generates and sends a feedback form to the user. The terminal displays the feedback form to the user, who then enters their experience and suggestions for improvement and submits it. The server then analyzes the received feedback using an emotion engine to determine the user's emotional state. The results are stored in a database and reflected in the next recommendation.

[1647] input:

[1648] Feedback content

[1649] output:

[1650] Analyzed emotion data, feedback stored in database

[1651] Specific behavior:

[1652] The server generates a feedback form and sends it to the device. The user enters their experience and suggestions for improvement into the form and clicks the submit button. The device transmits the information to the server, which analyzes it using an emotion engine and stores it in a database.

[1653] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1654] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1655] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1656] [Third embodiment]

[1657] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1658] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1659] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1660] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1661] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1662] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1663] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1664] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1665] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1666] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1667] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1668] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1669] This invention is a system for efficiently recruiting and applying for volunteer activities, and is implemented as follows.

[1670] User registration and profile creation

[1671] User

[1672] Users first access the platform and create a new account.

[1673] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[1674] After logging in, users are directed to a profile page where they can enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[1675] Terminal

[1676] The input information is received and sent to the server.

[1677] server

[1678] The received information is stored in a database.

[1679] Send a confirmation email to confirm registration and prepare to recommend volunteer activities suitable for the user based on their profile information.

[1680] Providing volunteer information and matching

[1681] server

[1682] Get local volunteer demand information from a database or external API.

[1683] The AI ​​model analyzes user profile information and volunteer demand information to generate appropriate recommendations.

[1684] Terminal

[1685] The recommendation list sent from the server is displayed to the user.

[1686] User

[1687] Select the volunteer activity you would like to participate in from the list of recommendations provided.

[1688] Volunteer booking and training

[1689] User

[1690] After selecting your volunteer activity, click the "Participate" button to proceed to the reservation form.

[1691] Enter the required information and confirm your reservation.

[1692] Terminal

[1693] The user's selection information is received and the information required for the reservation form is sent to the server.

[1694] server

[1695] Confirm the booking and save the volunteer activity details in a database.

[1696] A confirmation of the booking will be sent back to the user, along with any training materials or video links required for the relevant volunteer activity.

[1697] Terminal

[1698] Display training materials and links to users.

[1699] User

[1700] Review the training materials provided and acquire the necessary knowledge.

[1701] Volunteer Reminders and Execution

[1702] server

[1703] Send users a reminder the day before their volunteer activity.

[1704] Terminal

[1705] Receive reminder messages and notify users.

[1706] User

[1707] Receive reminders and reconfirm your volunteering dates.

[1708] Sharing and evaluating volunteer experiences

[1709] server

[1710] After the volunteer activity is completed, a feedback form is generated and sent to the user.

[1711] Terminal

[1712] A feedback form is displayed to the user and the entered information is sent to the server.

[1713] User

[1714] Fill out the feedback form and submit it to let us know your experience with the activity and any suggestions for improvement.

[1715] server

[1716] The received feedback is analyzed and stored in a database.

[1717] This will be used to recommend the next volunteer activity, allowing for more precise matching.

[1718] Specific examples

[1719] As a specific example, if user "Ichiro Suzuki" creates an account and enters in his profile that he has emergency medical skills, the server will recommend disaster relief activities taking place this weekend in the surrounding area. Then, it will prioritize activities that "can utilize his emergency medical skills." Ichiro Suzuki selects and reserves the activity, learning the provided training materials. He receives a reminder the day before the activity, and after completing the volunteer activity, he can enter feedback that will be reflected in the next activity.

[1720] The system recommends volunteer activities that best suit the user's needs and skills, making volunteering faster and more efficient.

[1721] The processing flow will be explained below.

[1722] Step 1:

[1723] User

[1724] The user accesses the platform, clicks "New Registration," enters the required information such as name, email address, and password, and presses the "Register" button.

[1725] Step 2:

[1726] Terminal

[1727] The terminal receives the information entered by the user and transmits it to the server.

[1728] Step 3:

[1729] server

[1730] The server stores the received information in a database and sends a confirmation email to the user once the information has been saved.

[1731] Step 4:

[1732] User

[1733] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[1734] Step 5:

[1735] Terminal

[1736] The terminal transmits the profile information entered by the user to the server.

[1737] Step 6:

[1738] server

[1739] The server stores the received profile information in a database.

[1740] Step 7:

[1741] server

[1742] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it uses a generative AI model to analyze the user's profile and volunteer demand information and generate a recommendation list.

[1743] Step 8:

[1744] Terminal

[1745] The terminal displays the recommendation list received from the server to the user.

[1746] Step 9:

[1747] User

[1748] The user selects the volunteer activity they wish to participate in from the displayed list of recommendations.

[1749] Step 10:

[1750] User

[1751] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[1752] Step 11:

[1753] Terminal

[1754] The terminal transmits the reservation information entered by the user to the server.

[1755] Step 12:

[1756] server

[1757] The server receives the reservation information, stores the volunteer activity details in a database, and then sends the user a notification that the reservation is complete, along with any necessary training materials and video links.

[1758] Step 13:

[1759] Terminal

[1760] The terminal displays the provided training materials and links to the user.

[1761] Step 14:

[1762] User

[1763] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[1764] Step 15:

[1765] server

[1766] The day before the volunteer activity, the server sends a reminder to the user.

[1767] Step 16:

[1768] Terminal

[1769] The terminal receives the reminder message and notifies the user.

[1770] Step 17:

[1771] User

[1772] Users receive reminders to reconfirm their volunteering dates.

[1773] Step 18:

[1774] server

[1775] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[1776] Step 19:

[1777] Terminal

[1778] The terminal displays a feedback form to the user and transmits the entered content to the server.

[1779] Step 20:

[1780] User

[1781] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1782] Step 21:

[1783] server

[1784] The server analyzes the received feedback and stores it in a database. Based on the analysis results, the server will use them to recommend the next volunteer activity.

[1785] Through this series of steps, users can efficiently participate in volunteer activities and use the experience gained from the activities for future use.

[1786] Example 1

[1787] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1788] In conventional volunteer recruitment systems, it is difficult for users to find volunteer activities that best suit their skills and interests, and the application process is cumbersome and inefficient. Furthermore, the management of activity bookings, training, reminders, and feedback is not centralized, and an improvement in the user experience is required.

[1789] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1790] In this invention, the server includes means for a user to input registration information, means for inputting basic information and detailed profile information of the user, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for sending a registration completion confirmation email to the user, means for obtaining local volunteer demand information from a database or an external API, means for analyzing the user's profile information and volunteer demand information with an AI model, means for providing the generated volunteer recommendations to the user, means for the user to make a reservation to participate in a volunteer activity, means for sending a reservation completion confirmation email and training materials to the user, and means for collecting feedback on the volunteer activity and using it for next recommendations. This makes it possible to efficiently find volunteer activities that best suit a user's skills and interests, simplify the application process, and centralize management of training, reminders, and feedback.

[1791] "User" refers to an individual or group that registers with the system to participate in volunteer activities and inputs and operates various information.

[1792] "Registration Information" refers to basic personal information such as name, email address, and password that a User enters into the System.

[1793] "Profile Information" refers to detailed information that a User enters into the system, such as volunteer experience, areas of interest, available time, and skills.

[1794] "Server" refers to a computer system that receives, processes, and stores information sent by users in a database.

[1795] "Database" refers to a data storage system for storing user data, including registration information, profile information, volunteer demand information, and feedback information.

[1796] "Generative AI Model" refers to an artificial intelligence model used to analyze a user's profile information and volunteer demand information and generate appropriate recommendations.

[1797] "Recommendations" refers to a list of volunteer activities recommended to a user by a generative AI model.

[1798] "Training Materials" means materials and video links that a User must study before participating in a Volunteer Activity.

[1799] "Feedback" refers to the user's experience with the activity and evaluation of areas for improvement that they enter after completing the volunteer activity.

[1800] "Reminder" refers to a notification message sent to a user immediately before a volunteer activity.

[1801] "External API" refers to an application programming interface used to obtain volunteer demand information from data sources external to the System.

[1802] The present invention is a system for efficiently recruiting and applying for volunteer activities. A specific embodiment of this system will be described below.

[1803] User registration and profile creation

[1804] User

[1805] Users first access the platform using a web browser or mobile application and are redirected to a page to create a new account.

[1806] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[1807] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[1808] Terminal

[1809] The terminal transmits the basic information and profile information entered by the user to the server.

[1810] server

[1811] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[1812] Providing volunteer information and matching

[1813] server

[1814] The server retrieves local volunteer demand information from an internal database or an external API.

[1815] The server analyzes the user's profile information and the acquired volunteer demand information using a generative AI model (e.g., using TensorFlow or PyTorch) to generate a list of recommended appropriate volunteer activities.

[1816] Terminal

[1817] The terminal displays the recommendation list received from the server to the user.

[1818] User

[1819] Users select the volunteer activities they would like to participate in from the recommendation list.

[1820] Volunteer booking and training

[1821] User

[1822] Users select the volunteer activity they wish to participate in and click the "Participate" button. They then fill in the necessary information in the reservation form to confirm their reservation.

[1823] Terminal

[1824] The terminal transmits the user's reservation information to the server.

[1825] server

[1826] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials (e.g., PDFs or video links) required for the volunteer activity.

[1827] Terminal

[1828] The terminal displays training materials and video links to the user.

[1829] User

[1830] The user reviews the provided training materials and acquires the necessary knowledge.

[1831] Volunteer Reminders and Execution

[1832] server

[1833] The server sends a reminder to the user the day before the volunteer activity.

[1834] Terminal

[1835] The terminal receives the reminder message and notifies the user.

[1836] User

[1837] Users receive reminders to reconfirm their volunteering dates.

