System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting a field of interest of a user; means for using a generative AI model to recommend an appropriate donation organization based on the field of interest; means for providing detailed information on a donation organization recommended by the generative AI model; means for performing a donation procedure using a mobile payment app; and means for generating a donation certification and providing the donation certification to the user after a donation is completed.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] In recent years, growing interest in environmental and social issues has led to an increase in opportunities for individuals to contribute to society through donations. However, choosing a donation recipient requires users to collect a large amount of information, which requires a lot of time and effort, causing significant stress for users. Furthermore, the complicated donation process can be a barrier to donating. Furthermore, many donation platforms charge fees, which can lead to the problem of not all donations reaching the recipient. There is a need for a system that can solve these issues and allow users to make donations easily and quickly. [Means for solving the problem]

[0005] The present invention relates to a system that collects a user's areas of interest and uses a generative AI model to recommend appropriate donation organizations based on that information. The system includes a means for using a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, a means for providing detailed information about the donation organizations recommended by the generative AI model, a means for carrying out donation procedures using a mobile payment app, and a means for generating and providing a donation certificate to the user after the donation is completed. This system allows users to easily select a donation recipient and quickly complete the donation. Furthermore, by simplifying the donation procedure and waiving fees, it reduces user stress and promotes social contribution activities.

[0006] "User" means an individual or organization that makes a donation using the System.

[0007] "Interest areas" are specific topics or categories that a user is interested in and wants to support.

[0008] A "donation organization" is an organization that receives donations from users and uses those funds to carry out social contribution or charitable activities.

[0009] A "generative AI model" is an artificial intelligence algorithm that recommends appropriate donation organizations based on a user's areas of interest.

[0010] "Recommendation" refers to the act of presenting a user with a donation organization selected by the generative AI model based on the user's areas of interest.

[0011] "Detailed information" refers to specific information about the activities of the recommended charity, how to donate, and past achievements.

[0012] A "mobile payment app" is a payment application for smartphones or tablets that users use to easily make donations.

[0013] A "donation procedure" is a series of actions a user takes to send donations to a donation organization.

[0014] A "donation certificate" is a document issued to certify that a donation has been officially completed, and includes information such as the donation amount, recipient, and date.

[0015] "Handling fees" are additional costs incurred when processing a donation. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. This system is made up of a server, a terminal, and a series of operations performed by the user.

[0038] Server Operation

[0039] 1. Receiving User Information

[0040] The server receives information entered by the user from the device, such as name, email address, and areas of interest.

[0041] 2. Recommendations using generative AI models

[0042] The server uses a generative AI model to research suitable donation organizations based on the user's areas of interest. The generative AI model then pulls relevant information from a database and lists the best donation recipients for the user.

[0043] 3. Providing detailed information

[0044] The server documents detailed information about the recommended donation organization (such as its activities, donation methods, and past performance) and sends it to the terminal.

[0045] 4. Managing donation procedures

[0046] When a user decides to donate, the server connects to the mobile payment app to initiate the donation process. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[0047] Device behavior

[0048] 1. Providing an interface

[0049] The device provides an interface for the user to enter input or make selections, such as displaying a screen that allows the user to select areas of interest or identify charitable organizations.

[0050] 2. Sending and receiving information

[0051] The information entered by the user is sent to the server, and at the same time, the recommendation list and detailed information received from the server are displayed, providing an interface that is easy for the user to use.

[0052] 3. Completing the donation process

[0053] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server.

[0054] User behavior

[0055] 1. Entering information and making selections

[0056] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the system to recommend organizations that match their interests.

[0057] 2. Check the recommendation list

[0058] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[0059] 3. Completing the donation process

[0060] Donate to the charity of your choice. Complete the payment through the mobile payment app to formalize your donation. Once the payment is complete, users will receive a donation certificate that they can save or print.

[0061] Specific examples

[0062] As a concrete example, consider the case where a user makes a donation to an environmental protection cause. The following is the sequence of events:

[0063] 1. Entering the user's initial information

[0064] A user turns on their device and selects "environmental protection" as an area of ​​interest. This information is sent to the server.

[0065] 2. Generative AI model to recommend donation organizations

[0066] The server uses a generative AI model to obtain information on multiple organizations engaged in environmental protection activities and generate a recommendation list.

[0067] 3. Submit and confirm your details

[0068] The server sends the generated recommendation list to the terminal, where the user can review the list, check the details of the "Environmental Protection Organization A" that interests the user, and finally decide to donate.

[0069] 4. Completing the donation process

[0070] The user launches the mobile payment app, enters their payment information, and makes a donation of 2,000 yen. If the payment is successful, the information is sent to the server.

[0071] 5. Receiving a donation certificate

[0072] The server generates a donation certificate and sends it to the device, which the user can download and save as a PDF.

[0073] As described above, this system provides users with a means to make donations easily and quickly, thereby promoting donation activities and raising awareness of social contribution.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[0077] Step 2:

[0078] The terminal sends the user's input information to the server, which stores the received information in a database and sends a notification to the terminal that registration is complete.

[0079] Step 3:

[0080] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[0081] Step 4:

[0082] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[0083] Step 5:

[0084] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[0085] Step 6:

[0086] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[0087] Step 7:

[0088] When the user selects a charity, the terminal displays a screen for inputting the donation amount for that charity. The user inputs the donation amount and clicks the Donate button.

[0089] Step 8:

[0090] When the device detects a click on the donation button, it launches the mobile payment app, and the user selects a payment method (e.g., credit card, electronic money, etc.) and completes the payment.

[0091] Step 9:

[0092] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[0093] Step 10:

[0094] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[0095] Step 11:

[0096] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[0097] The above is the specific process flow of this system, which allows users to make donations based on their areas of interest quickly and easily.

[0098] Example 1

[0099] 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."

[0100] Conventional donation systems have the problem that it is difficult for users to find a donation recipient that suits their area of ​​interest, and the complicated donation process prevents users from donating. In particular, users are discouraged from donating because they have to search multiple websites to get detailed information, and fees incurred during the donation process.

[0101] 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.

[0102] In this invention, the server includes means for collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for inputting a prompt sentence into the generative AI model to list multiple donation organizations, means for providing detailed information about the donation organizations recommended by the generative AI model, means for carrying out a donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to donate to areas of interest easily and efficiently.

[0103] "User Interests" refers to the activities or themes that are of particular interest to the user who wishes to donate.

[0104] A "generative AI model" refers to an artificial intelligence algorithm that recommends appropriate donation organizations based on input data and prompts.

[0105] A "prompt" refers to a question or instruction entered into a generative AI model to obtain a specific recommendation result.

[0106] A "donor organization" refers to a nonprofit organization that receives funds to support a specific social issue or cause.

[0107] "Detailed information" refers to information necessary for users to decide to donate, such as the activities of the donation organization, how to donate, and past performance.

[0108] "Mobile payment app" refers to a software application that allows users to make monetary payments using mobile devices such as smartphones and tablets.

[0109] "Donation Process" refers to the entire process of transferring funds to the donation organization selected by the User.

[0110] "Donation Certificate" means a document officially certifying that a User has made a Donation.

[0111] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. The system includes a server, a terminal, and a series of user operations.

[0112] First, the user enters their interests through the device's interface. Specifically, the user enters their name, email address, and the area of ​​interest they wish to support (e.g., "environmental protection") into the device, which then sends this information to the server. The device can be a smartphone, tablet, or PC, and uses an interface for inputting and receiving information.

[0113] Next, the server uses a generative AI model to recommend appropriate organizations to donate to based on the information received from the user. This generative AI model uses an advanced generative AI model (e.g., GPT-3) that uses natural language processing technology. By inputting a prompt sentence into the generative AI model, multiple organizations to donate to are listed. An example of this prompt sentence is, "I'm interested in environmental protection. Please recommend an appropriate organization for me to donate to."

[0114] The server then documents detailed information about the donation organizations listed by the generative AI model, including the activities of each organization, donation methods, past performance, etc. The documented details are sent from the server to the device, where the user can view them.

[0115] When the user checks the recommended list and decides to donate to a specific charity, a mobile payment app is launched. This mobile payment app can be, for example, PayPal or Stripe. The user enters the donation amount through the payment app and makes the payment. Once the payment is complete, the information is sent back to the server.

[0116] Finally, after the server confirms that the donation has been successfully completed, it will generate a donation certificate and send it to the user's email address, which the user can download and save.

[0117] As described above, the present invention provides a system that enables users to easily and quickly make donations to areas they are interested in. This aims to encourage donation activities and increase awareness of social contribution.

[0118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0119] Step 1:

[0120] Enter initial information

[0121] The user inputs information such as their interests, name, and email address through the device's interface. This information is temporarily stored within the device. Specifically, the user selects the interest category "environmental protection."

[0122] Input: Interests, Name, Email Address

[0123] Output: User input information (JSON format)

[0124] Step 2:

[0125] Sending user information

[0126] The device sends the information entered by the user to the server, using the REST API to transmit data over the HTTPS protocol to ensure security.

[0127] Input: User input information

[0128] Output: User information sent to the server

[0129] Step 3:

[0130] Recommendations based on generative AI models

[0131] The server uses a generative AI model (e.g., GPT-3) based on the received user interest information to research appropriate donation organizations. Specifically, it performs the following operations:

[0132] The server generates the prompt "I'm interested in environmental protection. Please recommend a suitable organization for me to donate to."

[0133] Input the prompt sentence into the generative AI model

[0134] The generative AI model generates a list of donation organizations and returns that information to the server.

[0135] Input: User information, prompt text

[0136] Output: List of recommended donors

[0137] Step 4:

[0138] Submit your recommendation list and details

[0139] The server documents detailed information about the donation organizations listed by the generative AI model (such as their activities, donation methods, and past performance) and sends it to the device. A template engine is used for the documentation, which responds dynamically.

[0140] Input: List of recommended donors

[0141] Output: Documented donor details

[0142] Step 5:

[0143] Check the recommendation list

[0144] Users can check the recommended list on their device and view detailed information on organizations they are interested in, which will then help them select the best recipient.

[0145] Input: Documented donor details

[0146] Output: Selected donors

[0147] Step 6:

[0148] Start the donation process

[0149] The user selects the organization to which they wish to donate and clicks the "Start Donation" button. This action launches the mobile payment app, and they also enter the donation amount.

[0150] Input: Selected charity, donation amount

[0151] Output: Launch of mobile payment app

[0152] Step 7:

[0153] Managing donation processes

[0154] The terminal guides the user through the payment method selected by the user to complete the donation. The server connects to the mobile payment app and monitors the progress of the payment in real time.

[0155] Input: Donation amount, payment method

[0156] Output: Payment completion information

[0157] Step 8:

[0158] Generate and send a donation certificate

[0159] The server verifies that the donation was successful and generates a donation certificate, which is created in PDF format and sent to the user's email address.

[0160] Input: Payment completion information

[0161] Output: Donation certificate (PDF), notification to user that submission is complete

[0162] Through these processing steps, users can easily and efficiently make donations to areas of interest.

[0163] (Application example 1)

[0164] 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."

[0165] In conventional donation systems, many users had to spend a lot of time and effort identifying a donation destination that suited their area of ​​interest and obtaining the appropriate information. Furthermore, the complicated donation process often hindered donation behavior. This created the problem of not raising awareness of social contribution and making it difficult to promote donation activities. The present invention aims to solve these problems by providing a system that allows users to more easily and quickly find a donation destination that suits their area of ​​interest and efficiently complete the donation process.

[0166] 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.

[0167] In this invention, the server includes means for collecting user-related information, means for using a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, means for providing specific information about the donation organizations recommended by the generative AI model, means for carrying out donation procedures using mobile payment technology, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to easily find donation organizations that match their areas of interest and quickly complete their donations.

[0168] "User related information" refers to information entered by the user, such as name, email address, and areas of interest.

[0169] "Using a generative AI model that recommends appropriate donation organizations based on areas of interest" means that the generative AI model identifies and recommends the most suitable donation organizations based on the user's area of ​​interest data.

[0170] "Specific information about the donation organizations recommended by the generative AI model" refers to detailed information such as the donation organization's activities, past performance, and donation methods.

[0171] "Completing donation transactions using mobile payment technology" refers to technology that allows donation payments to be made using a smartphone app or other mobile device.

[0172] "Generating a donation certificate and providing it to the user after the donation is completed" refers to confirming that the donation has been completed, creating a certificate as proof of that, and providing it to the user.

[0173] The present invention relates to a system that recommends appropriate donation organizations based on the user's areas of interest and simplifies the donation process, and is composed of a server, a terminal, and a generative AI model.

[0174] Server Operation

[0175] Receiving user information

[0176] The server receives information entered by the user from the device, such as name, email address, areas of interest, etc. This information collection allows the server to accumulate information related to the user.

[0177] Recommendations based on generative AI models

[0178] The server uses a generative AI model to research appropriate donation organizations based on the user's areas of interest. This generative AI model has been trained in advance using training data, and analyzes the user's input data based on prompts to recommend the most suitable donation organizations. Examples of prompts include:

[0179] "If a user has 'environmental protection' as an area of ​​interest, which charitable organizations would be recommended?"

[0180] Providing more information

[0181] The server aggregates and documents specific information about the charity recommended by the generative AI model, including its activities, past performance, donation methods, etc. These details are then sent to the device for review by the user.

[0182] Managing donation processes

[0183] When a user decides to donate to the charity of their choice, the server processes the donation using mobile payment technology. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[0184] Device behavior

[0185] Providing an interface

[0186] The terminal provides an interface for the user to input and select information, such as a screen for selecting areas of interest and a screen for confirming recommended donation organizations.

[0187] Sending and receiving information

[0188] The information entered by the user is sent to the server, and the recommendation list and detailed information received from the server are displayed at the same time, improving the convenience of the user when actually using the service.

[0189] Completing the donation process

[0190] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server and the donation is officially confirmed.

[0191] User behavior

[0192] Entering information and selecting options

[0193] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the server to recommend organizations that match the user's interests.

[0194] Check the recommendation list

[0195] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[0196] Complete the donation process

[0197] Users can make donations to the charity of their choice, complete the payment through a mobile payment app, and receive a donation certificate, which can be downloaded and saved in PDF format.

[0198] Specific examples

[0199] For example, if a user wants to donate to an environmental protection cause, they open the app on their smartphone and select "environmental protection" as their area of ​​interest. This information is sent to the server, and the generative AI model researches suitable donation organizations and generates a list of recommendations. The user selects "Environmental Protection Organization A" from the displayed list and completes the donation process using mobile payment technology. If the donation is successful, the server can generate a donation certificate and provide it to the user.

[0200] In this way, the present invention is a system that supports users in efficiently carrying out donation activities.

[0201] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0202] Step 1:

[0203] Entering user information

[0204] The user uses the device's interface to enter their name, email address, and interests, which are then sent by the device to the server.

[0205] Input: User's name, email address, and interests

[0206] Output: User information data sent to the server

[0207] Step 2:

[0208] Receiving and storing user information

[0209] The server receives the user information sent from the terminal and stores it in a virtual database, which is the data required for subsequent processing.

[0210] Input: User information data sent from the device

[0211] Output: User information stored in a virtual database

[0212] Step 3:

[0213] Recommendations based on generative AI models

[0214] The server uses a generative AI model based on the stored user information to generate a list of recommendations. The generative AI model creates a list of donation organizations based on the user's areas of interest, and the AI ​​uses prompts to suggest the most suitable organizations.

[0215] Input: User information stored in a virtual database

[0216] Data processing: Inference processing using generative AI models

[0217] Output: Recommendation list

[0218] Specific behavior:

[0219] The server inputs prompts such as "If the user's area of ​​interest is 'environmental protection,' which donation organizations would be recommended?" into the generative AI model and generates a list of recommendations.

[0220] Step 4:

[0221] Submit your recommendation list and details

[0222] The server sends the generated recommendation list and detailed information about each charity (such as activities, past performance, and donation methods) to the terminal, allowing the user to select an appropriate charity.

[0223] Input: Generated recommendation list and detailed information

[0224] Output: Recommendation list and details sent to your device

[0225] Specific behavior:

[0226] The server documents the recommendation list and sends it to the user's device.

[0227] Step 5:

[0228] Choosing a donation destination

[0229] The user uses the interface on the terminal to check the recommendation list and detailed information sent from the server and select a donation destination, which is then sent to the server by the terminal.

[0230] Input: Recommendation list and detailed information received from the server

[0231] Output: Selected donation information (sent from device to server)

[0232] Specific behavior:

[0233] Users scroll through the screen, check the information for each charity, and then select the charity of their choice.

[0234] Step 6:

[0235] Completing the donation process

[0236] Once the user has decided on a donation recipient, the device will launch a mobile payment app and prompt them to enter the donation amount and payment method. The entered payment information is then sent to the server, where the actual payment is processed.

[0237] Input: Donation information, donation amount, payment method

[0238] Data processing: Payment processing via mobile payment apps

[0239] Output: Payment completion notification

[0240] Specific behavior:

[0241] Users enter the donation amount and make the payment via a mobile payment app.

[0242] Step 7:

[0243] Generate and provide a donation certificate

[0244] The server confirms that the payment has been completed and generates a donation certificate, which is then sent to the user's device, where the user can download and save it.

[0245] Input: Payment completion notification

[0246] Data processing: Generating donation certificates

[0247] Output: Generated donation certificate (sent to terminal)

[0248] Specific behavior:

[0249] The server generates a donation certificate in PDF format and sends it to the device, where the user can open it, save it, or print it.

[0250] 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.

[0251] The present invention relates to a system that uses a generative AI model to recommend appropriate donation organizations based on a user's areas of interest, and optimizes the donation experience by analyzing the user's emotional state. This system operates through the interaction of a server, a terminal, and a user.

[0252] Server Operation

[0253] 1. Receiving and storing user information

[0254] The server receives information entered by the user from their device, such as their name, email address, and areas of interest, and stores this information in a database.

[0255] 2. Recommendations using generative AI models

[0256] The server uses a generative AI model to list appropriate donation organizations based on the user's areas of interest and past donation history, and the generative AI model pulls relevant information from a database and updates it accordingly.

[0257] 3. Emotion Recognition by Emotion Engine

[0258] The server uses an emotion engine to analyze the user's emotional state. The emotion engine obtains and analyzes emotion data from the user's facial expressions and voice input, for example, to determine whether the user is excited or calm.

[0259] 4. Providing more information

[0260] The server documents detailed information for each donation organization recommended by the generative AI model and sends it to the user's device in the most optimal format, taking into account the analysis results of the emotion engine.

[0261] 5. Managing donation procedures

[0262] If the user decides to donate, the server will connect to the mobile payment app and manage the donation process. Once the payment is complete, the server will generate a donation certificate and provide it to the user.

[0263] Device behavior

[0264] 1. Providing an interface

[0265] The terminal provides an interface for user input and selection, allowing the user to select areas of interest and view information about charitable organizations.

[0266] 2. Sending and receiving information

[0267] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[0268] 3. Acquiring Emotion Data

[0269] The device captures the user's facial expressions and voice input through a camera and microphone, and sends the data to a server where it is analyzed by an emotion engine.

[0270] 4. Donation Procedures

[0271] When a user makes a donation, the device launches a mobile payment app and assists the user in entering the payment method and amount, which is then sent to the server.

[0272] User behavior

[0273] 1. Information entry and selection

[0274] Users enter their name, email address, and interests through the device's interface, which then uses the camera and microphone to provide emotional data.

[0275] 2. Review and select from the recommended list

[0276] The user checks the list of recommendations received from the server and the details of each donation organization. The information displayed is based on the analysis results of the emotion engine and is presented in the most appropriate format for the user.

[0277] 3. Completing the donation process

[0278] Users select a donation recipient, enter the donation amount, and complete the payment. The donation is officially completed once payment is made through the mobile payment app.

[0279] 4. Preservation of donation certificates

[0280] Once the donation is complete, the server will send you a donation certificate, which you can then download and save or print as needed.

[0281] Specific examples

[0282] As a concrete example, consider the case where a user makes a donation to an educational support activity. The following is the flow of the process.

[0283] 1. Entering the user's initial information

[0284] The user launches the app and selects that they are interested in "educational support." Emotional data is collected from the user's facial expressions and voice and sent to the server.

[0285] 2. Recommending donation organizations using generative AI models and emotion engines

[0286] The server uses a generative AI model and an emotion engine to list appropriate educational support organizations and send detailed information taking into account the user's emotional state.

[0287] 3. Confirm details and decide to donate

[0288] The device displays a list of recommendations and detailed information, and the user becomes interested in "Educational Support Organization B" and decides to donate.

[0289] 4. Completing the donation process

[0290] The user enters the donation amount and makes a donation of 5,000 yen using a mobile payment app. If the payment is successful, the information is sent to the server.

[0291] 5. Receiving a donation certificate

[0292] The server generates a donation certificate and sends it to the device, which the user downloads and saves.

[0293] As described above, this system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[0294] The processing flow will be explained below.

[0295] Step 1:

[0296] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[0297] Step 2:

[0298] The terminal sends the user's input information to the server, which stores the received information in a database and sends a registration completion notification to the terminal.

[0299] Step 3:

[0300] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[0301] Step 4:

[0302] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[0303] Step 5:

[0304] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[0305] Step 6:

[0306] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[0307] Step 7:

[0308] Once the user selects a charity, the device uses an emotion engine to acquire emotional data such as the user's facial expressions and voice. This data is then sent to the server and analyzed by the emotion engine.

[0309] Step 8:

[0310] The server uses an emotion engine to analyze the user's emotional state and adjusts how the donation organization's details are displayed based on the user's emotional state, for example, highlighting key information if the user is excited.

[0311] Step 9:

[0312] The user enters the donation amount and clicks the donate button. The device launches the mobile payment app and prompts for payment information.

[0313] Step 10:

[0314] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[0315] Step 11:

[0316] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[0317] Step 12:

[0318] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[0319] This concludes the specific processing flow of our system, which combines an emotion engine, enabling users to enjoy a personalized donation experience that takes into account their emotional state.

[0320] Example 2

[0321] 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."

[0322] Existing donation systems do not take into account the user's emotional state when selecting appropriate donation organizations based on the user's areas of interest, resulting in a disorganized donation experience and making it difficult to donate efficiently. Furthermore, the complicated donation procedures and the provision of donation certificates make it difficult for users to complete the process, which prevents them from fully encouraging donation behavior.

[0323] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting the user's areas of interest, means for recommending appropriate organizations using a generative AI model, means for using an emotion engine to analyze the user's emotional state, means for providing detailed information about the recommended donation organizations, means for completing the donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide a personalized donation experience that takes the user's emotional state into consideration, thereby improving the efficiency of the donation process and encouraging donation behavior.

[0324] "User interests" refers to the areas or topics in which a user is particularly interested when making a donation.

[0325] "Generative AI models" are algorithms and systems that use artificial intelligence techniques to recommend appropriate organizations based on a user's areas of interest.

[0326] "Emotion engine" refers to software or hardware for analyzing a user's emotional state, including technology that recognizes emotions using the user's facial expressions and voice data.

[0327] A "mobile payment app" is an application that allows users to complete online payments using mobile devices such as smartphones and tablets.

[0328] A "donation certificate" is a document that certifies that a donation has been completed and contains details of the donation (donation amount, donation recipient, date and time, etc.).

[0329] MODE FOR CARRYING OUT THE INVENTION

[0330] The present invention is a system that uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, and analyzes the user's emotional state to optimize the donation experience. This system operates through the interaction of a server, a terminal, and the user.

[0331] Server Operation

[0332] The server uses the following hardware and software to implement this system:

[0333] Hardware: Server itself (including CPU, memory, and storage)

[0334] Software: MySQL database, generative AI model (e.g., GPT-4), emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API)

[0335] Specifically, the server does the following:

[0336] 1. Receiving and storing user information

[0337] The server receives information entered by the user on their device, such as their name, email address, and areas of interest, and stores this information in a MySQL database.

[0338] 2. Recommendations using generative AI models

[0339] The server retrieves the user's areas of interest and past donation history from the database and uses a generative AI model (e.g., GPT-4) to list appropriate donation organizations. An example of a prompt used here is, "The user is interested in supporting education. What organizations do you recommend for donation?"

[0340] 3. Emotion Recognition by Emotion Engine

[0341] The server receives the user's facial expression and voice data sent from the device and sends it to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API). The emotion engine's analysis results are used to determine the user's emotional state. For example, if the emotion engine determines the user's emotion to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[0342] 4. Providing more information

[0343] The server builds detailed information about the organizations recommended by the generative AI model and emotion engine and sends it to the device. The detailed information is collected using SQL queries from a database, including the organization's activities and impact.

[0344] 5. Managing donation procedures

[0345] When a user decides to donate and enters the amount on the terminal, the server connects to the mobile payment app to process the donation. After the payment is completed, a donation certificate is generated and provided to the user.

[0346] Device behavior

[0347] The device operates using the following hardware and software:

[0348] Hardware: Mobile devices (smartphones, tablets, etc.) equipped with a camera, microphone, CPU, memory, storage, etc.

[0349] Software: Mobile applications, mobile payment apps

[0350] Specifically, the terminal works as follows:

[0351] 1. Providing an interface

[0352] The device provides an interface for users to enter their name, email address, and interests, with text boxes and drop-down menus.

[0353] 2. Sending and receiving information

[0354] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[0355] 3. Acquiring Emotion Data

[0356] The device uses a camera and microphone to capture the user's facial expressions and voice data, and sends that data to a server where it is analyzed by an emotion engine.

[0357] 4. Donation Procedures

[0358] The user enters the donation amount, launches the mobile payment app, and sends the payment information to the server. Once the payment is complete, the user can download and save or print a donation certificate.

[0359] User behavior

[0360] Users use the system as follows:

[0361] 1. Information entry and selection

[0362] Through the device's interface, users enter their name, email address, and areas of interest, and provide emotional data using the camera and microphone.

[0363] 2. Review and select from the recommended list

[0364] The user checks the recommended list received from the server and the detailed information of each donation organization, and selects the organization to which the user wishes to donate.

[0365] 3. Completing the donation process

[0366] The user enters the donation amount and completes the payment using a mobile payment app.

[0367] 4. Preservation of donation certificates

[0368] After your donation is complete, you will receive a donation certificate from the server, which you can download, save, or print as needed.

[0369] As described above, this system uses a generative AI model and an emotion engine to recommend donation organizations based on the user's areas of interest, providing users with a personalized donation experience, which helps users make donations efficiently and contributes to promoting donation behavior.

[0370] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0371] Step 1:

[0372] Entering and submitting user information

[0373] Input: A user types their name, email address, or interests into a device.

[0374] Specific operation: The user uses the device interface to enter the required information for each form. For example, the user enters "Yamada Taro" as the name, "taro@example.com" as the email address, and "educational support" as the area of ​​interest.

[0375] Output: The device checks the entered information and sends it to the server.

[0376] Step 2:

[0377] Receiving and storing user information

[0378] Input: User information sent from your device (name, email address, interests).

[0379] Specific behavior: The server receives the information and performs initial validation to ensure the data format is correct. For example, it checks whether the email address format is correct. Then it executes an SQL query (e.g., "INSERT INTO user_info (name, email, interest) VALUES ('Yamada Taro', 'taro@example.com', 'Education Support')") to save the information to the MySQL database.

[0380] Output: User information is saved in the database.

[0381] Step 3:

[0382] Recommendations based on generative AI models

[0383] Input: User's areas of interest and past donation history retrieved from our database.

[0384] Specific operation: The server generates a prompt based on the user's areas of interest and inputs it into a generative AI model (e.g., GPT-4). Example prompt: "The user is interested in supporting education. What organizations do you recommend for donation?" The output returned by the model is analyzed and a list of appropriate donation organizations is generated.

[0385] Output: A list of recommended donor organizations.

[0386] Step 4:

[0387] Emotion recognition by emotion engine

[0388] Input: The user's facial and voice data sent from the device.

[0389] Specific operation: The server sends the received data to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API) and receives emotion data in response. For example, if the emotion engine judges the response to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[0390] Output: Analysis of the user's emotional state.

[0391] Step 5:

[0392] Providing more information

[0393] Input: A list of recommended donation organizations and the results of an analysis of the user's emotional state.

[0394] What it does: The server retrieves details of each donation organization from the database and formats them according to the user's emotional state. For example, it executes the SQL query "SELECT FROM donation_organizations WHERE id IN (1, 2, 3)" to retrieve the details. The format of the information is adjusted according to the user's emotional state (positive, negative, neutral).

[0395] Output: Optimized detailed information sent to the terminal.

[0396] Step 6:

[0397] Displaying Information

[0398] Input: Optimized details sent by the server.

[0399] What it does: The device receives the details and displays them in the interface. The user can review the information and choose the organization to donate to.

[0400] Output: The charitable organization selected by the user.

[0401] Step 7:

[0402] Completing the donation process

[0403] Input: User-selected charitable organization and donation amount.

[0404] Specific operation: The terminal launches the mobile payment app, and the user inputs the donation amount (for example, "5,000 yen"), presses the "Donate" button, and completes the payment. The payment information is sent to the server.

[0405] Output: Payment information is sent to the server and the donation is executed.

[0406] Step 8:

[0407] Generate and send a donation certificate

[0408] Input: Donation information after payment is completed.

[0409] Specific operation: The server generates a donation certificate and sends it to the user's email address. The certificate contains the user's name, the name of the donation organization, the donation amount, and the date and time. For example, "The donation certificate will state a donation of 5,000 yen to 'Yamada Taro' and 'Educational Support Organization B'."

[0410] Output: A donation certificate is provided to the user.

[0411] Through these processing steps, the system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[0412] (Application example 2)

[0413] 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."

[0414] While conventional donation systems had the ability to recommend organizations that matched a user's areas of interest, there were no systems that made recommendations that took into account the user's emotional state. Furthermore, there was a lack of sentiment analysis to optimize the donation experience, and the lack of real-time detailed information provided, which meant that users' motivation to donate and their satisfaction were not sufficiently improved.