[1838] Sharing and evaluating volunteer experiences

[1839] server

[1840] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[1841] Terminal

[1842] The terminal displays a feedback form to the user and transmits the entered content to the server.

[1843] User

[1844] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1845] server

[1846] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[1847] Examples of concrete examples and prompts

[1848] As a specific example, consider the case where user "A" has emergency medical skills. The server retrieves local volunteer information from a database or external API, analyzes it using a generative AI model, and recommends the most suitable volunteer activity for "A" (for example, disaster relief activities).

[1849] An example of a prompt is as follows:

[1850] "How do users select a volunteer activity and complete a booking?"

[1851] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1852] Step 1:

[1853] User

[1854] First, users access the platform using a web browser or mobile application, and are redirected to a new account creation page where they enter basic information such as their name, email address, and password, and then click the "Register" button to create an account.

[1855] Input: Name, Email Address, Password

[1856] Output: Registration request

[1857] Specific operation: The browser will redirect to the account creation page and display the input form. When the user presses the "Register" button, the input information will be sent to the server.

[1858] Step 2:

[1859] Terminal

[1860] The terminal sends the basic information entered by the user to the server.

[1861] Input: Basic information entered by the user

[1862] Output: Registration information sent to the server

[1863] Specific operation: The terminal sends an HTTP POST request to the server.

[1864] Step 3:

[1865] server

[1866] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[1867] Input: Registration information sent to the server

[1868] Output: User registration information stored in the database, confirmation email

[1869] Specific operation: The server creates a record in the database and sends a confirmation email using the mail server.

[1870] Step 4:

[1871] User

[1872] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[1873] Input: Login information, profile information

[1874] Output: Detailed profile information

[1875] Specific operation: The browser will redirect to the profile page, and an input form will be displayed. The user will enter their information.

[1876] Step 5:

[1877] Terminal

[1878] The terminal transmits the detailed profile information entered by the user to the server.

[1879] Input: Detailed profile information

[1880] Output: Profile information sent to the server

[1881] Specific operation: The terminal sends an HTTP POST request to the server.

[1882] Step 6:

[1883] server

[1884] The server stores the received profile information in a database and retrieves local volunteer demand information from an internal database or an external API.

[1885] Input: Profile information sent to the server

[1886] Output: Profile information stored in the database, local volunteer demand information

[1887] Specific operation: The server creates a record in the database and sends an API request to retrieve volunteer demand information.

[1888] Step 7:

[1889] server

[1890] The server analyzes the user's profile information and volunteer demand information using a generative AI model to generate appropriate volunteer recommendations.

[1891] Input: User profile information, volunteer demand information

[1892] Output: Volunteer recommendation list

[1893] Specific operations: Run analysis algorithms using generative AI models (such as TensorFlow or PyTorch).

[1894] Step 8:

[1895] Terminal

[1896] The terminal displays the recommendation list received from the server to the user.

[1897] Input: Volunteer Recommendation List

[1898] Output: The recommendation list shown to the user

[1899] Specific operation: The device receives the HTTP response and renders the recommendation list in the browser.

[1900] Step 9:

[1901] User

[1902] Users select the volunteer activity they want to participate in from the recommendation list and click the "Participate" button. Then, they fill in the necessary information in the reservation form to confirm their reservation.

[1903] Input: Recommendation list, reservation information

[1904] Output: Booking request

[1905] Specific operation: A click event transitions to the next form page, and after completing the input, press the "Confirm" button.

[1906] Step 10:

[1907] Terminal

[1908] The terminal transmits the user's reservation information to the server.

[1909] Input: Reservation information

[1910] Output: Reservation information sent to the server

[1911] Specific operation: The terminal sends an HTTP POST request to the server.

[1912] Step 11:

[1913] server

[1914] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials required for the volunteer activity.

[1915] Input: Reservation information

[1916] Output: Booking information stored in a database, confirmation emails, training materials

[1917] What happens: The server saves the reservation information in a database and uses a mail server to send a confirmation email containing the training materials.

[1918] Step 12:

[1919] Terminal

[1920] The terminal displays training materials and video links to the user.

[1921] Input: Training materials

[1922] Output: The training material displayed to the user

[1923] What happens: The browser or app renders the material and displays it to the user.

[1924] Step 13:

[1925] server

[1926] The server sends a reminder to the user the day before the volunteer activity.

[1927] Input: Date information for the relevant volunteer activity

[1928] Output: Reminder message

[1929] Specific operation: The server uses the mail server to send the reminder message.

[1930] Step 14:

[1931] Terminal

[1932] The terminal receives the reminder message and notifies the user.

[1933] Input: Reminder message

[1934] Output: Reminders notified to the user

[1935] Specific behavior: The device displays a notification and alerts the user.

[1936] Step 15:

[1937] server

[1938] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[1939] Input: Volunteer activity completion information

[1940] Output: Feedback form submission

[1941] Specific operation: The server sends the feedback form using the mail server.

[1942] Step 16:

[1943] Terminal

[1944] The terminal displays a feedback form to the user and transmits the entered content to the server.

[1945] Input: Feedback Form

[1946] Output: The input feedback

[1947] What happens: The browser or app displays a feedback form, which the user fills out and then submits to the server.

[1948] Step 17:

[1949] server

[1950] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[1951] Input: Feedback

[1952] Output: Parsed feedback data, feedback information stored in a database

[1953] What happens: The analysis algorithm processes the feedback and creates a record in the database.

[1954] (Application example 1)

[1955] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1956] Conventional volunteer participation systems often make it difficult for users to find activities that match their skills and interests, resulting in inappropriate matching. Additionally, users are often unable to fully prepare for volunteer activities due to insufficient training materials and videos. Furthermore, because feedback is collected and analyzed manually, it is difficult to effectively reflect this feedback in future recommendations.

[1957] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1958] In this invention, the server includes a means for a user to input registration information, a means for using a generative AI model that performs matching using the user's profile information and volunteer demand information, a means for providing the generated volunteer recommendations to the user, a means for the user to make a reservation to participate in a volunteer activity, a means further including a means for providing training materials and videos necessary for the volunteer activity, a means for collecting feedback on the volunteer activity and using it for the next recommendation, a means for viewing the training video using a head-mounted display, and a means for sending a reminder to the user the day before the volunteer activity. This allows users to easily find the most suitable volunteer activity based on their skills and interests, allowing them to participate in the activity with sufficient preparation, and allows feedback to be effectively collected and analyzed to be reflected in the next recommendation.

[1959] "User" refers to an individual who registers with the System and provides profile information to participate in volunteer activities.

[1960] "Means for entering registration information" refers to the interface through which a user accesses the system and enters basic information such as name, email address, and password.

[1961] "Profile information" refers to information that indicates the user's characteristics and background, such as the user's volunteer experience, areas of interest, available time, and skills.

[1962] "Volunteer demand information" refers to information about the types and content of volunteers needed in specific regions or organizations.

[1963] A "generative AI model" refers to an artificial intelligence model that analyzes a user's profile information and volunteer demand information to recommend the most suitable volunteer activities for the user.

[1964] "Recommendations" refers to potential volunteer activities suggested to users by the generative AI model.

[1965] "Means for making reservations" refers to an interface that allows a user to reserve a date, time, and location for a selected volunteer activity.

[1966] "Training materials and videos" refers to written and visual content that helps users learn the knowledge and skills necessary to participate in volunteer activities.

[1967] "Head-mounted display" refers to a display device used by a user to view training videos with a 360-degree field of view.

[1968] "Reminder" refers to a notification message sent to a user the day before a volunteer activity.

[1969] "Feedback" refers to the user's experience with the activity and their opinions on areas for improvement provided after completing the volunteer activity.

[1970] In the present invention, the following means and processes are used to provide a system that allows users to efficiently participate in volunteer activities.

[1971] 1. User registration and profile creation

[1972] A user accesses the system and creates a new account. The user enters basic information such as name, email address, and password, and presses the "Register" button, which sends the information to the server.

[1973] The server receives this and stores it in a database. After the user logs in, they go to their profile page and enter detailed profile information such as their volunteer experience, areas of interest, available time, skills, etc. This is also sent to the server and stored in the database.

[1974] 2. Providing volunteer information and matching

[1975] The server retrieves local volunteer demand information from a database or external API. Using a generative AI model, it analyzes the user's profile information and volunteer demand information to generate appropriate recommendations. These are sent to the user's device and displayed as a recommendation list.

[1976] Specifically, the following prompt sentences are input into the generative AI model, which then recommends the most suitable volunteer activity for the user:

[1977] User Profile:

[1978] Name: Ichiro Suzuki

[1979] Volunteer experience: Emergency medical technician

[1980] Area of ​​interest: Disaster relief

[1981] Available times: Weekends

[1982] Volunteer activities offered:

[1983] 1. Disaster support activities A

[1984] 2. Disaster relief activities B

[1985] 3. Community cleanup activities

[1986] Please choose one activity to recommend.

[1987] 3. Volunteer booking and training

[1988] The user selects the volunteer activity they wish to participate in from the recommended list. After making their selection, they click the "Participate" button and proceed to the reservation form. They then enter the required information and confirm their reservation.

[1989] The server receives the request, confirms the reservation, stores the volunteer activity details in a database, and returns a confirmation of the reservation to the user along with relevant training materials and video links that can be viewed on the user's smartphone or head-mounted display.

[1990] 4. Volunteer Reminders and Execution

[1991] The server sends a reminder to the user the day before the volunteer activity.

[1992] The terminal receives the reminder message and notifies the user.

[1993] The user checks this and reconfirms the schedule for volunteer activities.

[1994] 5. Sharing and evaluating volunteer experiences

[1995] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[1996] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[1997] The server receives this, stores it in a database, and uses it to recommend volunteer activities for the next time.

[1998] The system configuration utilizes the following hardware and software:

[1999] Smartphone: iOS or Android compatible.

[2000] Head-mounted display: VR compatible display.

[2001] Server side: Uses AWS (Amazon Web Services).

[2002] AI model: Use Amazon SageMaker, etc.

[2003] Database: MySQL or PostgreSQL.

[2004] This allows users to easily find the best volunteer activities based on their skills and interests, allows them to participate in activities well prepared, and effectively collect and analyze feedback to reflect in future recommendations.

[2005] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2006] Step 1:

[2007] The user enters registration information

[2008] input:

[2009] The user enters basic information such as name, email address, and password.

[2010] Data processing / calculation:

[2011] The terminal organizes the input information and sends it to the server.

[2012] output:

[2013] The server sends a confirmation email to the user and stores the information in a database.

[2014] Step 2:

[2015] User enters profile information

[2016] input:

[2017] Users enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2018] Data processing / calculation:

[2019] The terminal organizes the entered information and sends it to the server.

[2020] output:

[2021] The server saves the profile information to a database and notifies the user that the information has been saved.

[2022] Step 3:

[2023] Acquisition and analysis of volunteer demand information

[2024] input:

[2025] The server retrieves local volunteer demand information from a database or external API.

[2026] Data processing / calculation:

[2027] The server analyzes the acquired volunteer demand information and user profile information, and generates appropriate recommendations using a generative AI model.

[2028] output:

[2029] Send the recommendation list to the user.

[2030] Step 4:

[2031] User selects volunteer activity and makes reservation

[2032] input:

[2033] The user selects the volunteer activity they want to participate in from the recommended list and clicks "Participate." They then enter the required information and confirm their reservation.

[2034] Data processing / calculation:

[2035] The terminal transmits the input information to the server.

[2036] output:

[2037] The server stores the reservation information in a database and sends the user details, training materials and video links.

[2038] Step 5:

[2039] Watch training videos required for volunteer work

[2040] input:

[2041] The user receives the training materials and video links sent to them and begins watching them.

[2042] Data processing / calculation:

[2043] The device plays the video link on the head-mounted display or smartphone.

[2044] output:

[2045] Users watch training videos and acquire the necessary knowledge.

[2046] Step 6:

[2047] Volunteer Reminders

[2048] input:

[2049] The server sets a reminder the day before the volunteer activity.

[2050] Data processing / calculation:

[2051] The server generates a reminder message and sends it to the terminal.

[2052] output:

[2053] The terminal notifies the user of the reminder message.

[2054] Step 7:

[2055] Collecting feedback after volunteering

[2056] input:

[2057] After completing the activity, users enter their experience and suggestions for improvement in a feedback form submitted.

[2058] Data processing / calculation:

[2059] The device sends feedback information to the server, which analyzes it and stores it in a database.

[2060] output:

[2061] The server will incorporate the feedback into its next recommendations.

[2062] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2063] This invention is a system for efficiently recruiting and applying for volunteer activities, and in particular, it combines a function for recognizing a user's emotions and selecting activities. It is implemented through the following specific process.

[2064] User registration and profile creation

[2065] User

[2066] First, users access the platform and click "Sign Up." They then enter the required information, such as their name, email address, and password, and press the "Register" button to create an account.

[2067] Terminal

[2068] The terminal receives the information entered by the user and transmits it to the server.

[2069] server

[2070] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[2071] User

[2072] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2073] Terminal

[2074] The terminal transmits the profile information entered by the user to the server.

[2075] server

[2076] The server stores the received profile information in a database and uses an emotion engine to analyze the emotions expressed by the user when they input their information. Based on the analysis results, the server prepares to generate a more accurate recommendation list.

[2077] Providing volunteer information and matching

[2078] server

[2079] The server retrieves local volunteer demand information from a database or external API, and analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model, thereby generating appropriate recommendations based on the user's emotional state.

[2080] Terminal

[2081] The terminal displays the recommendation list sent from the server to the user.

[2082] User

[2083] The user selects the most suitable volunteer activity based on their emotional state from the presented recommendation list.

[2084] Volunteer booking and training

[2085] User

[2086] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[2087] Terminal

[2088] The terminal transmits the reservation information entered by the user to the server.

[2089] server

[2090] The server receives the reservation information, stores the volunteer activity details in a database, and then sends a notification to the user that the reservation is complete, along with any necessary training materials and video links.

[2091] Terminal

[2092] The terminal displays the provided training materials and links to the user.

[2093] User

[2094] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[2095] Volunteer Reminders and Execution

[2096] server

[2097] The day before the volunteer activity, the server sends a reminder to the user.

[2098] Terminal

[2099] The terminal receives the reminder message and notifies the user.

[2100] User

[2101] Users receive reminders to reconfirm their volunteering dates.

[2102] Sharing and evaluating volunteer experiences

[2103] server

[2104] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2105] Terminal

[2106] The terminal displays a feedback form to the user and transmits the entered content to the server.

[2107] User

[2108] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2109] server

[2110] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The results of this analysis are stored in a database and reflected in the next volunteer activity recommendation.

[2111] Specific examples

[2112] As a concrete example, suppose a user creates an account and participates in disaster relief activities last week. The user reviews the training materials, receives reminders, and participates in the activities. After completing the activities, the user enters "I was very happy and grateful" in the feedback form. The emotion engine classifies this emotion as "joy" and uses it to recommend activities for the next time. In this way, volunteer activities based on the user's emotions can be recommended, improving the user's experience.

[2113] This system analyzes the user's emotions and recommends volunteer activities based on those emotions, thereby achieving effective volunteer activities with high user satisfaction.

[2114] The processing flow will be explained below.

[2115] Step 1:

[2116] User

[2117] Users access the platform, click "Sign Up," enter the required information such as name, email address, and password, and then press the "Register" button to create an account.

[2118] Step 2:

[2119] Terminal

[2120] The terminal receives the information entered by the user and transmits it to the server.

[2121] Step 3:

[2122] server

[2123] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[2124] Step 4:

[2125] User

[2126] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2127] Step 5:

[2128] Terminal

[2129] The terminal transmits the profile information entered by the user to the server.

[2130] Step 6:

[2131] server

[2132] The server stores the received profile information in a database. It also uses an emotion engine to analyze the user's emotions when they input their information, and adds the analysis results to the profile information.

[2133] Step 7:

[2134] server

[2135] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model.

[2136] Step 8:

[2137] server

[2138] The server generates a recommendation list based on the analysis results and lists the most suitable volunteer activities taking into account the user's emotional state.

[2139] Step 9:

[2140] Terminal

[2141] The terminal displays the recommendation list sent from the server to the user.

[2142] Step 10:

[2143] User

[2144] The user selects the volunteer activity they would like to participate in from the recommended list and clicks the "Participate" button to confirm their selection.

[2145] Step 11:

[2146] Terminal

[2147] The terminal transmits the user's selection information to the server.

[2148] Step 12:

[2149] server

[2150] The server stores the received selection information in a database, confirms the reservation, records the volunteer activity details, notifies the user of the reservation completion, and provides the necessary training materials and video links to the device.

[2151] Step 13:

[2152] Terminal

[2153] The terminal displays the provided training materials and video links to the user.

[2154] Step 14:

[2155] User

[2156] Users review the training materials and videos provided to them and acquire the necessary knowledge.

[2157] Step 15:

[2158] server

[2159] The day before the volunteer activity, the server sends a reminder to the user.

[2160] Step 16:

[2161] Terminal

[2162] The terminal receives the reminder message and notifies the user.

[2163] Step 17:

[2164] User

[2165] The user checks the reminder and reconfirms the volunteering date.

[2166] Step 18:

[2167] server

[2168] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2169] Step 19:

[2170] Terminal

[2171] The terminal displays a feedback form to the user and transmits the entered content to the server.

[2172] Step 20:

[2173] User

[2174] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2175] Step 21:

[2176] server

[2177] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The analysis results are stored in a database and reflected in the next volunteer activity recommendation.

[2178] Step 22:

[2179] server

[2180] The next time the server generates recommendations, it will take into account the collected feedback and the results of sentiment analysis to suggest volunteer activities that are more suitable for the user.

[2181] This system analyzes users' emotions and recommends volunteer activities, thereby achieving high user satisfaction and effective volunteer activities.

[2182] Example 2

[2183] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2184] Conventional volunteer activity matching systems have difficulty recommending volunteer activities based on user emotions, which makes it difficult to increase user satisfaction. Furthermore, systems for efficiently collecting user feedback and utilizing it for next-time recommendations are lacking. Furthermore, systems for providing reminders before volunteer activities and necessary training materials are insufficient. To solve these issues, an advanced matching system that includes user emotion analysis is needed.

[2185] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2186] In this invention, the server includes: a means for users to input registration information; a means for saving user profile information in a database; a means including an emotion analysis engine for analyzing user emotions; a means for using a generative AI model to perform matching using volunteer demand information, user profile information, and emotion analysis results; a means for providing the generated volunteer recommendations to the user; a means for users to make reservations for volunteer activities; a means for providing training materials necessary for volunteer activities; a means for collecting feedback on volunteer activities and using it to make recommendations for the next activity; a means for sending a reminder to the user the day before the volunteer activity; and a means for analyzing the user's feedback using the emotion analysis engine and automatically saving the feedback in a database. This makes it possible to recommend optimal volunteer activities based on the user's emotions and increase user satisfaction. Furthermore, by reflecting the feedback analysis in the next recommendation, more effective volunteer activities can be realized.

[2187] "User" refers to an individual who accesses the System and participates in volunteer activities.

[2188] "Registration Information" refers to the necessary data, such as name, email address, and password, entered by a User when registering with the System.

[2189] "Profile Information" refers to detailed data entered by a user, such as volunteer experience, areas of interest, available time, and skills.

[2190] "Database" means a digital storage device for storing user registration and profile information.

[2191] "Emotion analysis engine" refers to an algorithm or software that analyzes a user's emotional state from their input.