[0415] The identification processing 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 collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for analyzing the user's emotional state, means for providing detailed information about the donation organizations recommended by the generative AI model based on the user's emotional state, means for acquiring emotional data using a camera and microphone, means for performing donation procedures using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide an optimized donation experience based on the user's emotional state.

[0416] "User Interests" are the topics or areas in which a donor has an interest or concern.

[0417] A "generative AI model" is a model that uses artificial intelligence to generate appropriate outputs based on specific input information.

[0418] "User emotional state" refers to the psychological and emotional state of the donor as estimated from their facial expressions and voice.

[0419] The "facial expression recognition API" is a program interface for analyzing a person's facial expressions from image data and estimating their emotional state.

[0420] The "Voice Emotion Analysis API" is a program interface for analyzing a speaker's emotional state from voice data.

[0421] "Detailed information" refers to specific information about the activities, achievements, and effects of the donation organization.

[0422] "Camera and microphone" refers to hardware devices that capture images and audio and use them as input data for sentiment analysis.

[0423] A "mobile payment app" is software that allows users to conduct online financial transactions using a smartphone.

[0424] A "donation process" is a series of steps that a user takes to transfer money to a donation organization of their choice.

[0425] A "certificate of donation" is an official document that certifies that a donation has been completed.

[0426] This invention relates to a system that recommends appropriate donation organizations that match a user's field of interest based on the user's emotional state. The specific system configuration and operation procedure are described below.

[0427] 1.Collection of User Information

[0428] The server provides a means to collect the user's interests. The user uses the smartphone interface to input their name, email address, and interests. They also use the camera and microphone to provide emotional data through facial expressions and voice.

[0429] 2. Recommendations using generative AI models

[0430] The server uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest. This generative AI model analyzes the user's areas of interest and past donation history to list relevant donation organizations. OpenAI GPT-4 is used as the generative AI model.

[0431] 3.Analysis of Emotional Data

[0432] The server analyzes the user's emotional state using an emotion engine. This emotion engine uses facial expression recognition APIs and voice emotion analysis APIs (e.g., Microsoft Azure Emotion API) to obtain and analyze emotional data from the user's facial expressions and voice.

[0433] 4. Provide detailed information

[0434] The server provides detailed information about the charity organizations recommended by the generative AI model. This detailed information is displayed in an optimal format based on the user's emotional state. Depending on the user's emotions, the server provides detailed information about the charity organization's activities, specific support activities, and achievements.

[0435] 5. Completing the donation process

[0436] If the user decides to donate, the server executes the donation process using a mobile payment app, which can be a common payment platform (e.g., Stripe or PayPal).

[0437] 6. Generate a donation certificate

[0438] Once the donation is complete, the server generates a donation certificate and provides it to the user. The donation certificate is generated electronically and can be received by email or other means.

[0439] Specific examples

[0440] For example, if a user is interested in "educational support," the system operates in the following steps:

[0441] 1. The user launches the smartphone app, inputs their interest in "educational support," and provides emotional data using the camera and microphone.

[0442] 2. The server uses the generative AI model to list donation organizations related to educational support, while simultaneously analyzing the user's emotional state using facial expression recognition APIs and voice emotion analysis APIs.

[0443] 3. The server provides the details of the charitable organizations listed by the generative AI model based on the analyzed emotional state. For example, if the user is in a positive emotional state, success stories and thank-you messages will be displayed.

[0444] 4. The user decides to donate 5,000 yen to a specific charity and completes the process using a mobile payment app.

[0445] 5. Once the payment is complete, the server generates a donation certificate and emails it to the user.

[0446] Example prompt sentence:

[0447] When a user enters "I'm interested in education" and provides emotional data (e.g., facial expression photo or voice message), the smartphone app uses a generative AI model to display a list of educational support organizations based on the user's emotional state, and also provides real-time information tailored to the user's specific preferences. For example, "organizations that provide learning materials" or "organizations that support teachers" are displayed. After the user selects a donation of 5,000 yen, the donation is completed through the Stripe payment system. A donation certificate is then sent to the user electronically.

[0448] This allows for a donation experience that is optimized based on the user's emotional state.

[0449] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0450] Step 1:

[0451] Users enter their interests and provide sentiment data

[0452] Users launch the smartphone application and enter their name, email address, and areas of interest, while simultaneously providing facial expressions and voice messages using the camera and microphone. This data is then transmitted from the device to the server.

[0453] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[0454] Output: User information and emotion data sent to the server

[0455] Step 2:

[0456] Storing user information and emotional data

[0457] The server stores the received user's name, email address, and areas of interest in a database, and also processes the facial expression photo and voice message into data to be sent to the emotion analysis API.

[0458] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[0459] Output: User information stored in the database, data for the sentiment analysis API

[0460] Step 3:

[0461] Sentiment Data Analysis

[0462] The server uses the facial expression recognition API and the voice emotion analysis API to obtain emotional data from the user's facial expression photo and voice message, and analyzes the user's emotional state.

[0463] Input: facial expression photo, voice message

[0464] Output: User emotional state as an analysis result of the sentiment analysis API

[0465] Step 4:

[0466] Recommending a charitable organization

[0467] The server uses a generative AI model based on the user's areas of interest and emotional state to list relevant donation organizations. The generative AI model analyzes the user's areas of interest and past donation history to recommend appropriate organizations.

[0468] Input: User's areas of interest, emotional state

[0469] Output: List of recommended donors

[0470] Step 5:

[0471] Providing more information

[0472] The server retrieves detailed information about the charity recommended by the generative AI model and sends it to the device in an optimal format based on the user's emotional state. For example, if the user is in a positive emotional state, success stories and messages of gratitude will be highlighted.

[0473] Input: List of recommended charitable organizations, user's emotional state

[0474] Output: Details of the donation organization sent to the user's device

[0475] Step 6:

[0476] Completing the donation process

[0477] If the user decides to donate, the terminal will launch the mobile payment app, and the user will input the donation amount. The payment information will be sent to the server, which will then process the donation through the payment platform.

[0478] Input: User's donation choice, donation amount

[0479] Output: Payment completion information, donation process execution

[0480] Step 7:

[0481] Generate and provide a donation certificate

[0482] Once the donation process is complete, the server generates a donation certificate and provides it to the user via email or download link.

[0483] Input: Payment completion information

[0484] Output: Donation certificate provided to the user

[0485] Through these steps, the system is able to provide an optimal donation experience based on the user's emotional state.

[0486] 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.

[0487] 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.

[0488] 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.

[0489] [Second embodiment]

[0490] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0491] 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.

[0492] 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).

[0493] 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.

[0494] 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.

[0495] 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).

[0496] 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.

[0497] 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.

[0498] 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.

[0499] 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.

[0500] 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.

[0501] 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."

[0502] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. This system is made up of a server, a terminal, and a series of operations performed by the user.

[0503] Server Operation

[0504] 1. Receiving User Information

[0505] The server receives information entered by the user from the device, such as name, email address, and areas of interest.

[0506] 2. Recommendations using generative AI models

[0507] The server uses a generative AI model to research suitable donation organizations based on the user's areas of interest. The generative AI model then pulls relevant information from a database and lists the best donation recipients for the user.

[0508] 3. Providing detailed information

[0509] The server documents detailed information about the recommended donation organization (such as its activities, donation methods, and past performance) and sends it to the terminal.

[0510] 4. Managing donation procedures

[0511] When a user decides to donate, the server connects to the mobile payment app to initiate the donation process. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[0512] Device behavior

[0513] 1. Providing an interface

[0514] The device provides an interface for the user to enter input or make selections, such as displaying a screen that allows the user to select areas of interest or identify charitable organizations.

[0515] 2. Sending and receiving information

[0516] The information entered by the user is sent to the server, and at the same time, the recommendation list and detailed information received from the server are displayed, providing an interface that is easy for the user to use.

[0517] 3. Completing the donation process

[0518] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server.

[0519] User behavior

[0520] 1. Entering information and making selections

[0521] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the system to recommend organizations that match their interests.

[0522] 2. Check the recommendation list

[0523] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[0524] 3. Completing the donation process

[0525] Donate to the charity of your choice. Complete the payment through the mobile payment app to formalize your donation. Once the payment is complete, users will receive a donation certificate that they can save or print.

[0526] Specific examples

[0527] As a concrete example, consider the case where a user makes a donation to an environmental protection cause. The following is the sequence of events:

[0528] 1. Entering the user's initial information

[0529] A user turns on their device and selects "environmental protection" as an area of ​​interest. This information is sent to the server.

[0530] 2. Generative AI model to recommend donation organizations

[0531] The server uses a generative AI model to obtain information on multiple organizations engaged in environmental protection activities and generate a recommendation list.

[0532] 3. Submit and confirm your details

[0533] The server sends the generated recommendation list to the terminal, where the user can review the list, check the details of the "Environmental Protection Organization A" that interests the user, and finally decide to donate.

[0534] 4. Completing the donation process

[0535] The user launches the mobile payment app, enters their payment information, and makes a donation of 2,000 yen. If the payment is successful, the information is sent to the server.

[0536] 5. Receiving a donation certificate

[0537] The server generates a donation certificate and sends it to the device, which the user can download and save as a PDF.

[0538] As described above, this system provides users with a means to make donations easily and quickly, thereby promoting donation activities and raising awareness of social contribution.

[0539] The processing flow will be explained below.

[0540] Step 1:

[0541] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[0542] Step 2:

[0543] The terminal sends the user's input information to the server, which stores the received information in a database and sends a notification to the terminal that registration is complete.

[0544] Step 3:

[0545] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[0546] Step 4:

[0547] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[0548] Step 5:

[0549] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[0550] Step 6:

[0551] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[0552] Step 7:

[0553] When the user selects a charity, the terminal displays a screen for inputting the donation amount for that charity. The user inputs the donation amount and clicks the Donate button.

[0554] Step 8:

[0555] When the device detects a click on the donation button, it launches the mobile payment app, and the user selects a payment method (e.g., credit card, electronic money, etc.) and completes the payment.

[0556] Step 9:

[0557] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[0558] Step 10:

[0559] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[0560] Step 11:

[0561] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[0562] The above is the specific process flow of this system, which allows users to make donations based on their areas of interest quickly and easily.

[0563] Example 1

[0564] 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."

[0565] Conventional donation systems have the problem that it is difficult for users to find a donation recipient that suits their area of ​​interest, and the complicated donation process prevents users from donating. In particular, users are discouraged from donating because they have to search multiple websites to get detailed information, and fees incurred during the donation process.

[0566] 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.

[0567] In this invention, the server includes means for collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for inputting a prompt sentence into the generative AI model to list multiple donation organizations, means for providing detailed information about the donation organizations recommended by the generative AI model, means for carrying out a donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to donate to areas of interest easily and efficiently.

[0568] "User Interests" refers to the activities or themes that are of particular interest to the user who wishes to donate.

[0569] A "generative AI model" refers to an artificial intelligence algorithm that recommends appropriate donation organizations based on input data and prompts.

[0570] A "prompt" refers to a question or instruction entered into a generative AI model to obtain a specific recommendation result.

[0571] A "donor organization" refers to a nonprofit organization that receives funds to support a specific social issue or cause.

[0572] "Detailed information" refers to information necessary for users to decide to donate, such as the activities of the donation organization, how to donate, and past performance.

[0573] "Mobile payment app" refers to a software application that allows users to make monetary payments using mobile devices such as smartphones and tablets.

[0574] "Donation Process" refers to the entire process of transferring funds to the donation organization selected by the User.

[0575] "Donation Certificate" means a document officially certifying that a User has made a Donation.

[0576] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. The system includes a server, a terminal, and a series of user operations.

[0577] First, the user enters their interests through the device's interface. Specifically, the user enters their name, email address, and the area of ​​interest they wish to support (e.g., "environmental protection") into the device, which then sends this information to the server. The device can be a smartphone, tablet, or PC, and uses an interface for inputting and receiving information.

[0578] Next, the server uses a generative AI model to recommend appropriate organizations to donate to based on the information received from the user. This generative AI model uses an advanced generative AI model (e.g., GPT-3) that uses natural language processing technology. By inputting a prompt sentence into the generative AI model, multiple organizations to donate to are listed. An example of this prompt sentence is, "I'm interested in environmental protection. Please recommend an appropriate organization for me to donate to."

[0579] The server then documents detailed information about the donation organizations listed by the generative AI model, including the activities of each organization, donation methods, past performance, etc. The documented details are sent from the server to the device, where the user can view them.

[0580] When the user checks the recommended list and decides to donate to a specific charity, a mobile payment app is launched. This mobile payment app can be, for example, PayPal or Stripe. The user enters the donation amount through the payment app and makes the payment. Once the payment is complete, the information is sent back to the server.

[0581] Finally, after the server confirms that the donation has been successfully completed, it will generate a donation certificate and send it to the user's email address, which the user can download and save.

[0582] As described above, the present invention provides a system that enables users to easily and quickly make donations to areas they are interested in. This aims to encourage donation activities and increase awareness of social contribution.

[0583] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0584] Step 1:

[0585] Enter initial information

[0586] The user inputs information such as their interests, name, and email address through the device's interface. This information is temporarily stored within the device. Specifically, the user selects the interest category "environmental protection."

[0587] Input: Interests, Name, Email Address

[0588] Output: User input information (JSON format)

[0589] Step 2:

[0590] Sending user information

[0591] The device sends the information entered by the user to the server, using the REST API to transmit data over the HTTPS protocol to ensure security.

[0592] Input: User input information

[0593] Output: User information sent to the server

[0594] Step 3:

[0595] Recommendations based on generative AI models

[0596] The server uses a generative AI model (e.g., GPT-3) based on the received user interest information to research appropriate donation organizations. Specifically, it performs the following operations:

[0597] The server generates the prompt "I'm interested in environmental protection. Please recommend a suitable organization for me to donate to."

[0598] Input the prompt sentence into the generative AI model

[0599] The generative AI model generates a list of donation organizations and returns that information to the server.

[0600] Input: User information, prompt text

[0601] Output: List of recommended donors

[0602] Step 4:

[0603] Submit your recommendation list and details

[0604] The server documents detailed information about the donation organizations listed by the generative AI model (such as their activities, donation methods, and past performance) and sends it to the device. A template engine is used for the documentation, which responds dynamically.

[0605] Input: List of recommended donors

[0606] Output: Documented donor details

[0607] Step 5:

[0608] Check the recommendation list

[0609] Users can check the recommended list on their device and view detailed information on organizations they are interested in, which will then help them select the best recipient.

[0610] Input: Documented donor details

[0611] Output: Selected donors

[0612] Step 6:

[0613] Start the donation process

[0614] The user selects the organization to which they wish to donate and clicks the "Start Donation" button. This action launches the mobile payment app, and they also enter the donation amount.

[0615] Input: Selected charity, donation amount

[0616] Output: Launch of mobile payment app

[0617] Step 7:

[0618] Managing donation processes

[0619] The terminal guides the user through the payment method selected by the user to complete the donation. The server connects to the mobile payment app and monitors the progress of the payment in real time.