[2192] "Volunteer demand information" refers to data on volunteer activities provided by local communities and organizations.

[2193] "Generative AI model" refers to an artificial intelligence model that recommends optimal volunteer activities based on a user's profile information and sentiment analysis results.

[2194] "Recommendations" refers to suggestions for volunteer activities suitable for the user, generated by a generative AI model.

[2195] "Reservation information" refers to detailed data such as the date, time, and location that a user enters to participate in a volunteer activity.

[2196] "Training Materials" means materials and video links that enable Users to acquire the necessary knowledge and skills before participating in a Volunteer Activity.

[2197] "Feedback" refers to information about the volunteer experience and areas for improvement provided by the user after completing the volunteer activity.

[2198] "Reminder" refers to a notification message sent to a user the day before a volunteer activity.

[2199] This invention provides a system that analyzes a user's emotions and recommends volunteer activities based on the results, thereby increasing user satisfaction and enabling effective volunteer activities. This system includes the following processes:

[2200] User registration and profile creation

[2201] User:

[2202] A user accesses the platform and registers, entering the required information (name, email address, password, etc.) to create an account.

[2203] Device:

[2204] The terminal receives the registration information entered by the user and transmits it to the server.

[2205] server:

[2206] The server stores the received information in a database and sends the user a confirmation email of the completed registration.

[2207] User:

[2208] A user logs in and goes to their profile page, where they enter details such as volunteer experience, areas of interest, available time, and skills.

[2209] Device:

[2210] The terminal transmits the profile information entered by the user to the server.

[2211] server:

[2212] The server stores the received profile information in a database and analyzes the user's input emotions using a sentiment analysis engine. Based on the analysis results, it prepares to generate a highly accurate recommendation list.

[2213] Providing volunteer information and matching

[2214] server:

[2215] The server retrieves information about local volunteer demand from a database or external API. It then uses the retrieved information, the user's profile information, and the results of emotion analysis to analyze the information using a generative AI model, generating appropriate recommendations based on the user's emotional state.

[2216] Device:

[2217] The terminal displays the recommendation list sent from the server to the user.

[2218] User:

[2219] The user selects the most suitable volunteer activity from the presented recommendation list according to their emotional state.

[2220] Volunteer booking and training

[2221] User:

[2222] The user clicks the "Participate" button and proceeds to the reservation form, where they enter the required information to confirm the reservation.

[2223] Device:

[2224] The terminal transmits the input reservation information to the server.

[2225] server:

[2226] The server saves the reservation information in a database and sends the user a notification that the reservation is complete, along with any necessary training materials and video links.

[2227] Device:

[2228] The terminal displays the provided training materials and video links to the user.

[2229] User:

[2230] Users review training materials and videos to gain the necessary knowledge.

[2231] Volunteer Reminders and Execution

[2232] server:

[2233] The day before the volunteer activity, the server sends a reminder email to the user.

[2234] Device:

[2235] The terminal receives the reminder message and notifies the user.

[2236] User:

[2237] Users receive reminders to reconfirm their volunteering dates.

[2238] Sharing and evaluating volunteer experiences

[2239] server:

[2240] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2241] Device:

[2242] The terminal displays the feedback form to the user and transmits the entered content to the server.

[2243] User:

[2244] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2245] server:

[2246] The server analyzes the received feedback using a sentiment analysis engine to determine the user's sentiment. The analysis results are stored in a database and used to improve the quality of future recommendations.

[2247] Specific examples

[2248] As a concrete example, consider a case where a user created an account and participated in disaster relief activities last week. The user reviewed the training materials, received reminders, and participated in the activities. After completing the activities, the user entered "I was very happy and grateful" in the feedback form. The sentiment analysis engine classifies this emotion as "joy" and uses it to recommend activities for the next time. In this way, volunteer activities based on the user's emotions are recommended, improving the user's experience.

[2249] Prompt Sentence Examples

[2250] "Build a system that analyzes users' emotional data and volunteer demand information to recommend appropriate volunteer activities. This system combines an emotion analysis engine and a generative AI model, and takes into account users' emotions such as joy and sadness."

[2251] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2252] Step 1:

[2253] User

[2254] A user accesses the platform and clicks "New Registration." They enter the required information (name, email address, password, etc.) and clicks "Register."

[2255] Input: User's name, email address, and password

[2256] Output: Registration information is sent to the device

[2257] Step 2:

[2258] Terminal

[2259] The terminal transmits the registration information entered by the user to the server.

[2260] Input: User registration information

[2261] Output: Registration information sent to the server

[2262] Step 3:

[2263] server

[2264] The server stores the received registration information in a database and automatically generates and sends a confirmation email to confirm that registration is complete.

[2265] Input: Registration information

[2266] Data processing / data calculation: Saving registration information in a database, generating confirmation emails

[2267] Output: Send confirmation email

[2268] Step 4:

[2269] User

[2270] A user logs in, visits their profile page, and enters detailed profile information (volunteer experience, areas of interest, available hours, skills, etc.).

[2271] Input: Profile information

[2272] Output: Profile information is sent to the device

[2273] Step 5:

[2274] Terminal

[2275] The terminal transmits the profile information entered by the user to the server.

[2276] Input: User profile information

[2277] Output: Profile information sent to the server

[2278] Step 6:

[2279] server

[2280] The server stores the received profile information in a database, launches a sentiment analysis engine to analyze the user's input sentiment, saves the analysis results, and prepares recommendations.

[2281] Input: Profile information

[2282] Data processing / data calculation: saving profile information in a database, analyzing using a sentiment analysis engine, and saving the analysis results

[2283] Output: Save the analysis results

[2284] Step 7:

[2285] server

[2286] The server retrieves local volunteer demand information from a database or external API. Using this information, it analyzes the user's profile information and sentiment analysis results using a generative AI model to generate recommendations.

[2287] Input: Volunteer demand information, user profile information, sentiment analysis results

[2288] Data processing / data calculation: Analysis and recommendation generation using generative AI models

[2289] Output: Generate a recommendation list

[2290] Step 8:

[2291] Terminal

[2292] The terminal displays the recommendation list sent from the server to the user.

[2293] Input: Recommendation list

[2294] Output: Display of recommendation list

[2295] Step 9:

[2296] User

[2297] The user selects the most suitable volunteer activity from the list of recommendations provided and clicks "Participate." Next, the user fills in the necessary information in the reservation form to confirm the reservation.

[2298] Input: Reservation information

[2299] Output: Reservation information is sent to the terminal

[2300] Step 10:

[2301] Terminal

[2302] The terminal transmits the input reservation information to the server.

[2303] Input: Reservation information

[2304] Output: Reservation information sent to the server

[2305] Step 11:

[2306] server

[2307] The server saves the reservation information in a database, notifies the user of the completion of the reservation, and simultaneously generates the necessary training materials and video links and sends them to the terminal.

[2308] Input: Reservation information

[2309] Data processing / data calculation: storing reservation information in a database, generating notifications, generating training materials and links

[2310] Output: Notification of reservation completion, sending of training materials and video links

[2311] Step 12:

[2312] Terminal

[2313] The terminal displays the provided training materials and video links to the user.

[2314] Input: Training materials, video links

[2315] Output: Display of training materials and video links

[2316] Step 13:

[2317] User

[2318] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[2319] Input: Training materials, videos

[2320] Output: Training completed

[2321] Step 14:

[2322] server

[2323] The day before the volunteer activity, the server sends a reminder email to the user.

[2324] Input: Reservation information

[2325] Data processing / data calculation: generating and sending reminder emails

[2326] Output: Send reminder email

[2327] Step 15:

[2328] Terminal

[2329] The terminal receives the reminder message and notifies the user.

[2330] Input: Reminder message

[2331] Output: Reminder message notification

[2332] Step 16:

[2333] User

[2334] Users receive reminders to reconfirm their volunteering dates.

[2335] Enter: Reminder

[2336] Output: Reconfirm date

[2337] Step 17:

[2338] server

[2339] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2340] Input: Reservation information, activity information

[2341] Data processing / data calculation: feedback form generation and submission

[2342] Output: Feedback form submission

[2343] Step 18:

[2344] Terminal

[2345] The terminal displays the feedback form to the user and transmits the entered content to the server.

[2346] Input: Feedback

[2347] Output: Feedback sent to the server

[2348] Step 19:

[2349] User

[2350] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2351] Input: Feedback

[2352] Output: Feedback sent

[2353] Step 20:

[2354] server

[2355] The server analyzes the received feedback using a sentiment analysis engine to determine the user's emotions, and stores the analysis results in a database to be used to improve the quality of future recommendations.

[2356] Input: Feedback

[2357] Data processing / data calculation: Analysis using the sentiment analysis engine, saving the analysis results

[2358] Output: Save the analysis results

[2359] (Application example 2)

[2360] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2361] Conventional volunteer activity participation systems only match users based on their profile information and volunteer demand information, without considering their emotions. This results in low user satisfaction and compatibility, and often results in users not actually participating in activities. Furthermore, they are unable to fully utilize user feedback, making continuous improvement difficult. There is a need to solve these issues and provide more accurate recommendations that reflect users' emotions.

[2362] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a generative AI model that performs matching using user profile information and volunteer demand information, means for analyzing user emotions and selecting activities, and means for collecting user emotional data in real time when the user visits the store and reflecting this data in recommendations. This makes it possible to recommend appropriate volunteer activities based on the user's emotions.

[2363] "User" refers to an individual who registers with the system and wishes to participate in volunteer activities.

[2364] "Profile Information" refers to basic information such as a user's name, email address, and password, as well as detailed information such as volunteer experience, areas of interest, available time, and skills.

[2365] "Volunteer demand information" refers to information such as the type of volunteer activities desired by local communities and organizations, the skills required, the dates and times of activities, and the location.

[2366] A "generative AI model" is a type of artificial intelligence that analyzes a user's profile information and volunteer demand information to recommend the most appropriate volunteer activities.

[2367] "Means for analyzing emotions" refers to technologies for recognizing and analyzing a user's emotional state in real time, such as emotion engines and emotion analysis algorithms.

[2368] "Recommendations" refers to a list of volunteer activities and services suggested by the system based on the user's attributes and status.

[2369] "Training Materials" means written, video, or other educational materials containing the information necessary for a User to properly perform a particular Volunteer Activity.

[2370] "Feedback" refers to impressions and opinions, including experiences and suggestions for improvement, provided by users after volunteering.

[2371] "Database" refers to a system for storing and managing user information, activity history, feedback, etc.

[2372] "Means for making reservations" refers to a function that allows users to reserve a date, time, and location online to participate in volunteer activities.

[2373] A "reminder" is a message sent to the user the day before an activity to remind them of their plans.

[2374] "Emotional data" refers to information that expresses the emotional state obtained from the user's facial expressions, actions, words, etc. in numerical or categorical form.

[2375] "Means of collecting data in real time" refers to technology that allows users to instantly collect their behavior and emotions on the spot and record them as data.

[2376] The present invention provides a system that streamlines the process for users to participate in volunteer activities and, in particular, provides more accurate recommendations by incorporating sentiment analysis. Specific embodiments are described below.

[2377] 1. User registration and profile creation

[2378] A user first accesses the platform, clicks "New Registration," and enters the required information, such as name, email address, and password. Once the information is entered, the device receives the information and sends it to the server. The server stores the received information in a database and sends the user a confirmation email of successful registration. The user then goes to the profile page and enters detailed information, such as volunteer experience, areas of interest, available time, and skills, which is then sent to the server via the device. The server stores this detailed profile information in a database and prepares it for analyzing the user's emotions.

[2379] 2. Providing volunteer information and matching

[2380] The server retrieves local volunteer demand information from a database or external API, compares this information with the user's profile information, analyzes the user's current emotional state using an emotion engine, and recommends optimal volunteer activities using a generative AI model. The device displays the recommendation list sent from the server to the user.

[2381] 3. Volunteer booking and training

[2382] The user selects the volunteer activity they want from the displayed recommendation list and clicks the "Participate" button to proceed to the reservation form. After entering the required information and confirming the reservation, the device sends this information to the server. The server receives the reservation information, stores the volunteer activity details in a database, and notifies the user that the reservation is complete. It also provides the necessary training materials and video links.

[2383] 4. Volunteer Reminders and Execution

[2384] The day before the volunteer activity, the server sends a reminder message to the user. The device receives this reminder message and notifies the user. The user receives the notification and reconfirms the activity schedule.

[2385] 5. Sharing and evaluating volunteer experiences

[2386] After the volunteer activity is completed, the server generates and sends a feedback form to the user. The terminal displays the feedback form to the user, who then enters their experience and suggestions for improvement and submits it. The server then analyzes the received feedback using an emotion engine to determine the user's emotional state. The results are stored in a database and reflected in the next recommendation.

[2387] Examples of concrete examples and prompts

[2388] Examples:

[2389] A user comes into the store, and the camera recognizes their smile and classifies it as "happy."

[2390] Based on the emotional state of "joy," the system refers to past profile information and purchase history to recommend refreshing products (flowers, aroma goods, etc.).

[2391] The user follows the recommendation, purchases the product, and enters feedback such as "It was very refreshing."

[2392] The next time you visit, we will use this feedback to provide you with even more accurate recommendations.

[2393] Example prompt sentence:

[2394] Recommend the best products and services to users based on the following data:

[2395] 1. User basic information (name, gender, age, interests)

[2396] 2. The user's emotional state (happiness, sadness, anger, etc.)

[2397] 3. User purchase history

[2398] For example, "User name: Tanaka Taro," "Gender: Male," "Age: 35," "Interests: Outdoors, gardening," "Emotional state: Joy," "Purchase history: Outdoor goods, houseplants," etc.

[2399] Prompt: Recommendation if you see a girl smiling: "Recommend a refreshing product, such as flowers or aromatherapy products."

[2400] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2401] Step 1:

[2402] A user accesses the platform and clicks "New Registration." They enter the required information, such as their name, email address, and password. Once the information is entered, the device receives it and sends it to the server. The entered data is sent to the server, which then stores it in a database.

[2403] input:

[2404] User basic information (name, email address, password)

[2405] output:

[2406] User information stored in a database

[2407] Specific behavior:

[2408] The user enters basic information into the on-screen form and clicks the submit button. The device transmits the information to the server, which stores it in a database.

[2409] Step 2:

[2410] The server sends the user a confirmation email to confirm the registration. The user receives the confirmation email and accesses the platform again to log in. After logging in, the user goes to the profile page and enters details such as volunteer experience, areas of interest, available time, skills, etc. The device then sends these details to the server.

[2411] input:

[2412] Detailed user profile information (activity experience, interests, available time, skills)

[2413] output:

[2414] Detailed profile information stored in a database

[2415] Specific behavior:

[2416] The user clicks on the link in the confirmation email and logs back into the platform. They enter their details on the profile page and click the submit button. The device transmits the information to the server, which stores it in a database.

[2417] Step 3:

[2418] The server retrieves information about local volunteer demand from a database or external API. It compares this information with the user's profile information and uses an emotion engine to analyze the user's current emotional state. It then uses a generative AI model to generate recommendations for optimal volunteer activities.

[2419] input:

[2420] User profile information, local volunteer demand information, emotional data

[2421] output:

[2422] Recommendation List

[2423] Specific behavior:

[2424] The server periodically updates and stores local volunteer demand data in a database. The generative AI model analyzes this data and user profiles to generate recommendations for optimal volunteer activities.

[2425] Step 4:

[2426] The terminal displays the recommendation list sent from the server to the user, who then selects a volunteer activity from the displayed recommendation list.

[2427] input:

[2428] Recommendation List

[2429] output:

[2430] User-selected volunteer activities

[2431] Specific behavior:

[2432] The server sends the generated recommendation list to the terminal, which displays it to the user. The user selects a preferred activity and sends the selection information.

[2433] Step 5:

[2434] The user clicks the "Participate" button to proceed to the reservation form. They enter the required information and confirm the reservation. The device sends this information to the server. The server receives the reservation information, stores the volunteer activity details in a database, and sends a notification to the user that the reservation is complete.

[2435] input:

[2436] Reservation information (date, time, location, contact information, etc.)

[2437] output:

[2438] Reservation information stored in the database, reservation completion notification

[2439] Specific behavior:

[2440] The user enters the necessary information into the reservation form and clicks the submit button. The terminal transmits the information to the server, which stores it in a database and sends a confirmation email.

[2441] Step 6:

[2442] The server provides the user with the necessary training materials and video links, and the terminal displays these training materials to the user, who then reviews them and acquires the necessary knowledge.

[2443] input:

[2444] Training materials, video links

[2445] output:

[2446] User learning progress

[2447] Specific behavior:

[2448] The server generates a training material link and sends it to the terminal, which displays it to the user, who then checks the material.

[2449] Step 7:

[2450] The server sends a reminder message to the user the day before the volunteer activity. The device receives the reminder message and notifies the user. The user receives the notification and reconfirms the activity date.

[2451] input:

[2452] Reminder Information

[2453] output:

[2454] Reminders

[2455] Specific behavior:

[2456] The server generates a reminder message at the set date and time and sends it to the device, which then displays the reminder to the user.

[2457] Step 8:

[2458] After the volunteer activity is completed, the server generates and sends a feedback form to the user. The terminal displays the feedback form to the user, who then enters their experience and suggestions for improvement and submits it. The server then analyzes the received feedback using an emotion engine to determine the user's emotional state. The results are stored in a database and reflected in the next recommendation.

[2459] input:

[2460] Feedback content

[2461] output:

[2462] Analyzed emotion data, feedback stored in database

[2463] Specific behavior:

[2464] The server generates a feedback form and sends it to the device. The user enters their experience and suggestions for improvement into the form and clicks the submit button. The device transmits the information to the server, which analyzes it using an emotion engine and stores it in a database.

[2465] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2466] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2467] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2468] [Fourth embodiment]

[2469] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2470] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2471] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2472] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2473] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2474] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2475] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2476] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2477] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2478] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[2479] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2480] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2481] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2482] This invention is a system for efficiently recruiting and applying for volunteer activities, and is implemented as follows.

[2483] User registration and profile creation

[2484] User

[2485] Users first access the platform and create a new account.

[2486] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[2487] After logging in, users are directed to a profile page where they can enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2488] Terminal

[2489] The input information is received and sent to the server.

[2490] server

[2491] The received information is stored in a database.

[2492] Send a confirmation email to confirm registration and prepare to recommend volunteer activities suitable for the user based on their profile information.

[2493] Providing volunteer information and matching

[2494] server

[2495] Get local volunteer demand information from a database or external API.

[2496] The AI ​​model analyzes user profile information and volunteer demand information to generate appropriate recommendations.

[2497] Terminal

[2498] The recommendation list sent from the server is displayed to the user.

[2499] User

[2500] Select the volunteer activity you would like to participate in from the list of recommendations provided.

[2501] Volunteer booking and training

[2502] User

[2503] After selecting your volunteer activity, click the "Participate" button to proceed to the reservation form.

[2504] Enter the required information and confirm your reservation.

[2505] Terminal

[2506] The user's selection information is received and the information required for the reservation form is sent to the server.

[2507] server

[2508] Confirm the booking and save the volunteer activity details in a database.

[2509] A confirmation of the booking will be sent back to the user, along with any training materials or video links required for the relevant volunteer activity.

[2510] Terminal

[2511] Display training materials and links to users.

[2512] User

[2513] Review the training materials provided and acquire the necessary knowledge.