[0620] Input: Donation amount, payment method

[0621] Output: Payment completion information

[0622] Step 8:

[0623] Generate and send a donation certificate

[0624] The server verifies that the donation was successful and generates a donation certificate, which is created in PDF format and sent to the user's email address.

[0625] Input: Payment completion information

[0626] Output: Donation certificate (PDF), notification to user that submission is complete

[0627] Through these processing steps, users can easily and efficiently make donations to areas of interest.

[0628] (Application example 1)

[0629] 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."

[0630] In conventional donation systems, many users had to spend a lot of time and effort identifying a donation destination that suited their area of ​​interest and obtaining the appropriate information. Furthermore, the complicated donation process often hindered donation behavior. This created the problem of not raising awareness of social contribution and making it difficult to promote donation activities. The present invention aims to solve these problems by providing a system that allows users to more easily and quickly find a donation destination that suits their area of ​​interest and efficiently complete the donation process.

[0631] 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.

[0632] In this invention, the server includes means for collecting user-related information, means for using a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, means for providing specific information about the donation organizations recommended by the generative AI model, means for carrying out donation procedures using mobile payment technology, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to easily find donation organizations that match their areas of interest and quickly complete their donations.

[0633] "User related information" refers to information entered by the user, such as name, email address, and areas of interest.

[0634] "Using a generative AI model that recommends appropriate donation organizations based on areas of interest" means that the generative AI model identifies and recommends the most suitable donation organizations based on the user's area of ​​interest data.

[0635] "Specific information about the donation organizations recommended by the generative AI model" refers to detailed information such as the donation organization's activities, past performance, and donation methods.

[0636] "Completing donation transactions using mobile payment technology" refers to technology that allows donation payments to be made using a smartphone app or other mobile device.

[0637] "Generating a donation certificate and providing it to the user after the donation is completed" refers to confirming that the donation has been completed, creating a certificate as proof of that, and providing it to the user.

[0638] The present invention relates to a system that recommends appropriate donation organizations based on the user's areas of interest and simplifies the donation process, and is composed of a server, a terminal, and a generative AI model.

[0639] Server Operation

[0640] Receiving user information

[0641] The server receives information entered by the user from the device, such as name, email address, areas of interest, etc. This information collection allows the server to accumulate information related to the user.

[0642] Recommendations based on generative AI models

[0643] The server uses a generative AI model to research appropriate donation organizations based on the user's areas of interest. This generative AI model has been trained in advance using training data, and analyzes the user's input data based on prompts to recommend the most suitable donation organizations. Examples of prompts include:

[0644] "If a user has 'environmental protection' as an area of ​​interest, which charitable organizations would be recommended?"

[0645] Providing more information

[0646] The server aggregates and documents specific information about the charity recommended by the generative AI model, including its activities, past performance, donation methods, etc. These details are then sent to the device for review by the user.

[0647] Managing donation processes

[0648] When a user decides to donate to the charity of their choice, the server processes the donation using mobile payment technology. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[0649] Device behavior

[0650] Providing an interface

[0651] The terminal provides an interface for the user to input and select information, such as a screen for selecting areas of interest and a screen for confirming recommended donation organizations.

[0652] Sending and receiving information

[0653] The information entered by the user is sent to the server, and the recommendation list and detailed information received from the server are displayed at the same time, improving the convenience of the user when actually using the service.

[0654] Completing the donation process

[0655] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server and the donation is officially confirmed.

[0656] User behavior

[0657] Entering information and selecting options

[0658] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the server to recommend organizations that match the user's interests.

[0659] Check the recommendation list

[0660] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[0661] Complete the donation process

[0662] Users can make donations to the charity of their choice, complete the payment through a mobile payment app, and receive a donation certificate, which can be downloaded and saved in PDF format.

[0663] Specific examples

[0664] For example, if a user wants to donate to an environmental protection cause, they open the app on their smartphone and select "environmental protection" as their area of ​​interest. This information is sent to the server, and the generative AI model researches suitable donation organizations and generates a list of recommendations. The user selects "Environmental Protection Organization A" from the displayed list and completes the donation process using mobile payment technology. If the donation is successful, the server can generate a donation certificate and provide it to the user.

[0665] In this way, the present invention is a system that supports users in efficiently carrying out donation activities.

[0666] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0667] Step 1:

[0668] Entering user information

[0669] The user uses the device's interface to enter their name, email address, and interests, which are then sent by the device to the server.

[0670] Input: User's name, email address, and interests

[0671] Output: User information data sent to the server

[0672] Step 2:

[0673] Receiving and storing user information

[0674] The server receives the user information sent from the terminal and stores it in a virtual database, which is the data required for subsequent processing.

[0675] Input: User information data sent from the device

[0676] Output: User information stored in a virtual database

[0677] Step 3:

[0678] Recommendations based on generative AI models

[0679] The server uses a generative AI model based on the stored user information to generate a list of recommendations. The generative AI model creates a list of donation organizations based on the user's areas of interest, and the AI ​​uses prompts to suggest the most suitable organizations.

[0680] Input: User information stored in a virtual database

[0681] Data processing: Inference processing using generative AI models

[0682] Output: Recommendation list

[0683] Specific behavior:

[0684] The server inputs prompts such as "If the user's area of ​​interest is 'environmental protection,' which donation organizations would be recommended?" into the generative AI model and generates a list of recommendations.

[0685] Step 4:

[0686] Submit your recommendation list and details

[0687] The server sends the generated recommendation list and detailed information about each charity (such as activities, past performance, and donation methods) to the terminal, allowing the user to select an appropriate charity.

[0688] Input: Generated recommendation list and detailed information

[0689] Output: Recommendation list and details sent to your device

[0690] Specific behavior:

[0691] The server documents the recommendation list and sends it to the user's device.

[0692] Step 5:

[0693] Choosing a donation destination

[0694] The user uses the interface on the terminal to check the recommendation list and detailed information sent from the server and select a donation destination, which is then sent to the server by the terminal.

[0695] Input: Recommendation list and detailed information received from the server

[0696] Output: Selected donation information (sent from device to server)

[0697] Specific behavior:

[0698] Users scroll through the screen, check the information for each charity, and then select the charity of their choice.

[0699] Step 6:

[0700] Completing the donation process

[0701] Once the user has decided on a donation recipient, the device will launch a mobile payment app and prompt them to enter the donation amount and payment method. The entered payment information is then sent to the server, where the actual payment is processed.

[0702] Input: Donation information, donation amount, payment method

[0703] Data processing: Payment processing via mobile payment apps

[0704] Output: Payment completion notification

[0705] Specific behavior:

[0706] Users enter the donation amount and make the payment via a mobile payment app.

[0707] Step 7:

[0708] Generate and provide a donation certificate

[0709] The server confirms that the payment has been completed and generates a donation certificate, which is then sent to the user's device, where the user can download and save it.

[0710] Input: Payment completion notification

[0711] Data processing: Generating donation certificates

[0712] Output: Generated donation certificate (sent to terminal)

[0713] Specific behavior:

[0714] The server generates a donation certificate in PDF format and sends it to the device, where the user can open it, save it, or print it.

[0715] 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.

[0716] The present invention relates to a system that uses a generative AI model to recommend appropriate donation organizations based on a user's areas of interest, and optimizes the donation experience by analyzing the user's emotional state. This system operates through the interaction of a server, a terminal, and a user.

[0717] Server Operation

[0718] 1. Receiving and storing user information

[0719] The server receives information entered by the user from their device, such as their name, email address, and areas of interest, and stores this information in a database.

[0720] 2. Recommendations using generative AI models

[0721] The server uses a generative AI model to list appropriate donation organizations based on the user's areas of interest and past donation history, and the generative AI model pulls relevant information from a database and updates it accordingly.

[0722] 3. Emotion Recognition by Emotion Engine

[0723] The server uses an emotion engine to analyze the user's emotional state. The emotion engine obtains and analyzes emotion data from the user's facial expressions and voice input, for example, to determine whether the user is excited or calm.

[0724] 4. Providing more information

[0725] The server documents detailed information for each donation organization recommended by the generative AI model and sends it to the user's device in the most optimal format, taking into account the analysis results of the emotion engine.

[0726] 5. Managing donation procedures

[0727] If the user decides to donate, the server will connect to the mobile payment app and manage the donation process. Once the payment is complete, the server will generate a donation certificate and provide it to the user.

[0728] Device behavior

[0729] 1. Providing an interface

[0730] The terminal provides an interface for user input and selection, allowing the user to select areas of interest and view information about charitable organizations.

[0731] 2. Sending and receiving information

[0732] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[0733] 3. Acquiring Emotion Data

[0734] The device captures the user's facial expressions and voice input through a camera and microphone, and sends the data to a server where it is analyzed by an emotion engine.

[0735] 4. Donation Procedures

[0736] When a user makes a donation, the device launches a mobile payment app and assists the user in entering the payment method and amount, which is then sent to the server.

[0737] User behavior

[0738] 1. Information entry and selection

[0739] Users enter their name, email address, and interests through the device's interface, which then uses the camera and microphone to provide emotional data.

[0740] 2. Review and select from the recommended list

[0741] The user checks the list of recommendations received from the server and the details of each donation organization. The information displayed is based on the analysis results of the emotion engine and is presented in the most appropriate format for the user.

[0742] 3. Completing the donation process

[0743] Users select a donation recipient, enter the donation amount, and complete the payment. The donation is officially completed once payment is made through the mobile payment app.

[0744] 4. Preservation of donation certificates

[0745] Once the donation is complete, the server will send you a donation certificate, which you can then download and save or print as needed.

[0746] Specific examples

[0747] As a concrete example, consider the case where a user makes a donation to an educational support activity. The following is the flow of the process.

[0748] 1. Entering the user's initial information

[0749] The user launches the app and selects that they are interested in "educational support." Emotional data is collected from the user's facial expressions and voice and sent to the server.

[0750] 2. Recommending donation organizations using generative AI models and emotion engines

[0751] The server uses a generative AI model and an emotion engine to list appropriate educational support organizations and send detailed information taking into account the user's emotional state.

[0752] 3. Confirm details and decide to donate

[0753] The device displays a list of recommendations and detailed information, and the user becomes interested in "Educational Support Organization B" and decides to donate.

[0754] 4. Completing the donation process

[0755] The user enters the donation amount and makes a donation of 5,000 yen using a mobile payment app. If the payment is successful, the information is sent to the server.

[0756] 5. Receiving a donation certificate

[0757] The server generates a donation certificate and sends it to the device, which the user downloads and saves.

[0758] As described above, this system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[0759] The processing flow will be explained below.

[0760] Step 1:

[0761] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[0762] Step 2:

[0763] The terminal sends the user's input information to the server, which stores the received information in a database and sends a registration completion notification to the terminal.

[0764] Step 3:

[0765] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[0766] Step 4:

[0767] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[0768] Step 5:

[0769] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[0770] Step 6:

[0771] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[0772] Step 7:

[0773] Once the user selects a charity, the device uses an emotion engine to acquire emotional data such as the user's facial expressions and voice. This data is then sent to the server and analyzed by the emotion engine.

[0774] Step 8:

[0775] The server uses an emotion engine to analyze the user's emotional state and adjusts how the donation organization's details are displayed based on the user's emotional state, for example, highlighting key information if the user is excited.

[0776] Step 9:

[0777] The user enters the donation amount and clicks the donate button. The device launches the mobile payment app and prompts for payment information.

[0778] Step 10:

[0779] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[0780] Step 11:

[0781] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[0782] Step 12:

[0783] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[0784] This concludes the specific processing flow of our system, which combines an emotion engine, enabling users to enjoy a personalized donation experience that takes into account their emotional state.

[0785] Example 2

[0786] 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."

[0787] Existing donation systems do not take into account the user's emotional state when selecting appropriate donation organizations based on the user's areas of interest, resulting in a disorganized donation experience and making it difficult to donate efficiently. Furthermore, the complicated donation procedures and the provision of donation certificates make it difficult for users to complete the process, which prevents them from fully encouraging donation behavior.

[0788] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting the user's areas of interest, means for recommending appropriate organizations using a generative AI model, means for using an emotion engine to analyze the user's emotional state, means for providing detailed information about the recommended donation organizations, means for completing the donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide a personalized donation experience that takes the user's emotional state into consideration, thereby improving the efficiency of the donation process and encouraging donation behavior.

[0789] "User interests" refers to the areas or topics in which a user is particularly interested when making a donation.

[0790] "Generative AI models" are algorithms and systems that use artificial intelligence techniques to recommend appropriate organizations based on a user's areas of interest.

[0791] "Emotion engine" refers to software or hardware for analyzing a user's emotional state, including technology that recognizes emotions using the user's facial expressions and voice data.

[0792] A "mobile payment app" is an application that allows users to complete online payments using mobile devices such as smartphones and tablets.

[0793] A "donation certificate" is a document that certifies that a donation has been completed and contains details of the donation (donation amount, donation recipient, date and time, etc.).

[0794] MODE FOR CARRYING OUT THE INVENTION

[0795] The present invention is a system that uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, and analyzes the user's emotional state to optimize the donation experience. This system operates through the interaction of a server, a terminal, and the user.

[0796] Server Operation

[0797] The server uses the following hardware and software to implement this system:

[0798] Hardware: Server itself (including CPU, memory, and storage)

[0799] Software: MySQL database, generative AI model (e.g., GPT-4), emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API)

[0800] Specifically, the server does the following:

[0801] 1. Receiving and storing user information

[0802] The server receives information entered by the user on their device, such as their name, email address, and areas of interest, and stores this information in a MySQL database.

[0803] 2. Recommendations using generative AI models

[0804] The server retrieves the user's areas of interest and past donation history from the database and uses a generative AI model (e.g., GPT-4) to list appropriate donation organizations. An example of a prompt used here is, "The user is interested in supporting education. What organizations do you recommend for donation?"

[0805] 3. Emotion Recognition by Emotion Engine

[0806] The server receives the user's facial expression and voice data sent from the device and sends it to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API). The emotion engine's analysis results are used to determine the user's emotional state. For example, if the emotion engine determines the user's emotion to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[0807] 4. Providing more information

[0808] The server builds detailed information about the organizations recommended by the generative AI model and emotion engine and sends it to the device. The detailed information is collected using SQL queries from a database, including the organization's activities and impact.

[0809] 5. Managing donation procedures

[0810] When a user decides to donate and enters the amount on the terminal, the server connects to the mobile payment app to process the donation. After the payment is completed, a donation certificate is generated and provided to the user.

[0811] Device behavior

[0812] The device operates using the following hardware and software:

[0813] Hardware: Mobile devices (smartphones, tablets, etc.) equipped with a camera, microphone, CPU, memory, storage, etc.

[0814] Software: Mobile applications, mobile payment apps

[0815] Specifically, the terminal works as follows:

[0816] 1. Providing an interface

[0817] The device provides an interface for users to enter their name, email address, and interests, with text boxes and drop-down menus.

[0818] 2. Sending and receiving information

[0819] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[0820] 3. Acquiring Emotion Data

[0821] The device uses a camera and microphone to capture the user's facial expressions and voice data, and sends that data to a server where it is analyzed by an emotion engine.

[0822] 4. Donation Procedures

[0823] The user enters the donation amount, launches the mobile payment app, and sends the payment information to the server. Once the payment is complete, the user can download and save or print a donation certificate.

[0824] User behavior

[0825] Users use the system as follows:

[0826] 1. Information entry and selection

[0827] Through the device's interface, users enter their name, email address, and areas of interest, and provide emotional data using the camera and microphone.

[0828] 2. Review and select from the recommended list

[0829] The user checks the recommended list received from the server and the detailed information of each donation organization, and selects the organization to which the user wishes to donate.

[0830] 3. Completing the donation process

[0831] The user enters the donation amount and completes the payment using a mobile payment app.

[0832] 4. Preservation of donation certificates

[0833] After your donation is complete, you will receive a donation certificate from the server, which you can download, save, or print as needed.

[0834] As described above, this system uses a generative AI model and an emotion engine to recommend donation organizations based on the user's areas of interest, providing users with a personalized donation experience, which helps users make donations efficiently and contributes to promoting donation behavior.

[0835] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0836] Step 1:

[0837] Entering and submitting user information

[0838] Input: A user types their name, email address, or interests into a device.

[0839] Specific operation: The user uses the device interface to enter the required information for each form. For example, the user enters "Yamada Taro" as the name, "taro@example.com" as the email address, and "educational support" as the area of ​​interest.

[0840] Output: The device checks the entered information and sends it to the server.

[0841] Step 2:

[0842] Receiving and storing user information

[0843] Input: User information sent from your device (name, email address, interests).

[0844] Specific behavior: The server receives the information and performs initial validation to ensure the data format is correct. For example, it checks whether the email address format is correct. Then it executes an SQL query (e.g., "INSERT INTO user_info (name, email, interest) VALUES ('Yamada Taro', 'taro@example.com', 'Education Support')") to save the information to the MySQL database.

[0845] Output: User information is saved in the database.

[0846] Step 3:

[0847] Recommendations based on generative AI models

[0848] Input: User's areas of interest and past donation history retrieved from our database.

[0849] Specific operation: The server generates a prompt based on the user's areas of interest and inputs it into a generative AI model (e.g., GPT-4). Example prompt: "The user is interested in supporting education. What organizations do you recommend for donation?" The output returned by the model is analyzed and a list of appropriate donation organizations is generated.

[0850] Output: A list of recommended donor organizations.

[0851] Step 4:

[0852] Emotion recognition by emotion engine

[0853] Input: The user's facial and voice data sent from the device.

[0854] Specific operation: The server sends the received data to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API) and receives emotion data in response. For example, if the emotion engine judges the response to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[0855] Output: Analysis of the user's emotional state.

[0856] Step 5:

[0857] Providing more information

[0858] Input: A list of recommended donation organizations and the results of an analysis of the user's emotional state.

[0859] What it does: The server retrieves details of each donation organization from the database and formats them according to the user's emotional state. For example, it executes the SQL query "SELECT FROM donation_organizations WHERE id IN (1, 2, 3)" to retrieve the details. The format of the information is adjusted according to the user's emotional state (positive, negative, neutral).

[0860] Output: Optimized detailed information sent to the terminal.

[0861] Step 6:

[0862] Displaying Information

[0863] Input: Optimized details sent by the server.

[0864] What it does: The device receives the details and displays them in the interface. The user can review the information and choose the organization to donate to.

[0865] Output: The charitable organization selected by the user.

[0866] Step 7:

[0867] Completing the donation process

[0868] Input: User-selected charitable organization and donation amount.

[0869] Specific operation: The terminal launches the mobile payment app, and the user inputs the donation amount (for example, "5,000 yen"), presses the "Donate" button, and completes the payment. The payment information is sent to the server.

[0870] Output: Payment information is sent to the server and the donation is executed.

[0871] Step 8:

[0872] Generate and send a donation certificate

[0873] Input: Donation information after payment is completed.

[0874] Specific operation: The server generates a donation certificate and sends it to the user's email address. The certificate contains the user's name, the name of the donation organization, the donation amount, and the date and time. For example, "The donation certificate will state a donation of 5,000 yen to 'Yamada Taro' and 'Educational Support Organization B'."

[0875] Output: A donation certificate is provided to the user.

[0876] Through these processing steps, the system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[0877] (Application example 2)

[0878] 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."

[0879] While conventional donation systems had the ability to recommend organizations that matched a user's areas of interest, there were no systems that made recommendations that took into account the user's emotional state. Furthermore, there was a lack of sentiment analysis to optimize the donation experience, and the lack of real-time detailed information provided, which meant that users' motivation to donate and their satisfaction were not sufficiently improved.

[0880] The identification processing 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 collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for analyzing the user's emotional state, means for providing detailed information about the donation organizations recommended by the generative AI model based on the user's emotional state, means for acquiring emotional data using a camera and microphone, means for performing donation procedures using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide an optimized donation experience based on the user's emotional state.

[0881] "User Interests" are the topics or areas in which a donor has an interest or concern.

[0882] A "generative AI model" is a model that uses artificial intelligence to generate appropriate outputs based on specific input information.

[0883] "User emotional state" refers to the psychological and emotional state of the donor as estimated from their facial expressions and voice.

[0884] The "facial expression recognition API" is a program interface for analyzing a person's facial expressions from image data and estimating their emotional state.

[0885] The "Voice Emotion Analysis API" is a program interface for analyzing a speaker's emotional state from voice data.

[0886] "Detailed information" refers to specific information about the activities, achievements, and effects of the donation organization.

[0887] "Camera and microphone" refers to hardware devices that capture images and audio and use them as input data for sentiment analysis.

[0888] A "mobile payment app" is software that allows users to conduct online financial transactions using a smartphone.

[0889] A "donation process" is a series of steps that a user takes to transfer money to a donation organization of their choice.

[0890] A "certificate of donation" is an official document that certifies that a donation has been completed.

[0891] This invention relates to a system that recommends appropriate donation organizations that match a user's field of interest based on the user's emotional state. The specific system configuration and operation procedure are described below.

[0892] 1.Collection of User Information

[0893] The server provides a means to collect the user's interests. The user uses the smartphone interface to input their name, email address, and interests. They also use the camera and microphone to provide emotional data through facial expressions and voice.

[0894] 2. Recommendations using generative AI models

[0895] The server uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest. This generative AI model analyzes the user's areas of interest and past donation history to list relevant donation organizations. OpenAI GPT-4 is used as the generative AI model.

[0896] 3.Analysis of Emotional Data

[0897] The server analyzes the user's emotional state using an emotion engine. This emotion engine uses facial expression recognition APIs and voice emotion analysis APIs (e.g., Microsoft Azure Emotion API) to obtain and analyze emotional data from the user's facial expressions and voice.

[0898] 4. Provide detailed information

[0899] The server provides detailed information about the charity organizations recommended by the generative AI model. This detailed information is displayed in an optimal format based on the user's emotional state. Depending on the user's emotions, the server provides detailed information about the charity organization's activities, specific support activities, and achievements.

[0900] 5. Completing the donation process

[0901] If the user decides to donate, the server executes the donation process using a mobile payment app, which can be a common payment platform (e.g., Stripe or PayPal).

[0902] 6. Generate a donation certificate

[0903] Once the donation is complete, the server generates a donation certificate and provides it to the user. The donation certificate is generated electronically and can be received by email or other means.

[0904] Specific examples

[0905] For example, if a user is interested in "educational support," the system operates in the following steps:

[0906] 1. The user launches the smartphone app, inputs their interest in "educational support," and provides emotional data using the camera and microphone.

[0907] 2. The server uses the generative AI model to list donation organizations related to educational support, while simultaneously analyzing the user's emotional state using facial expression recognition APIs and voice emotion analysis APIs.

[0908] 3. The server provides the details of the charitable organizations listed by the generative AI model based on the analyzed emotional state. For example, if the user is in a positive emotional state, success stories and thank-you messages will be displayed.

[0909] 4. The user decides to donate 5,000 yen to a specific charity and completes the process using a mobile payment app.

[0910] 5. Once the payment is complete, the server generates a donation certificate and emails it to the user.

[0911] Example prompt sentence:

[0912] When a user enters "I'm interested in education" and provides emotional data (e.g., facial expression photo or voice message), the smartphone app uses a generative AI model to display a list of educational support organizations based on the user's emotional state, and also provides real-time information tailored to the user's specific preferences. For example, "organizations that provide learning materials" or "organizations that support teachers" are displayed. After the user selects a donation of 5,000 yen, the donation is completed through the Stripe payment system. A donation certificate is then sent to the user electronically.

[0913] This allows for a donation experience that is optimized based on the user's emotional state.

[0914] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0915] Step 1:

[0916] Users enter their interests and provide sentiment data

[0917] Users launch the smartphone application and enter their name, email address, and areas of interest, while simultaneously providing facial expressions and voice messages using the camera and microphone. This data is then transmitted from the device to the server.

[0918] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[0919] Output: User information and emotion data sent to the server

[0920] Step 2:

[0921] Storing user information and emotional data

[0922] The server stores the received user's name, email address, and areas of interest in a database, and also processes the facial expression photo and voice message into data to be sent to the emotion analysis API.

[0923] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[0924] Output: User information stored in the database, data for the sentiment analysis API

[0925] Step 3:

[0926] Sentiment Data Analysis

[0927] The server uses the facial expression recognition API and the voice emotion analysis API to obtain emotional data from the user's facial expression photo and voice message, and analyzes the user's emotional state.

[0928] Input: facial expression photo, voice message

[0929] Output: User emotional state as an analysis result of the sentiment analysis API

[0930] Step 4:

[0931] Recommending a charitable organization

[0932] The server uses a generative AI model based on the user's areas of interest and emotional state to list relevant donation organizations. The generative AI model analyzes the user's areas of interest and past donation history to recommend appropriate organizations.

[0933] Input: User's areas of interest, emotional state

[0934] Output: List of recommended donors

[0935] Step 5:

[0936] Providing more information

[0937] The server retrieves detailed information about the charity recommended by the generative AI model and sends it to the device in an optimal format based on the user's emotional state. For example, if the user is in a positive emotional state, success stories and messages of gratitude will be highlighted.

[0938] Input: List of recommended charitable organizations, user's emotional state

[0939] Output: Details of the donation organization sent to the user's device

[0940] Step 6:

[0941] Completing the donation process

[0942] If the user decides to donate, the terminal will launch the mobile payment app, and the user will input the donation amount. The payment information will be sent to the server, which will then process the donation through the payment platform.

[0943] Input: User's donation choice, donation amount

[0944] Output: Payment completion information, donation process execution

[0945] Step 7:

[0946] Generate and provide a donation certificate

[0947] Once the donation process is complete, the server generates a donation certificate and provides it to the user via email or download link.

[0948] Input: Payment completion information

[0949] Output: Donation certificate provided to the user

[0950] Through these steps, the system is able to provide an optimal donation experience based on the user's emotional state.

[0951] 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.

[0952] 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.

[0953] 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.

[0954] [Third embodiment]

[0955] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0956] 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.

[0957] 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).

[0958] 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.

[0959] 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.

[0960] 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).

[0961] 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.

[0962] 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.

[0963] 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.

[0964] 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.

[0965] 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.

[0966] 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."

[0967] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. This system is made up of a server, a terminal, and a series of operations performed by the user.

[0968] Server Operation

[0969] 1. Receiving User Information

[0970] The server receives information entered by the user from the device, such as name, email address, and areas of interest.

[0971] 2. Recommendations using generative AI models

[0972] The server uses a generative AI model to research suitable donation organizations based on the user's areas of interest. The generative AI model then pulls relevant information from a database and lists the best donation recipients for the user.

[0973] 3. Providing detailed information

[0974] The server documents detailed information about the recommended donation organization (such as its activities, donation methods, and past performance) and sends it to the terminal.

[0975] 4. Managing donation procedures

[0976] When a user decides to donate, the server connects to the mobile payment app to initiate the donation process. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[0977] Device behavior

[0978] 1. Providing an interface

[0979] The device provides an interface for the user to enter input or make selections, such as displaying a screen that allows the user to select areas of interest or identify charitable organizations.

[0980] 2. Sending and receiving information

[0981] The information entered by the user is sent to the server, and at the same time, the recommendation list and detailed information received from the server are displayed, providing an interface that is easy for the user to use.

[0982] 3. Completing the donation process

[0983] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server.

[0984] User behavior

[0985] 1. Entering information and making selections

[0986] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the system to recommend organizations that match their interests.

[0987] 2. Check the recommendation list

[0988] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[0989] 3. Completing the donation process

[0990] Donate to the charity of your choice. Complete the payment through the mobile payment app to formalize your donation. Once the payment is complete, users will receive a donation certificate that they can save or print.

[0991] Specific examples

[0992] As a concrete example, consider the case where a user makes a donation to an environmental protection cause. The following is the sequence of events:

[0993] 1. Entering the user's initial information

[0994] A user turns on their device and selects "environmental protection" as an area of ​​interest. This information is sent to the server.

[0995] 2. Generative AI model to recommend donation organizations

[0996] The server uses a generative AI model to obtain information on multiple organizations engaged in environmental protection activities and generate a recommendation list.

[0997] 3. Submit and confirm your details

[0998] The server sends the generated recommendation list to the terminal, where the user can review the list, check the details of the "Environmental Protection Organization A" that interests the user, and finally decide to donate.

[0999] 4. Completing the donation process

[1000] The user launches the mobile payment app, enters their payment information, and makes a donation of 2,000 yen. If the payment is successful, the information is sent to the server.

[1001] 5. Receiving a donation certificate

[1002] The server generates a donation certificate and sends it to the device, which the user can download and save as a PDF.

[1003] As described above, this system provides users with a means to make donations easily and quickly, thereby promoting donation activities and raising awareness of social contribution.

[1004] The processing flow will be explained below.

[1005] Step 1:

[1006] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[1007] Step 2:

[1008] The terminal sends the user's input information to the server, which stores the received information in a database and sends a notification to the terminal that registration is complete.

[1009] Step 3:

[1010] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[1011] Step 4:

[1012] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[1013] Step 5:

[1014] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[1015] Step 6:

[1016] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[1017] Step 7:

[1018] When the user selects a charity, the terminal displays a screen for inputting the donation amount for that charity. The user inputs the donation amount and clicks the Donate button.

[1019] Step 8:

[1020] When the device detects a click on the donation button, it launches the mobile payment app, and the user selects a payment method (e.g., credit card, electronic money, etc.) and completes the payment.

[1021] Step 9:

[1022] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[1023] Step 10:

[1024] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[1025] Step 11:

[1026] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[1027] The above is the specific process flow of this system, which allows users to make donations based on their areas of interest quickly and easily.

[1028] Example 1

[1029] 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."

[1030] Conventional donation systems have the problem that it is difficult for users to find a donation recipient that suits their area of ​​interest, and the complicated donation process prevents users from donating. In particular, users are discouraged from donating because they have to search multiple websites to get detailed information, and fees incurred during the donation process.

[1031] 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.

[1032] In this invention, the server includes means for collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for inputting a prompt sentence into the generative AI model to list multiple donation organizations, means for providing detailed information about the donation organizations recommended by the generative AI model, means for carrying out a donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to donate to areas of interest easily and efficiently.