[2514] Volunteer Reminders and Execution

[2515] server

[2516] Send users a reminder the day before their volunteer activity.

[2517] Terminal

[2518] Receive reminder messages and notify users.

[2519] User

[2520] Receive reminders and reconfirm your volunteering dates.

[2521] Sharing and evaluating volunteer experiences

[2522] server

[2523] After the volunteer activity is completed, a feedback form is generated and sent to the user.

[2524] Terminal

[2525] A feedback form is displayed to the user and the entered information is sent to the server.

[2526] User

[2527] Fill out the feedback form and submit it to let us know your experience with the activity and any suggestions for improvement.

[2528] server

[2529] The received feedback is analyzed and stored in a database.

[2530] This will be used to recommend the next volunteer activity, allowing for more precise matching.

[2531] Specific examples

[2532] As a specific example, if user "Ichiro Suzuki" creates an account and enters in his profile that he has emergency medical skills, the server will recommend disaster relief activities taking place this weekend in the surrounding area. Then, it will prioritize activities that "can utilize his emergency medical skills." Ichiro Suzuki selects and reserves the activity, learning the provided training materials. He receives a reminder the day before the activity, and after completing the volunteer activity, he can enter feedback that will be reflected in the next activity.

[2533] The system recommends volunteer activities that best suit the user's needs and skills, making volunteering faster and more efficient.

[2534] The processing flow will be explained below.

[2535] Step 1:

[2536] User

[2537] The user accesses the platform, clicks "New Registration," enters the required information such as name, email address, and password, and presses the "Register" button.

[2538] Step 2:

[2539] Terminal

[2540] The terminal receives the information entered by the user and transmits it to the server.

[2541] Step 3:

[2542] server

[2543] The server stores the received information in a database and sends a confirmation email to the user once the information has been saved.

[2544] Step 4:

[2545] User

[2546] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2547] Step 5:

[2548] Terminal

[2549] The terminal transmits the profile information entered by the user to the server.

[2550] Step 6:

[2551] server

[2552] The server stores the received profile information in a database.

[2553] Step 7:

[2554] server

[2555] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it uses a generative AI model to analyze the user's profile and volunteer demand information and generate a recommendation list.

[2556] Step 8:

[2557] Terminal

[2558] The terminal displays the recommendation list received from the server to the user.

[2559] Step 9:

[2560] User

[2561] The user selects the volunteer activity they wish to participate in from the displayed list of recommendations.

[2562] Step 10:

[2563] User

[2564] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[2565] Step 11:

[2566] Terminal

[2567] The terminal transmits the reservation information entered by the user to the server.

[2568] Step 12:

[2569] server

[2570] The server receives the reservation information, stores the volunteer activity details in a database, and then sends the user a notification that the reservation is complete, along with any necessary training materials and video links.

[2571] Step 13:

[2572] Terminal

[2573] The terminal displays the provided training materials and links to the user.

[2574] Step 14:

[2575] User

[2576] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[2577] Step 15:

[2578] server

[2579] The day before the volunteer activity, the server sends a reminder to the user.

[2580] Step 16:

[2581] Terminal

[2582] The terminal receives the reminder message and notifies the user.

[2583] Step 17:

[2584] User

[2585] Users receive reminders to reconfirm their volunteering dates.

[2586] Step 18:

[2587] server

[2588] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2589] Step 19:

[2590] Terminal

[2591] The terminal displays a feedback form to the user and transmits the entered content to the server.

[2592] Step 20:

[2593] User

[2594] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2595] Step 21:

[2596] server

[2597] The server analyzes the received feedback and stores it in a database. Based on the analysis results, the server will use them to recommend the next volunteer activity.

[2598] Through this series of steps, users can efficiently participate in volunteer activities and use the experience gained from the activities for future use.

[2599] Example 1

[2600] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2601] In conventional volunteer recruitment systems, it is difficult for users to find volunteer activities that best suit their skills and interests, and the application process is cumbersome and inefficient. Furthermore, the management of activity bookings, training, reminders, and feedback is not centralized, and an improvement in the user experience is required.

[2602] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2603] In this invention, the server includes means for a user to input registration information, means for inputting basic information and detailed profile information of the user, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for sending a registration completion confirmation email to the user, means for obtaining local volunteer demand information from a database or an external API, means for analyzing the user's profile information and volunteer demand information with an AI model, means for providing the generated volunteer recommendations to the user, means for the user to make a reservation to participate in a volunteer activity, means for sending a reservation completion confirmation email and training materials to the user, and means for collecting feedback on the volunteer activity and using it for next recommendations. This makes it possible to efficiently find volunteer activities that best suit a user's skills and interests, simplify the application process, and centralize management of training, reminders, and feedback.

[2604] "User" refers to an individual or group that registers with the system to participate in volunteer activities and inputs and operates various information.

[2605] "Registration Information" refers to basic personal information such as name, email address, and password that a User enters into the System.

[2606] "Profile Information" refers to detailed information that a User enters into the system, such as volunteer experience, areas of interest, available time, and skills.

[2607] "Server" refers to a computer system that receives, processes, and stores information sent by users in a database.

[2608] "Database" refers to a data storage system for storing user data, including registration information, profile information, volunteer demand information, and feedback information.

[2609] "Generative AI Model" refers to an artificial intelligence model used to analyze a user's profile information and volunteer demand information and generate appropriate recommendations.

[2610] "Recommendations" refers to a list of volunteer activities recommended to a user by a generative AI model.

[2611] "Training Materials" means materials and video links that a User must study before participating in a Volunteer Activity.

[2612] "Feedback" refers to the user's experience with the activity and evaluation of areas for improvement that they enter after completing the volunteer activity.

[2613] "Reminder" refers to a notification message sent to a user immediately before a volunteer activity.

[2614] "External API" refers to an application programming interface used to obtain volunteer demand information from data sources external to the System.

[2615] The present invention is a system for efficiently recruiting and applying for volunteer activities. A specific embodiment of this system will be described below.

[2616] User registration and profile creation

[2617] User

[2618] Users first access the platform using a web browser or mobile application and are redirected to a page to create a new account.

[2619] Enter basic information such as your name, email address, and password, then click the "Register" button to create an account.

[2620] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[2621] Terminal

[2622] The terminal transmits the basic information and profile information entered by the user to the server.

[2623] server

[2624] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[2625] Providing volunteer information and matching

[2626] server

[2627] The server retrieves local volunteer demand information from an internal database or an external API.

[2628] The server analyzes the user's profile information and the acquired volunteer demand information using a generative AI model (e.g., using TensorFlow or PyTorch) to generate a list of recommended appropriate volunteer activities.

[2629] Terminal

[2630] The terminal displays the recommendation list received from the server to the user.

[2631] User

[2632] Users select the volunteer activities they would like to participate in from the recommendation list.

[2633] Volunteer booking and training

[2634] User

[2635] Users select the volunteer activity they wish to participate in and click the "Participate" button. They then fill in the necessary information in the reservation form to confirm their reservation.

[2636] Terminal

[2637] The terminal transmits the user's reservation information to the server.

[2638] server

[2639] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials (e.g., PDFs or video links) required for the volunteer activity.

[2640] Terminal

[2641] The terminal displays training materials and video links to the user.

[2642] User

[2643] The user reviews the provided training materials and acquires the necessary knowledge.

[2644] Volunteer Reminders and Execution

[2645] server

[2646] The server sends a reminder to the user the day before the volunteer activity.

[2647] Terminal

[2648] The terminal receives the reminder message and notifies the user.

[2649] User

[2650] Users receive reminders to reconfirm their volunteering dates.

[2651] Sharing and evaluating volunteer experiences

[2652] server

[2653] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[2654] Terminal

[2655] The terminal displays a feedback form to the user and transmits the entered content to the server.

[2656] User

[2657] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2658] server

[2659] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[2660] Examples of concrete examples and prompts

[2661] As a specific example, consider the case where user "A" has emergency medical skills. The server retrieves local volunteer information from a database or external API, analyzes it using a generative AI model, and recommends the most suitable volunteer activity for "A" (for example, disaster relief activities).

[2662] An example of a prompt is as follows:

[2663] "How do users select a volunteer activity and complete a booking?"

[2664] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2665] Step 1:

[2666] User

[2667] First, users access the platform using a web browser or mobile application, and are redirected to a new account creation page where they enter basic information such as their name, email address, and password, and then click the "Register" button to create an account.

[2668] Input: Name, Email Address, Password

[2669] Output: Registration request

[2670] Specific operation: The browser will redirect to the account creation page and display the input form. When the user presses the "Register" button, the input information will be sent to the server.

[2671] Step 2:

[2672] Terminal

[2673] The terminal sends the basic information entered by the user to the server.

[2674] Input: Basic information entered by the user

[2675] Output: Registration information sent to the server

[2676] Specific operation: The terminal sends an HTTP POST request to the server.

[2677] Step 3:

[2678] server

[2679] The server stores the received information in a database, sends the user a confirmation email, and prepares to recommend volunteer activities suitable for the user based on their profile information.

[2680] Input: Registration information sent to the server

[2681] Output: User registration information stored in the database, confirmation email

[2682] Specific operation: The server creates a record in the database and sends a confirmation email using the mail server.

[2683] Step 4:

[2684] User

[2685] After creating an account, users log in and are taken to a profile page where they can enter details such as volunteer experience, areas of interest, available hours, and skills.

[2686] Input: Login information, profile information

[2687] Output: Detailed profile information

[2688] Specific operation: The browser will redirect to the profile page, and an input form will be displayed. The user will enter their information.

[2689] Step 5:

[2690] Terminal

[2691] The terminal transmits the detailed profile information entered by the user to the server.

[2692] Input: Detailed profile information

[2693] Output: Profile information sent to the server

[2694] Specific operation: The terminal sends an HTTP POST request to the server.