[1033] "User Interests" refers to the activities or themes that are of particular interest to the user who wishes to donate.

[1034] A "generative AI model" refers to an artificial intelligence algorithm that recommends appropriate donation organizations based on input data and prompts.

[1035] A "prompt" refers to a question or instruction entered into a generative AI model to obtain a specific recommendation result.

[1036] A "donor organization" refers to a nonprofit organization that receives funds to support a specific social issue or cause.

[1037] "Detailed information" refers to information necessary for users to decide to donate, such as the activities of the donation organization, how to donate, and past performance.

[1038] "Mobile payment app" refers to a software application that allows users to make monetary payments using mobile devices such as smartphones and tablets.

[1039] "Donation Process" refers to the entire process of transferring funds to the donation organization selected by the User.

[1040] "Donation Certificate" means a document officially certifying that a User has made a Donation.

[1041] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. The system includes a server, a terminal, and a series of user operations.

[1042] First, the user enters their interests through the device's interface. Specifically, the user enters their name, email address, and the area of ​​interest they wish to support (e.g., "environmental protection") into the device, which then sends this information to the server. The device can be a smartphone, tablet, or PC, and uses an interface for inputting and receiving information.

[1043] Next, the server uses a generative AI model to recommend appropriate organizations to donate to based on the information received from the user. This generative AI model uses an advanced generative AI model (e.g., GPT-3) that uses natural language processing technology. By inputting a prompt sentence into the generative AI model, multiple organizations to donate to are listed. An example of this prompt sentence is, "I'm interested in environmental protection. Please recommend an appropriate organization for me to donate to."

[1044] The server then documents detailed information about the donation organizations listed by the generative AI model, including the activities of each organization, donation methods, past performance, etc. The documented details are sent from the server to the device, where the user can view them.

[1045] When the user checks the recommended list and decides to donate to a specific charity, a mobile payment app is launched. This mobile payment app can be, for example, PayPal or Stripe. The user enters the donation amount through the payment app and makes the payment. Once the payment is complete, the information is sent back to the server.

[1046] Finally, after the server confirms that the donation has been successfully completed, it will generate a donation certificate and send it to the user's email address, which the user can download and save.

[1047] As described above, the present invention provides a system that enables users to easily and quickly make donations to areas they are interested in. This aims to encourage donation activities and increase awareness of social contribution.

[1048] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1049] Step 1:

[1050] Enter initial information

[1051] The user inputs information such as their interests, name, and email address through the device's interface. This information is temporarily stored within the device. Specifically, the user selects the interest category "environmental protection."

[1052] Input: Interests, Name, Email Address

[1053] Output: User input information (JSON format)

[1054] Step 2:

[1055] Sending user information

[1056] The device sends the information entered by the user to the server, using the REST API to transmit data over the HTTPS protocol to ensure security.

[1057] Input: User input information

[1058] Output: User information sent to the server

[1059] Step 3:

[1060] Recommendations based on generative AI models

[1061] The server uses a generative AI model (e.g., GPT-3) based on the received user interest information to research appropriate donation organizations. Specifically, it performs the following operations:

[1062] The server generates the prompt "I'm interested in environmental protection. Please recommend a suitable organization for me to donate to."

[1063] Input the prompt sentence into the generative AI model

[1064] The generative AI model generates a list of donation organizations and returns that information to the server.

[1065] Input: User information, prompt text

[1066] Output: List of recommended donors

[1067] Step 4:

[1068] Submit your recommendation list and details

[1069] The server documents detailed information about the donation organizations listed by the generative AI model (such as their activities, donation methods, and past performance) and sends it to the device. A template engine is used for the documentation, which responds dynamically.

[1070] Input: List of recommended donors

[1071] Output: Documented donor details

[1072] Step 5:

[1073] Check the recommendation list

[1074] Users can check the recommended list on their device and view detailed information on organizations they are interested in, which will then help them select the best recipient.

[1075] Input: Documented donor details

[1076] Output: Selected donors

[1077] Step 6:

[1078] Start the donation process

[1079] The user selects the organization to which they wish to donate and clicks the "Start Donation" button. This action launches the mobile payment app, and they also enter the donation amount.

[1080] Input: Selected charity, donation amount

[1081] Output: Launch of mobile payment app

[1082] Step 7:

[1083] Managing donation processes

[1084] The terminal guides the user through the payment method selected by the user to complete the donation. The server connects to the mobile payment app and monitors the progress of the payment in real time.

[1085] Input: Donation amount, payment method

[1086] Output: Payment completion information

[1087] Step 8:

[1088] Generate and send a donation certificate

[1089] The server verifies that the donation was successful and generates a donation certificate, which is created in PDF format and sent to the user's email address.

[1090] Input: Payment completion information

[1091] Output: Donation certificate (PDF), notification to user that submission is complete

[1092] Through these processing steps, users can easily and efficiently make donations to areas of interest.

[1093] (Application example 1)

[1094] 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."

[1095] In conventional donation systems, many users had to spend a lot of time and effort identifying a donation destination that suited their area of ​​interest and obtaining the appropriate information. Furthermore, the complicated donation process often hindered donation behavior. This created the problem of not raising awareness of social contribution and making it difficult to promote donation activities. The present invention aims to solve these problems by providing a system that allows users to more easily and quickly find a donation destination that suits their area of ​​interest and efficiently complete the donation process.

[1096] 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.

[1097] In this invention, the server includes means for collecting user-related information, means for using a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, means for providing specific information about the donation organizations recommended by the generative AI model, means for carrying out donation procedures using mobile payment technology, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to easily find donation organizations that match their areas of interest and quickly complete their donations.

[1098] "User related information" refers to information entered by the user, such as name, email address, and areas of interest.

[1099] "Using a generative AI model that recommends appropriate donation organizations based on areas of interest" means that the generative AI model identifies and recommends the most suitable donation organizations based on the user's area of ​​interest data.

[1100] "Specific information about the donation organizations recommended by the generative AI model" refers to detailed information such as the donation organization's activities, past performance, and donation methods.

[1101] "Completing donation transactions using mobile payment technology" refers to technology that allows donation payments to be made using a smartphone app or other mobile device.

[1102] "Generating a donation certificate and providing it to the user after the donation is completed" refers to confirming that the donation has been completed, creating a certificate as proof of that, and providing it to the user.

[1103] The present invention relates to a system that recommends appropriate donation organizations based on the user's areas of interest and simplifies the donation process, and is composed of a server, a terminal, and a generative AI model.

[1104] Server Operation

[1105] Receiving user information

[1106] The server receives information entered by the user from the device, such as name, email address, areas of interest, etc. This information collection allows the server to accumulate information related to the user.

[1107] Recommendations based on generative AI models

[1108] The server uses a generative AI model to research appropriate donation organizations based on the user's areas of interest. This generative AI model has been trained in advance using training data, and analyzes the user's input data based on prompts to recommend the most suitable donation organizations. Examples of prompts include:

[1109] "If a user has 'environmental protection' as an area of ​​interest, which charitable organizations would be recommended?"

[1110] Providing more information

[1111] The server aggregates and documents specific information about the charity recommended by the generative AI model, including its activities, past performance, donation methods, etc. These details are then sent to the device for review by the user.

[1112] Managing donation processes

[1113] When a user decides to donate to the charity of their choice, the server processes the donation using mobile payment technology. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[1114] Device behavior

[1115] Providing an interface

[1116] The terminal provides an interface for the user to input and select information, such as a screen for selecting areas of interest and a screen for confirming recommended donation organizations.

[1117] Sending and receiving information

[1118] The information entered by the user is sent to the server, and the recommendation list and detailed information received from the server are displayed at the same time, improving the convenience of the user when actually using the service.

[1119] Completing the donation process

[1120] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server and the donation is officially confirmed.

[1121] User behavior

[1122] Entering information and selecting options

[1123] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the server to recommend organizations that match the user's interests.

[1124] Check the recommendation list

[1125] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[1126] Complete the donation process

[1127] Users can make donations to the charity of their choice, complete the payment through a mobile payment app, and receive a donation certificate, which can be downloaded and saved in PDF format.

[1128] Specific examples

[1129] For example, if a user wants to donate to an environmental protection cause, they open the app on their smartphone and select "environmental protection" as their area of ​​interest. This information is sent to the server, and the generative AI model researches suitable donation organizations and generates a list of recommendations. The user selects "Environmental Protection Organization A" from the displayed list and completes the donation process using mobile payment technology. If the donation is successful, the server can generate a donation certificate and provide it to the user.

[1130] In this way, the present invention is a system that supports users in efficiently carrying out donation activities.

[1131] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1132] Step 1:

[1133] Entering user information

[1134] The user uses the device's interface to enter their name, email address, and interests, which are then sent by the device to the server.

[1135] Input: User's name, email address, and interests

[1136] Output: User information data sent to the server

[1137] Step 2:

[1138] Receiving and storing user information

[1139] The server receives the user information sent from the terminal and stores it in a virtual database, which is the data required for subsequent processing.

[1140] Input: User information data sent from the device

[1141] Output: User information stored in a virtual database

[1142] Step 3:

[1143] Recommendations based on generative AI models

[1144] The server uses a generative AI model based on the stored user information to generate a list of recommendations. The generative AI model creates a list of donation organizations based on the user's areas of interest, and the AI ​​uses prompts to suggest the most suitable organizations.

[1145] Input: User information stored in a virtual database

[1146] Data processing: Inference processing using generative AI models

[1147] Output: Recommendation list

[1148] Specific behavior:

[1149] The server inputs prompts such as "If the user's area of ​​interest is 'environmental protection,' which donation organizations would be recommended?" into the generative AI model and generates a list of recommendations.

[1150] Step 4:

[1151] Submit your recommendation list and details

[1152] The server sends the generated recommendation list and detailed information about each charity (such as activities, past performance, and donation methods) to the terminal, allowing the user to select an appropriate charity.

[1153] Input: Generated recommendation list and detailed information

[1154] Output: Recommendation list and details sent to your device

[1155] Specific behavior:

[1156] The server documents the recommendation list and sends it to the user's device.

[1157] Step 5:

[1158] Choosing a donation destination

[1159] The user uses the interface on the terminal to check the recommendation list and detailed information sent from the server and select a donation destination, which is then sent to the server by the terminal.

[1160] Input: Recommendation list and detailed information received from the server

[1161] Output: Selected donation information (sent from device to server)

[1162] Specific behavior:

[1163] Users scroll through the screen, check the information for each charity, and then select the charity of their choice.

[1164] Step 6:

[1165] Completing the donation process

[1166] Once the user has decided on a donation recipient, the device will launch a mobile payment app and prompt them to enter the donation amount and payment method. The entered payment information is then sent to the server, where the actual payment is processed.

[1167] Input: Donation information, donation amount, payment method

[1168] Data processing: Payment processing via mobile payment apps

[1169] Output: Payment completion notification

[1170] Specific behavior:

[1171] Users enter the donation amount and make the payment via a mobile payment app.

[1172] Step 7:

[1173] Generate and provide a donation certificate

[1174] The server confirms that the payment has been completed and generates a donation certificate, which is then sent to the user's device, where the user can download and save it.

[1175] Input: Payment completion notification

[1176] Data processing: Generating donation certificates

[1177] Output: Generated donation certificate (sent to terminal)

[1178] Specific behavior:

[1179] The server generates a donation certificate in PDF format and sends it to the device, where the user can open it, save it, or print it.

[1180] 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.

[1181] The present invention relates to a system that uses a generative AI model to recommend appropriate donation organizations based on a user's areas of interest, and optimizes the donation experience by analyzing the user's emotional state. This system operates through the interaction of a server, a terminal, and a user.

[1182] Server Operation

[1183] 1. Receiving and storing user information

[1184] The server receives information entered by the user from their device, such as their name, email address, and areas of interest, and stores this information in a database.

[1185] 2. Recommendations using generative AI models

[1186] The server uses a generative AI model to list appropriate donation organizations based on the user's areas of interest and past donation history, and the generative AI model pulls relevant information from a database and updates it accordingly.

[1187] 3. Emotion Recognition by Emotion Engine

[1188] The server uses an emotion engine to analyze the user's emotional state. The emotion engine obtains and analyzes emotion data from the user's facial expressions and voice input, for example, to determine whether the user is excited or calm.

[1189] 4. Providing more information

[1190] The server documents detailed information for each donation organization recommended by the generative AI model and sends it to the user's device in the most optimal format, taking into account the analysis results of the emotion engine.

[1191] 5. Managing donation procedures

[1192] If the user decides to donate, the server will connect to the mobile payment app and manage the donation process. Once the payment is complete, the server will generate a donation certificate and provide it to the user.

[1193] Device behavior

[1194] 1. Providing an interface

[1195] The terminal provides an interface for user input and selection, allowing the user to select areas of interest and view information about charitable organizations.

[1196] 2. Sending and receiving information

[1197] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[1198] 3. Acquiring Emotion Data

[1199] The device captures the user's facial expressions and voice input through a camera and microphone, and sends the data to a server where it is analyzed by an emotion engine.

[1200] 4. Donation Procedures

[1201] When a user makes a donation, the device launches a mobile payment app and assists the user in entering the payment method and amount, which is then sent to the server.

[1202] User behavior

[1203] 1. Information entry and selection

[1204] Users enter their name, email address, and interests through the device's interface, which then uses the camera and microphone to provide emotional data.

[1205] 2. Review and select from the recommended list

[1206] The user checks the list of recommendations received from the server and the details of each donation organization. The information displayed is based on the analysis results of the emotion engine and is presented in the most appropriate format for the user.

[1207] 3. Completing the donation process

[1208] Users select a donation recipient, enter the donation amount, and complete the payment. The donation is officially completed once payment is made through the mobile payment app.

[1209] 4. Preservation of donation certificates

[1210] Once the donation is complete, the server will send you a donation certificate, which you can then download and save or print as needed.

[1211] Specific examples

[1212] As a concrete example, consider the case where a user makes a donation to an educational support activity. The following is the flow of the process.

[1213] 1. Entering the user's initial information

[1214] The user launches the app and selects that they are interested in "educational support." Emotional data is collected from the user's facial expressions and voice and sent to the server.

[1215] 2. Recommending donation organizations using generative AI models and emotion engines

[1216] The server uses a generative AI model and an emotion engine to list appropriate educational support organizations and send detailed information taking into account the user's emotional state.

[1217] 3. Confirm details and decide to donate

[1218] The device displays a list of recommendations and detailed information, and the user becomes interested in "Educational Support Organization B" and decides to donate.

[1219] 4. Completing the donation process

[1220] The user enters the donation amount and makes a donation of 5,000 yen using a mobile payment app. If the payment is successful, the information is sent to the server.

[1221] 5. Receiving a donation certificate

[1222] The server generates a donation certificate and sends it to the device, which the user downloads and saves.

[1223] As described above, this system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[1224] The processing flow will be explained below.

[1225] Step 1:

[1226] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[1227] Step 2:

[1228] The terminal sends the user's input information to the server, which stores the received information in a database and sends a registration completion notification to the terminal.

[1229] Step 3:

[1230] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[1231] Step 4:

[1232] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[1233] Step 5:

[1234] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[1235] Step 6:

[1236] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[1237] Step 7:

[1238] Once the user selects a charity, the device uses an emotion engine to acquire emotional data such as the user's facial expressions and voice. This data is then sent to the server and analyzed by the emotion engine.

[1239] Step 8:

[1240] The server uses an emotion engine to analyze the user's emotional state and adjusts how the donation organization's details are displayed based on the user's emotional state, for example, highlighting key information if the user is excited.

[1241] Step 9:

[1242] The user enters the donation amount and clicks the donate button. The device launches the mobile payment app and prompts for payment information.

[1243] Step 10:

[1244] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[1245] Step 11:

[1246] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[1247] Step 12:

[1248] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[1249] This concludes the specific processing flow of our system, which combines an emotion engine, enabling users to enjoy a personalized donation experience that takes into account their emotional state.

[1250] Example 2

[1251] 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."

[1252] Existing donation systems do not take into account the user's emotional state when selecting appropriate donation organizations based on the user's areas of interest, resulting in a disorganized donation experience and making it difficult to donate efficiently. Furthermore, the complicated donation procedures and the provision of donation certificates make it difficult for users to complete the process, which prevents them from fully encouraging donation behavior.

[1253] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting the user's areas of interest, means for recommending appropriate organizations using a generative AI model, means for using an emotion engine to analyze the user's emotional state, means for providing detailed information about the recommended donation organizations, means for completing the donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide a personalized donation experience that takes the user's emotional state into consideration, thereby improving the efficiency of the donation process and encouraging donation behavior.

[1254] "User interests" refers to the areas or topics in which a user is particularly interested when making a donation.

[1255] "Generative AI models" are algorithms and systems that use artificial intelligence techniques to recommend appropriate organizations based on a user's areas of interest.

[1256] "Emotion engine" refers to software or hardware for analyzing a user's emotional state, including technology that recognizes emotions using the user's facial expressions and voice data.

[1257] A "mobile payment app" is an application that allows users to complete online payments using mobile devices such as smartphones and tablets.

[1258] A "donation certificate" is a document that certifies that a donation has been completed and contains details of the donation (donation amount, donation recipient, date and time, etc.).

[1259] MODE FOR CARRYING OUT THE INVENTION

[1260] The present invention is a system that uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, and analyzes the user's emotional state to optimize the donation experience. This system operates through the interaction of a server, a terminal, and the user.

[1261] Server Operation

[1262] The server uses the following hardware and software to implement this system:

[1263] Hardware: Server itself (including CPU, memory, and storage)

[1264] Software: MySQL database, generative AI model (e.g., GPT-4), emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API)

[1265] Specifically, the server does the following:

[1266] 1. Receiving and storing user information

[1267] The server receives information entered by the user on their device, such as their name, email address, and areas of interest, and stores this information in a MySQL database.

[1268] 2. Recommendations using generative AI models

[1269] The server retrieves the user's areas of interest and past donation history from the database and uses a generative AI model (e.g., GPT-4) to list appropriate donation organizations. An example of a prompt used here is, "The user is interested in supporting education. What organizations do you recommend for donation?"

[1270] 3. Emotion Recognition by Emotion Engine

[1271] The server receives the user's facial expression and voice data sent from the device and sends it to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API). The emotion engine's analysis results are used to determine the user's emotional state. For example, if the emotion engine determines the user's emotion to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[1272] 4. Providing more information

[1273] The server builds detailed information about the organizations recommended by the generative AI model and emotion engine and sends it to the device. The detailed information is collected using SQL queries from a database, including the organization's activities and impact.

[1274] 5. Managing donation procedures

[1275] When a user decides to donate and enters the amount on the terminal, the server connects to the mobile payment app to process the donation. After the payment is completed, a donation certificate is generated and provided to the user.

[1276] Device behavior

[1277] The device operates using the following hardware and software:

[1278] Hardware: Mobile devices (smartphones, tablets, etc.) equipped with a camera, microphone, CPU, memory, storage, etc.

[1279] Software: Mobile applications, mobile payment apps

[1280] Specifically, the terminal works as follows:

[1281] 1. Providing an interface

[1282] The device provides an interface for users to enter their name, email address, and interests, with text boxes and drop-down menus.

[1283] 2. Sending and receiving information

[1284] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[1285] 3. Acquiring Emotion Data

[1286] The device uses a camera and microphone to capture the user's facial expressions and voice data, and sends that data to a server where it is analyzed by an emotion engine.

[1287] 4. Donation Procedures

[1288] The user enters the donation amount, launches the mobile payment app, and sends the payment information to the server. Once the payment is complete, the user can download and save or print a donation certificate.

[1289] User behavior

[1290] Users use the system as follows:

[1291] 1. Information entry and selection

[1292] Through the device's interface, users enter their name, email address, and areas of interest, and provide emotional data using the camera and microphone.

[1293] 2. Review and select from the recommended list

[1294] The user checks the recommended list received from the server and the detailed information of each donation organization, and selects the organization to which the user wishes to donate.

[1295] 3. Completing the donation process

[1296] The user enters the donation amount and completes the payment using a mobile payment app.

[1297] 4. Preservation of donation certificates

[1298] After your donation is complete, you will receive a donation certificate from the server, which you can download, save, or print as needed.

[1299] As described above, this system uses a generative AI model and an emotion engine to recommend donation organizations based on the user's areas of interest, providing users with a personalized donation experience, which helps users make donations efficiently and contributes to promoting donation behavior.

[1300] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1301] Step 1:

[1302] Entering and submitting user information

[1303] Input: A user types their name, email address, or interests into a device.

[1304] Specific operation: The user uses the device interface to enter the required information for each form. For example, the user enters "Yamada Taro" as the name, "taro@example.com" as the email address, and "educational support" as the area of ​​interest.

[1305] Output: The device checks the entered information and sends it to the server.

[1306] Step 2:

[1307] Receiving and storing user information

[1308] Input: User information sent from your device (name, email address, interests).

[1309] Specific behavior: The server receives the information and performs initial validation to ensure the data format is correct. For example, it checks whether the email address format is correct. Then it executes an SQL query (e.g., "INSERT INTO user_info (name, email, interest) VALUES ('Yamada Taro', 'taro@example.com', 'Education Support')") to save the information to the MySQL database.

[1310] Output: User information is saved in the database.

[1311] Step 3:

[1312] Recommendations based on generative AI models

[1313] Input: User's areas of interest and past donation history retrieved from our database.

[1314] Specific operation: The server generates a prompt based on the user's areas of interest and inputs it into a generative AI model (e.g., GPT-4). Example prompt: "The user is interested in supporting education. What organizations do you recommend for donation?" The output returned by the model is analyzed and a list of appropriate donation organizations is generated.

[1315] Output: A list of recommended donor organizations.

[1316] Step 4:

[1317] Emotion recognition by emotion engine

[1318] Input: The user's facial and voice data sent from the device.

[1319] Specific operation: The server sends the received data to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API) and receives emotion data in response. For example, if the emotion engine judges the response to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[1320] Output: Analysis of the user's emotional state.

[1321] Step 5:

[1322] Providing more information

[1323] Input: A list of recommended donation organizations and the results of an analysis of the user's emotional state.

[1324] What it does: The server retrieves details of each donation organization from the database and formats them according to the user's emotional state. For example, it executes the SQL query "SELECT FROM donation_organizations WHERE id IN (1, 2, 3)" to retrieve the details. The format of the information is adjusted according to the user's emotional state (positive, negative, neutral).

[1325] Output: Optimized detailed information sent to the terminal.

[1326] Step 6:

[1327] Displaying Information

[1328] Input: Optimized details sent by the server.

[1329] What it does: The device receives the details and displays them in the interface. The user can review the information and choose the organization to donate to.

[1330] Output: The charitable organization selected by the user.

[1331] Step 7:

[1332] Completing the donation process

[1333] Input: User-selected charitable organization and donation amount.

[1334] Specific operation: The terminal launches the mobile payment app, and the user inputs the donation amount (for example, "5,000 yen"), presses the "Donate" button, and completes the payment. The payment information is sent to the server.

[1335] Output: Payment information is sent to the server and the donation is executed.

[1336] Step 8:

[1337] Generate and send a donation certificate

[1338] Input: Donation information after payment is completed.

[1339] Specific operation: The server generates a donation certificate and sends it to the user's email address. The certificate contains the user's name, the name of the donation organization, the donation amount, and the date and time. For example, "The donation certificate will state a donation of 5,000 yen to 'Yamada Taro' and 'Educational Support Organization B'."

[1340] Output: A donation certificate is provided to the user.

[1341] Through these processing steps, the system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[1342] (Application example 2)

[1343] 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."

[1344] While conventional donation systems had the ability to recommend organizations that matched a user's areas of interest, there were no systems that made recommendations that took into account the user's emotional state. Furthermore, there was a lack of sentiment analysis to optimize the donation experience, and the lack of real-time detailed information provided, which meant that users' motivation to donate and their satisfaction were not sufficiently improved.

[1345] The identification processing 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 collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for analyzing the user's emotional state, means for providing detailed information about the donation organizations recommended by the generative AI model based on the user's emotional state, means for acquiring emotional data using a camera and microphone, means for performing donation procedures using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide an optimized donation experience based on the user's emotional state.

[1346] "User Interests" are the topics or areas in which a donor has an interest or concern.

[1347] A "generative AI model" is a model that uses artificial intelligence to generate appropriate outputs based on specific input information.

[1348] "User emotional state" refers to the psychological and emotional state of the donor as estimated from their facial expressions and voice.

[1349] The "facial expression recognition API" is a program interface for analyzing a person's facial expressions from image data and estimating their emotional state.

[1350] The "Voice Emotion Analysis API" is a program interface for analyzing a speaker's emotional state from voice data.

[1351] "Detailed information" refers to specific information about the activities, achievements, and effects of the donation organization.

[1352] "Camera and microphone" refers to hardware devices that capture images and audio and use them as input data for sentiment analysis.

[1353] A "mobile payment app" is software that allows users to conduct online financial transactions using a smartphone.

[1354] A "donation process" is a series of steps that a user takes to transfer money to a donation organization of their choice.

[1355] A "certificate of donation" is an official document that certifies that a donation has been completed.

[1356] This invention relates to a system that recommends appropriate donation organizations that match a user's field of interest based on the user's emotional state. The specific system configuration and operation procedure are described below.

[1357] 1.Collection of User Information

[1358] The server provides a means to collect the user's interests. The user uses the smartphone interface to input their name, email address, and interests. They also use the camera and microphone to provide emotional data through facial expressions and voice.

[1359] 2. Recommendations using generative AI models

[1360] The server uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest. This generative AI model analyzes the user's areas of interest and past donation history to list relevant donation organizations. OpenAI GPT-4 is used as the generative AI model.

[1361] 3.Analysis of Emotional Data

[1362] The server analyzes the user's emotional state using an emotion engine. This emotion engine uses facial expression recognition APIs and voice emotion analysis APIs (e.g., Microsoft Azure Emotion API) to obtain and analyze emotional data from the user's facial expressions and voice.

[1363] 4. Provide detailed information

[1364] The server provides detailed information about the charity organizations recommended by the generative AI model. This detailed information is displayed in an optimal format based on the user's emotional state. Depending on the user's emotions, the server provides detailed information about the charity organization's activities, specific support activities, and achievements.

[1365] 5. Completing the donation process

[1366] If the user decides to donate, the server executes the donation process using a mobile payment app, which can be a common payment platform (e.g., Stripe or PayPal).

[1367] 6. Generate a donation certificate

[1368] Once the donation is complete, the server generates a donation certificate and provides it to the user. The donation certificate is generated electronically and can be received by email or other means.

[1369] Specific examples

[1370] For example, if a user is interested in "educational support," the system operates in the following steps:

[1371] 1. The user launches the smartphone app, inputs their interest in "educational support," and provides emotional data using the camera and microphone.

[1372] 2. The server uses the generative AI model to list donation organizations related to educational support, while simultaneously analyzing the user's emotional state using facial expression recognition APIs and voice emotion analysis APIs.

[1373] 3. The server provides the details of the charitable organizations listed by the generative AI model based on the analyzed emotional state. For example, if the user is in a positive emotional state, success stories and thank-you messages will be displayed.

[1374] 4. The user decides to donate 5,000 yen to a specific charity and completes the process using a mobile payment app.

[1375] 5. Once the payment is complete, the server generates a donation certificate and emails it to the user.

[1376] Example prompt sentence:

[1377] When a user enters "I'm interested in education" and provides emotional data (e.g., facial expression photo or voice message), the smartphone app uses a generative AI model to display a list of educational support organizations based on the user's emotional state, and also provides real-time information tailored to the user's specific preferences. For example, "organizations that provide learning materials" or "organizations that support teachers" are displayed. After the user selects a donation of 5,000 yen, the donation is completed through the Stripe payment system. A donation certificate is then sent to the user electronically.

[1378] This allows for a donation experience that is optimized based on the user's emotional state.

[1379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1380] Step 1:

[1381] Users enter their interests and provide sentiment data

[1382] Users launch the smartphone application and enter their name, email address, and areas of interest, while simultaneously providing facial expressions and voice messages using the camera and microphone. This data is then transmitted from the device to the server.

[1383] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[1384] Output: User information and emotion data sent to the server

[1385] Step 2:

[1386] Storing user information and emotional data

[1387] The server stores the received user's name, email address, and areas of interest in a database, and also processes the facial expression photo and voice message into data to be sent to the emotion analysis API.

[1388] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[1389] Output: User information stored in the database, data for the sentiment analysis API

[1390] Step 3:

[1391] Sentiment Data Analysis

[1392] The server uses the facial expression recognition API and the voice emotion analysis API to obtain emotional data from the user's facial expression photo and voice message, and analyzes the user's emotional state.

[1393] Input: facial expression photo, voice message

[1394] Output: User emotional state as an analysis result of the sentiment analysis API

[1395] Step 4:

[1396] Recommending a charitable organization

[1397] The server uses a generative AI model based on the user's areas of interest and emotional state to list relevant donation organizations. The generative AI model analyzes the user's areas of interest and past donation history to recommend appropriate organizations.

[1398] Input: User's areas of interest, emotional state

[1399] Output: List of recommended donors

[1400] Step 5:

[1401] Providing more information

[1402] The server retrieves detailed information about the charity recommended by the generative AI model and sends it to the device in an optimal format based on the user's emotional state. For example, if the user is in a positive emotional state, success stories and messages of gratitude will be highlighted.

[1403] Input: List of recommended charitable organizations, user's emotional state

[1404] Output: Details of the donation organization sent to the user's device

[1405] Step 6:

[1406] Completing the donation process

[1407] If the user decides to donate, the terminal will launch the mobile payment app, and the user will input the donation amount. The payment information will be sent to the server, which will then process the donation through the payment platform.

[1408] Input: User's donation choice, donation amount

[1409] Output: Payment completion information, donation process execution

[1410] Step 7:

[1411] Generate and provide a donation certificate

[1412] Once the donation process is complete, the server generates a donation certificate and provides it to the user via email or download link.