[2695] Step 6:

[2696] server

[2697] The server stores the received profile information in a database and retrieves local volunteer demand information from an internal database or an external API.

[2698] Input: Profile information sent to the server

[2699] Output: Profile information stored in the database, local volunteer demand information

[2700] Specific operation: The server creates a record in the database and sends an API request to retrieve volunteer demand information.

[2701] Step 7:

[2702] server

[2703] The server analyzes the user's profile information and volunteer demand information using a generative AI model to generate appropriate volunteer recommendations.

[2704] Input: User profile information, volunteer demand information

[2705] Output: Volunteer recommendation list

[2706] Specific operations: Run analysis algorithms using generative AI models (such as TensorFlow or PyTorch).

[2707] Step 8:

[2708] Terminal

[2709] The terminal displays the recommendation list received from the server to the user.

[2710] Input: Volunteer Recommendation List

[2711] Output: The recommendation list shown to the user

[2712] Specific operation: The device receives the HTTP response and renders the recommendation list in the browser.

[2713] Step 9:

[2714] User

[2715] Users select the volunteer activity they want to participate in from the recommendation list and click the "Participate" button. Then, they fill in the necessary information in the reservation form to confirm their reservation.

[2716] Input: Recommendation list, reservation information

[2717] Output: Booking request

[2718] Specific operation: A click event transitions to the next form page, and after completing the input, press the "Confirm" button.

[2719] Step 10:

[2720] Terminal

[2721] The terminal transmits the user's reservation information to the server.

[2722] Input: Reservation information

[2723] Output: Reservation information sent to the server

[2724] Specific operation: The terminal sends an HTTP POST request to the server.

[2725] Step 11:

[2726] server

[2727] The server confirms the reservation, stores the volunteer activity details in a database, and sends the user a confirmation email along with any training materials required for the volunteer activity.

[2728] Input: Reservation information

[2729] Output: Booking information stored in a database, confirmation emails, training materials

[2730] What happens: The server saves the reservation information in a database and uses a mail server to send a confirmation email containing the training materials.

[2731] Step 12:

[2732] Terminal

[2733] The terminal displays training materials and video links to the user.

[2734] Input: Training materials

[2735] Output: The training material displayed to the user

[2736] What happens: The browser or app renders the material and displays it to the user.

[2737] Step 13:

[2738] server

[2739] The server sends a reminder to the user the day before the volunteer activity.

[2740] Input: Date information for the relevant volunteer activity

[2741] Output: Reminder message

[2742] Specific operation: The server uses the mail server to send the reminder message.

[2743] Step 14:

[2744] Terminal

[2745] The terminal receives the reminder message and notifies the user.

[2746] Input: Reminder message

[2747] Output: Reminders notified to the user

[2748] Specific behavior: The device displays a notification and alerts the user.

[2749] Step 15:

[2750] server

[2751] After the volunteer activity is completed, the server generates a feedback form and sends it to the user.

[2752] Input: Volunteer activity completion information

[2753] Output: Feedback form submission

[2754] Specific operation: The server sends the feedback form using the mail server.

[2755] Step 16:

[2756] Terminal

[2757] The terminal displays a feedback form to the user and transmits the entered content to the server.

[2758] Input: Feedback Form

[2759] Output: The input feedback

[2760] What happens: The browser or app displays a feedback form, which the user fills out and then submits to the server.

[2761] Step 17:

[2762] server

[2763] The server analyzes the received feedback, stores it in a database, and uses it to recommend the next volunteer activity.

[2764] Input: Feedback

[2765] Output: Parsed feedback data, feedback information stored in a database

[2766] What happens: The analysis algorithm processes the feedback and creates a record in the database.

[2767] (Application example 1)

[2768] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2769] Conventional volunteer participation systems often make it difficult for users to find activities that match their skills and interests, resulting in inappropriate matching. Additionally, users are often unable to fully prepare for volunteer activities due to insufficient training materials and videos. Furthermore, because feedback is collected and analyzed manually, it is difficult to effectively reflect this feedback in future recommendations.

[2770] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2771] In this invention, the server includes a means for a user to input registration information, a means for using a generative AI model that performs matching using the user's profile information and volunteer demand information, a means for providing the generated volunteer recommendations to the user, a means for the user to make a reservation to participate in a volunteer activity, a means further including a means for providing training materials and videos necessary for the volunteer activity, a means for collecting feedback on the volunteer activity and using it for the next recommendation, a means for viewing the training video using a head-mounted display, and a means for sending a reminder to the user the day before the volunteer activity. This allows users to easily find the most suitable volunteer activity based on their skills and interests, allowing them to participate in the activity with sufficient preparation, and allows feedback to be effectively collected and analyzed to be reflected in the next recommendation.

[2772] "User" refers to an individual who registers with the System and provides profile information to participate in volunteer activities.

[2773] "Means for entering registration information" refers to the interface through which a user accesses the system and enters basic information such as name, email address, and password.

[2774] "Profile information" refers to information that indicates the user's characteristics and background, such as the user's volunteer experience, areas of interest, available time, and skills.

[2775] "Volunteer demand information" refers to information about the types and content of volunteers needed in specific regions or organizations.

[2776] A "generative AI model" refers to an artificial intelligence model that analyzes a user's profile information and volunteer demand information to recommend the most suitable volunteer activities for the user.

[2777] "Recommendations" refers to potential volunteer activities suggested to users by the generative AI model.

[2778] "Means for making reservations" refers to an interface that allows a user to reserve a date, time, and location for a selected volunteer activity.

[2779] "Training materials and videos" refers to written and visual content that helps users learn the knowledge and skills necessary to participate in volunteer activities.

[2780] "Head-mounted display" refers to a display device used by a user to view training videos with a 360-degree field of view.

[2781] "Reminder" refers to a notification message sent to a user the day before a volunteer activity.

[2782] "Feedback" refers to the user's experience with the activity and their opinions on areas for improvement provided after completing the volunteer activity.

[2783] In the present invention, the following means and processes are used to provide a system that allows users to efficiently participate in volunteer activities.

[2784] 1. User registration and profile creation

[2785] A user accesses the system and creates a new account. The user enters basic information such as name, email address, and password, and presses the "Register" button, which sends the information to the server.

[2786] The server receives this and stores it in a database. After the user logs in, they go to their profile page and enter detailed profile information such as their volunteer experience, areas of interest, available time, skills, etc. This is also sent to the server and stored in the database.

[2787] 2. Providing volunteer information and matching

[2788] The server retrieves local volunteer demand information from a database or external API. Using a generative AI model, it analyzes the user's profile information and volunteer demand information to generate appropriate recommendations. These are sent to the user's device and displayed as a recommendation list.

[2789] Specifically, the following prompt sentences are input into the generative AI model, which then recommends the most suitable volunteer activity for the user:

[2790] User Profile:

[2791] Name: Ichiro Suzuki

[2792] Volunteer experience: Emergency medical technician

[2793] Area of ​​interest: Disaster relief

[2794] Available times: Weekends

[2795] Volunteer activities offered:

[2796] 1. Disaster support activities A

[2797] 2. Disaster relief activities B

[2798] 3. Community cleanup activities

[2799] Please choose one activity to recommend.

[2800] 3. Volunteer booking and training

[2801] The user selects the volunteer activity they wish to participate in from the recommended list. After making their selection, they click the "Participate" button and proceed to the reservation form. They then enter the required information and confirm their reservation.

[2802] The server receives the request, confirms the reservation, stores the volunteer activity details in a database, and returns a confirmation of the reservation to the user along with relevant training materials and video links that can be viewed on the user's smartphone or head-mounted display.

[2803] 4. Volunteer Reminders and Execution

[2804] The server sends a reminder to the user the day before the volunteer activity.

[2805] The terminal receives the reminder message and notifies the user.

[2806] The user checks this and reconfirms the schedule for volunteer activities.

[2807] 5. Sharing and evaluating volunteer experiences

[2808] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2809] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2810] The server receives this, stores it in a database, and uses it to recommend volunteer activities for the next time.

[2811] The system configuration utilizes the following hardware and software:

[2812] Smartphone: iOS or Android compatible.

[2813] Head-mounted display: VR compatible display.

[2814] Server side: Uses AWS (Amazon Web Services).

[2815] AI model: Use Amazon SageMaker, etc.

[2816] Database: MySQL or PostgreSQL.

[2817] This allows users to easily find the best volunteer activities based on their skills and interests, allows them to participate in activities well prepared, and effectively collect and analyze feedback to reflect in future recommendations.

[2818] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2819] Step 1:

[2820] The user enters registration information

[2821] input:

[2822] The user enters basic information such as name, email address, and password.

[2823] Data processing / calculation:

[2824] The terminal organizes the input information and sends it to the server.

[2825] output:

[2826] The server sends a confirmation email to the user and stores the information in a database.

[2827] Step 2:

[2828] User enters profile information

[2829] input:

[2830] Users enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2831] Data processing / calculation:

[2832] The terminal organizes the entered information and sends it to the server.

[2833] output:

[2834] The server saves the profile information to a database and notifies the user that the information has been saved.

[2835] Step 3:

[2836] Acquisition and analysis of volunteer demand information

[2837] input:

[2838] The server retrieves local volunteer demand information from a database or external API.

[2839] Data processing / calculation:

[2840] The server analyzes the acquired volunteer demand information and user profile information, and generates appropriate recommendations using a generative AI model.

[2841] output:

[2842] Send the recommendation list to the user.

[2843] Step 4:

[2844] User selects volunteer activity and makes reservation

[2845] input:

[2846] The user selects the volunteer activity they want to participate in from the recommended list and clicks "Participate." They then enter the required information and confirm their reservation.

[2847] Data processing / calculation:

[2848] The terminal transmits the input information to the server.

[2849] output:

[2850] The server stores the reservation information in a database and sends the user details, training materials and video links.

[2851] Step 5:

[2852] Watch training videos required for volunteer work

[2853] input:

[2854] The user receives the training materials and video links sent to them and begins watching them.

[2855] Data processing / calculation:

[2856] The device plays the video link on the head-mounted display or smartphone.

[2857] output:

[2858] Users watch training videos and acquire the necessary knowledge.

[2859] Step 6:

[2860] Volunteer Reminders

[2861] input:

[2862] The server sets a reminder the day before the volunteer activity.

[2863] Data processing / calculation:

[2864] The server generates a reminder message and sends it to the terminal.

[2865] output:

[2866] The terminal notifies the user of the reminder message.

[2867] Step 7:

[2868] Collecting feedback after volunteering

[2869] input:

[2870] After completing the activity, users enter their experience and suggestions for improvement in a feedback form submitted.

[2871] Data processing / calculation:

[2872] The device sends feedback information to the server, which analyzes it and stores it in a database.

[2873] output:

[2874] The server will incorporate the feedback into its next recommendations.

[2875] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2876] This invention is a system for efficiently recruiting and applying for volunteer activities, and in particular, it combines a function for recognizing a user's emotions and selecting activities. It is implemented through the following specific process.

[2877] User registration and profile creation

[2878] User

[2879] First, users access the platform and click "Sign Up." They then enter the required information, such as their name, email address, and password, and press the "Register" button to create an account.

[2880] Terminal

[2881] The terminal receives the information entered by the user and transmits it to the server.

[2882] server

[2883] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[2884] User

[2885] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2886] Terminal

[2887] The terminal transmits the profile information entered by the user to the server.

[2888] server

[2889] The server stores the received profile information in a database and uses an emotion engine to analyze the emotions expressed by the user when they input their information. Based on the analysis results, the server prepares to generate a more accurate recommendation list.

[2890] Providing volunteer information and matching

[2891] server

[2892] The server retrieves local volunteer demand information from a database or external API, and analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model, thereby generating appropriate recommendations based on the user's emotional state.

[2893] Terminal

[2894] The terminal displays the recommendation list sent from the server to the user.

[2895] User

[2896] The user selects the most suitable volunteer activity based on their emotional state from the presented recommendation list.

[2897] Volunteer booking and training

[2898] User

[2899] The user clicks the "Participate" button, proceeds to the reservation form, enters the necessary information, and confirms the reservation.

[2900] Terminal

[2901] The terminal transmits the reservation information entered by the user to the server.

[2902] server

[2903] The server receives the reservation information, stores the volunteer activity details in a database, and then sends a notification to the user that the reservation is complete, along with any necessary training materials and video links.

[2904] Terminal

[2905] The terminal displays the provided training materials and links to the user.

[2906] User

[2907] The user reviews the displayed training materials and videos and acquires the necessary knowledge.

[2908] Volunteer Reminders and Execution

[2909] server

[2910] The day before the volunteer activity, the server sends a reminder to the user.

[2911] Terminal

[2912] The terminal receives the reminder message and notifies the user.

[2913] User

[2914] Users receive reminders to reconfirm their volunteering dates.

[2915] Sharing and evaluating volunteer experiences

[2916] server

[2917] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2918] Terminal

[2919] The terminal displays a feedback form to the user and transmits the entered content to the server.

[2920] User

[2921] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2922] server

[2923] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The results of this analysis are stored in a database and reflected in the next volunteer activity recommendation.

[2924] Specific examples

[2925] As a concrete example, suppose a user creates an account and participates in disaster relief activities last week. The user reviews the training materials, receives reminders, and participates in the activities. After completing the activities, the user enters "I was very happy and grateful" in the feedback form. The emotion engine classifies this emotion as "joy" and uses it to recommend activities for the next time. In this way, volunteer activities based on the user's emotions can be recommended, improving the user's experience.

[2926] This system analyzes the user's emotions and recommends volunteer activities based on those emotions, thereby achieving effective volunteer activities with high user satisfaction.

[2927] The processing flow will be explained below.

[2928] Step 1:

[2929] User

[2930] Users access the platform, click "Sign Up," enter the required information such as name, email address, and password, and then press the "Register" button to create an account.

[2931] Step 2:

[2932] Terminal

[2933] The terminal receives the information entered by the user and transmits it to the server.

[2934] Step 3:

[2935] server

[2936] The server stores the received information in a database and sends the user a confirmation email that registration is complete.

[2937] Step 4:

[2938] User

[2939] Users log in and go to their profile page to enter detailed profile information such as volunteer experience, areas of interest, available time, and skills.

[2940] Step 5:

[2941] Terminal

[2942] The terminal transmits the profile information entered by the user to the server.

[2943] Step 6:

[2944] server

[2945] The server stores the received profile information in a database. It also uses an emotion engine to analyze the user's emotions when they input their information, and adds the analysis results to the profile information.

[2946] Step 7:

[2947] server

[2948] The server retrieves local volunteer demand information from a database or external API. Based on the retrieved information, it analyzes the user's profile information and volunteer demand information using an emotion engine and generative AI model.

[2949] Step 8:

[2950] server

[2951] The server generates a recommendation list based on the analysis results and lists the most suitable volunteer activities taking into account the user's emotional state.

[2952] Step 9:

[2953] Terminal

[2954] The terminal displays the recommendation list sent from the server to the user.

[2955] Step 10:

[2956] User

[2957] The user selects the volunteer activity they would like to participate in from the recommended list and clicks the "Participate" button to confirm their selection.

[2958] Step 11:

[2959] Terminal

[2960] The terminal transmits the user's selection information to the server.

[2961] Step 12:

[2962] server

[2963] The server stores the received selection information in a database, confirms the reservation, records the volunteer activity details, notifies the user of the reservation completion, and provides the necessary training materials and video links to the device.

[2964] Step 13:

[2965] Terminal

[2966] The terminal displays the provided training materials and video links to the user.

[2967] Step 14:

[2968] User

[2969] Users review the training materials and videos provided to them and acquire the necessary knowledge.

[2970] Step 15:

[2971] server

[2972] The day before the volunteer activity, the server sends a reminder to the user.

[2973] Step 16:

[2974] Terminal

[2975] The terminal receives the reminder message and notifies the user.

[2976] Step 17:

[2977] User

[2978] The user checks the reminder and reconfirms the volunteering date.

[2979] Step 18:

[2980] server

[2981] After the volunteer activity is completed, the server generates and sends a feedback form to the user.

[2982] Step 19:

[2983] Terminal

[2984] The terminal displays a feedback form to the user and transmits the entered content to the server.

[2985] Step 20:

[2986] User

[2987] Users enter their experience with the activity and suggestions for improvement in the feedback form and submit it.

[2988] Step 21:

[2989] server

[2990] The server analyzes the received feedback using an emotion engine to determine the user's emotions. The analysis results are stored in a database and reflected in the next volunteer activity recommendation.

[2991] Step 22:

[2992] server

[2993] The next time the server generates recommendations, it will take into account the collected feedback and the results of sentiment analysis to suggest volunteer activities that are more suitable for the user.

[2994] This system analyzes users' emotions and recommends volunteer activities, thereby achieving high user satisfaction and effective volunteer activities.

[2995] Example 2

[2996] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2997] Conventional volunteer activity matching systems have difficulty recommending volunteer activities based on user emotions, which makes it difficult to increase user satisfaction. Furthermore, systems for efficiently collecting user feedback and utilizing it for next-time recommendations are lacking. Furthermore, systems for providing reminders before volunteer activities and necessary training materials are insufficient. To solve these issues, an advanced matching system that includes user emotion analysis is needed.

[2998] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2999] In this invention, the server includes: a means for users to input registration information; a means for saving user profile information in a database; a means including an emotion analysis engine for analyzing user emotions; a means for using a generative AI model to perform matching using volunteer demand information, user profile information, and emotion analysis results; a means for providing the generated volunteer recommendations to the user; a means for users to make reservations for volunteer activities; a means for providing training materials necessary for volunteer activities; a means for collecting feedback on volunteer activities and using it to make recommendations for the next activity; a means for sending a reminder to the user the day before the volunteer activity; and a means for analyzing the user's feedback using the emotion analysis engine and automatically saving the feedback in a database. This makes it possible to recommend optimal volunteer activities based on the user's emotions and increase user satisfaction. Furthermore, by reflecting the feedback analysis in the next recommendation, more effective volunteer activities can be realized.

[3000] "User" refers to an individual who accesses the System and participates in volunteer activities.

[3001] "Registration Information" refers to the necessary data, such as name, email address, and password, entered by a User when registering with the System.

[3002] "Profile Information" refers to detailed data entered by a user, such as volunteer experience, areas of interest, available time, and skills.

[3003] "Database" means a digital storage device for storing user registration and profile information.

[3004] "Emotion analysis engine" refers to an algorithm or software that analyzes a user's emotional state from their input.

[3005] "Volunteer demand information" refers to data on volunteer activities provided by local communities and organizations.

[3006] "Generative AI model" refers to an artificial intelligence model that recommends optimal volunteer activities based on a user's profile information and sentiment analysis results.

[3007] "Recommendations" refers to suggestions for volunteer activities suitable for the user, generated by a generative AI model.

[3008] "Reservation information" refers to detailed data such as the date, time, and location that a user enters to participate in a volunteer activity. ...

Claims

1. A means for users participating in volunteer activities to input registration information; a means for using a generative AI model to perform matching using user profile information and volunteer demand information; means for providing the generated volunteer recommendations to a user; a means for a user to make a reservation to participate in a volunteer activity; a means of providing training materials necessary for volunteer work; A system that includes a means to collect feedback on volunteer activities and use it to inform future recommendations.

2. The system of claim 1 , further comprising means for sending a reminder to the user the day before the volunteer activity.

3. 2. The system according to claim 1, further comprising means for analyzing the user's feedback content and automatically storing the content in a database.

Images