[1413] Input: Payment completion information

[1414] Output: Donation certificate provided to the user

[1415] Through these steps, the system is able to provide an optimal donation experience based on the user's emotional state.

[1416] 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.

[1417] 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.

[1418] 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.

[1419] [Fourth embodiment]

[1420] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1421] 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.

[1422] 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).

[1423] 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.

[1424] 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.

[1425] 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).

[1426] 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.

[1427] 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.

[1428] 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.

[1429] 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.

[1430] 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.

[1431] 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.

[1432] 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."

[1433] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. This system is made up of a server, a terminal, and a series of operations performed by the user.

[1434] Server Operation

[1435] 1. Receiving User Information

[1436] The server receives information entered by the user from the device, such as name, email address, and areas of interest.

[1437] 2. Recommendations using generative AI models

[1438] The server uses a generative AI model to research suitable donation organizations based on the user's areas of interest. The generative AI model then pulls relevant information from a database and lists the best donation recipients for the user.

[1439] 3. Providing detailed information

[1440] The server documents detailed information about the recommended donation organization (such as its activities, donation methods, and past performance) and sends it to the terminal.

[1441] 4. Managing donation procedures

[1442] When a user decides to donate, the server connects to the mobile payment app to initiate the donation process. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[1443] Device behavior

[1444] 1. Providing an interface

[1445] The device provides an interface for the user to enter input or make selections, such as displaying a screen that allows the user to select areas of interest or identify charitable organizations.

[1446] 2. Sending and receiving information

[1447] The information entered by the user is sent to the server, and at the same time, the recommendation list and detailed information received from the server are displayed, providing an interface that is easy for the user to use.

[1448] 3. Completing the donation process

[1449] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server.

[1450] User behavior

[1451] 1. Entering information and making selections

[1452] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the system to recommend organizations that match their interests.

[1453] 2. Check the recommendation list

[1454] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[1455] 3. Completing the donation process

[1456] Donate to the charity of your choice. Complete the payment through the mobile payment app to formalize your donation. Once the payment is complete, users will receive a donation certificate that they can save or print.

[1457] Specific examples

[1458] As a concrete example, consider the case where a user makes a donation to an environmental protection cause. The following is the sequence of events:

[1459] 1. Entering the user's initial information

[1460] A user turns on their device and selects "environmental protection" as an area of ​​interest. This information is sent to the server.

[1461] 2. Generative AI model to recommend donation organizations

[1462] The server uses a generative AI model to obtain information on multiple organizations engaged in environmental protection activities and generate a recommendation list.

[1463] 3. Submit and confirm your details

[1464] The server sends the generated recommendation list to the terminal, where the user can review the list, check the details of the "Environmental Protection Organization A" that interests the user, and finally decide to donate.

[1465] 4. Completing the donation process

[1466] The user launches the mobile payment app, enters their payment information, and makes a donation of 2,000 yen. If the payment is successful, the information is sent to the server.

[1467] 5. Receiving a donation certificate

[1468] The server generates a donation certificate and sends it to the device, which the user can download and save as a PDF.

[1469] As described above, this system provides users with a means to make donations easily and quickly, thereby promoting donation activities and raising awareness of social contribution.

[1470] The processing flow will be explained below.

[1471] Step 1:

[1472] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[1473] Step 2:

[1474] The terminal sends the user's input information to the server, which stores the received information in a database and sends a notification to the terminal that registration is complete.

[1475] Step 3:

[1476] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[1477] Step 4:

[1478] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[1479] Step 5:

[1480] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[1481] Step 6:

[1482] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[1483] Step 7:

[1484] When the user selects a charity, the terminal displays a screen for inputting the donation amount for that charity. The user inputs the donation amount and clicks the Donate button.

[1485] Step 8:

[1486] When the device detects a click on the donation button, it launches the mobile payment app, and the user selects a payment method (e.g., credit card, electronic money, etc.) and completes the payment.

[1487] Step 9:

[1488] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[1489] Step 10:

[1490] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[1491] Step 11:

[1492] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[1493] The above is the specific process flow of this system, which allows users to make donations based on their areas of interest quickly and easily.

[1494] Example 1

[1495] 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."

[1496] Conventional donation systems have the problem that it is difficult for users to find a donation recipient that suits their area of ​​interest, and the complicated donation process prevents users from donating. In particular, users are discouraged from donating because they have to search multiple websites to get detailed information, and fees incurred during the donation process.

[1497] 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.

[1498] In this invention, the server includes means for collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for inputting a prompt sentence into the generative AI model to list multiple donation organizations, means for providing detailed information about the donation organizations recommended by the generative AI model, means for carrying out a donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to donate to areas of interest easily and efficiently.

[1499] "User Interests" refers to the activities or themes that are of particular interest to the user who wishes to donate.

[1500] A "generative AI model" refers to an artificial intelligence algorithm that recommends appropriate donation organizations based on input data and prompts.

[1501] A "prompt" refers to a question or instruction entered into a generative AI model to obtain a specific recommendation result.

[1502] A "donor organization" refers to a nonprofit organization that receives funds to support a specific social issue or cause.

[1503] "Detailed information" refers to information necessary for users to decide to donate, such as the activities of the donation organization, how to donate, and past performance.

[1504] "Mobile payment app" refers to a software application that allows users to make monetary payments using mobile devices such as smartphones and tablets.

[1505] "Donation Process" refers to the entire process of transferring funds to the donation organization selected by the User.

[1506] "Donation Certificate" means a document officially certifying that a User has made a Donation.

[1507] The present invention relates to a system that allows users to easily make donations by receiving recommendations for appropriate donation organizations based on their areas of interest. The system includes a server, a terminal, and a series of user operations.

[1508] First, the user enters their interests through the device's interface. Specifically, the user enters their name, email address, and the area of ​​interest they wish to support (e.g., "environmental protection") into the device, which then sends this information to the server. The device can be a smartphone, tablet, or PC, and uses an interface for inputting and receiving information.

[1509] Next, the server uses a generative AI model to recommend appropriate organizations to donate to based on the information received from the user. This generative AI model uses an advanced generative AI model (e.g., GPT-3) that uses natural language processing technology. By inputting a prompt sentence into the generative AI model, multiple organizations to donate to are listed. An example of this prompt sentence is, "I'm interested in environmental protection. Please recommend an appropriate organization for me to donate to."

[1510] The server then documents detailed information about the donation organizations listed by the generative AI model, including the activities of each organization, donation methods, past performance, etc. The documented details are sent from the server to the device, where the user can view them.

[1511] When the user checks the recommended list and decides to donate to a specific charity, a mobile payment app is launched. This mobile payment app can be, for example, PayPal or Stripe. The user enters the donation amount through the payment app and makes the payment. Once the payment is complete, the information is sent back to the server.

[1512] Finally, after the server confirms that the donation has been successfully completed, it will generate a donation certificate and send it to the user's email address, which the user can download and save.

[1513] As described above, the present invention provides a system that enables users to easily and quickly make donations to areas they are interested in. This aims to encourage donation activities and increase awareness of social contribution.

[1514] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1515] Step 1:

[1516] Enter initial information

[1517] The user inputs information such as their interests, name, and email address through the device's interface. This information is temporarily stored within the device. Specifically, the user selects the interest category "environmental protection."

[1518] Input: Interests, Name, Email Address

[1519] Output: User input information (JSON format)

[1520] Step 2:

[1521] Sending user information

[1522] The device sends the information entered by the user to the server, using the REST API to transmit data over the HTTPS protocol to ensure security.

[1523] Input: User input information

[1524] Output: User information sent to the server

[1525] Step 3:

[1526] Recommendations based on generative AI models

[1527] The server uses a generative AI model (e.g., GPT-3) based on the received user interest information to research appropriate donation organizations. Specifically, it performs the following operations:

[1528] The server generates the prompt "I'm interested in environmental protection. Please recommend a suitable organization for me to donate to."

[1529] Input the prompt sentence into the generative AI model

[1530] The generative AI model generates a list of donation organizations and returns that information to the server.

[1531] Input: User information, prompt text

[1532] Output: List of recommended donors

[1533] Step 4:

[1534] Submit your recommendation list and details

[1535] The server documents detailed information about the donation organizations listed by the generative AI model (such as their activities, donation methods, and past performance) and sends it to the device. A template engine is used for the documentation, which responds dynamically.

[1536] Input: List of recommended donors

[1537] Output: Documented donor details

[1538] Step 5:

[1539] Check the recommendation list

[1540] Users can check the recommended list on their device and view detailed information on organizations they are interested in, which will then help them select the best recipient.

[1541] Input: Documented donor details

[1542] Output: Selected donors

[1543] Step 6:

[1544] Start the donation process

[1545] The user selects the organization to which they wish to donate and clicks the "Start Donation" button. This action launches the mobile payment app, and they also enter the donation amount.

[1546] Input: Selected charity, donation amount

[1547] Output: Launch of mobile payment app

[1548] Step 7:

[1549] Managing donation processes

[1550] The terminal guides the user through the payment method selected by the user to complete the donation. The server connects to the mobile payment app and monitors the progress of the payment in real time.

[1551] Input: Donation amount, payment method

[1552] Output: Payment completion information

[1553] Step 8:

[1554] Generate and send a donation certificate

[1555] The server verifies that the donation was successful and generates a donation certificate, which is created in PDF format and sent to the user's email address.

[1556] Input: Payment completion information

[1557] Output: Donation certificate (PDF), notification to user that submission is complete

[1558] Through these processing steps, users can easily and efficiently make donations to areas of interest.

[1559] (Application example 1)

[1560] 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."

[1561] In conventional donation systems, many users had to spend a lot of time and effort identifying a donation destination that suited their area of ​​interest and obtaining the appropriate information. Furthermore, the complicated donation process often hindered donation behavior. This created the problem of not raising awareness of social contribution and making it difficult to promote donation activities. The present invention aims to solve these problems by providing a system that allows users to more easily and quickly find a donation destination that suits their area of ​​interest and efficiently complete the donation process.

[1562] 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.

[1563] In this invention, the server includes means for collecting user-related information, means for using a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, means for providing specific information about the donation organizations recommended by the generative AI model, means for carrying out donation procedures using mobile payment technology, and means for generating and providing a donation certificate to the user after the donation is completed, thereby enabling users to easily find donation organizations that match their areas of interest and quickly complete their donations.

[1564] "User related information" refers to information entered by the user, such as name, email address, and areas of interest.

[1565] "Using a generative AI model that recommends appropriate donation organizations based on areas of interest" means that the generative AI model identifies and recommends the most suitable donation organizations based on the user's area of ​​interest data.

[1566] "Specific information about the donation organizations recommended by the generative AI model" refers to detailed information such as the donation organization's activities, past performance, and donation methods.

[1567] "Completing donation transactions using mobile payment technology" refers to technology that allows donation payments to be made using a smartphone app or other mobile device.

[1568] "Generating a donation certificate and providing it to the user after the donation is completed" refers to confirming that the donation has been completed, creating a certificate as proof of that, and providing it to the user.

[1569] The present invention relates to a system that recommends appropriate donation organizations based on the user's areas of interest and simplifies the donation process, and is composed of a server, a terminal, and a generative AI model.

[1570] Server Operation

[1571] Receiving user information

[1572] The server receives information entered by the user from the device, such as name, email address, areas of interest, etc. This information collection allows the server to accumulate information related to the user.

[1573] Recommendations based on generative AI models

[1574] The server uses a generative AI model to research appropriate donation organizations based on the user's areas of interest. This generative AI model has been trained in advance using training data, and analyzes the user's input data based on prompts to recommend the most suitable donation organizations. Examples of prompts include:

[1575] "If a user has 'environmental protection' as an area of ​​interest, which charitable organizations would be recommended?"

[1576] Providing more information

[1577] The server aggregates and documents specific information about the charity recommended by the generative AI model, including its activities, past performance, donation methods, etc. These details are then sent to the device for review by the user.

[1578] Managing donation processes

[1579] When a user decides to donate to the charity of their choice, the server processes the donation using mobile payment technology. Once the payment is complete, the server generates a donation certificate and provides it to the user.

[1580] Device behavior

[1581] Providing an interface

[1582] The terminal provides an interface for the user to input and select information, such as a screen for selecting areas of interest and a screen for confirming recommended donation organizations.

[1583] Sending and receiving information

[1584] The information entered by the user is sent to the server, and the recommendation list and detailed information received from the server are displayed at the same time, improving the convenience of the user when actually using the service.

[1585] Completing the donation process

[1586] When a user initiates a donation process, the device launches a mobile payment app and prompts them to enter the payment method and amount. Once the payment is complete, the information is sent to the server and the donation is officially confirmed.

[1587] User behavior

[1588] Entering information and selecting options

[1589] Users enter basic information such as their name and email address, as well as the areas of interest they wish to support, through their device, allowing the server to recommend organizations that match the user's interests.

[1590] Check the recommendation list

[1591] Users can then review the list of recommendations and detailed information received from the server and select the most suitable donation recipient. During this process, users can choose the organization that interests them most from multiple options.

[1592] Complete the donation process

[1593] Users can make donations to the charity of their choice, complete the payment through a mobile payment app, and receive a donation certificate, which can be downloaded and saved in PDF format.

[1594] Specific examples

[1595] For example, if a user wants to donate to an environmental protection cause, they open the app on their smartphone and select "environmental protection" as their area of ​​interest. This information is sent to the server, and the generative AI model researches suitable donation organizations and generates a list of recommendations. The user selects "Environmental Protection Organization A" from the displayed list and completes the donation process using mobile payment technology. If the donation is successful, the server can generate a donation certificate and provide it to the user.

[1596] In this way, the present invention is a system that supports users in efficiently carrying out donation activities.

[1597] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1598] Step 1:

[1599] Entering user information

[1600] The user uses the device's interface to enter their name, email address, and interests, which are then sent by the device to the server.

[1601] Input: User's name, email address, and interests

[1602] Output: User information data sent to the server

[1603] Step 2:

[1604] Receiving and storing user information

[1605] The server receives the user information sent from the terminal and stores it in a virtual database, which is the data required for subsequent processing.

[1606] Input: User information data sent from the device

[1607] Output: User information stored in a virtual database

[1608] Step 3:

[1609] Recommendations based on generative AI models

[1610] The server uses a generative AI model based on the stored user information to generate a list of recommendations. The generative AI model creates a list of donation organizations based on the user's areas of interest, and the AI ​​uses prompts to suggest the most suitable organizations.

[1611] Input: User information stored in a virtual database

[1612] Data processing: Inference processing using generative AI models

[1613] Output: Recommendation list

[1614] Specific behavior:

[1615] The server inputs prompts such as "If the user's area of ​​interest is 'environmental protection,' which donation organizations would be recommended?" into the generative AI model and generates a list of recommendations.

[1616] Step 4:

[1617] Submit your recommendation list and details

[1618] The server sends the generated recommendation list and detailed information about each charity (such as activities, past performance, and donation methods) to the terminal, allowing the user to select an appropriate charity.

[1619] Input: Generated recommendation list and detailed information

[1620] Output: Recommendation list and details sent to your device

[1621] Specific behavior:

[1622] The server documents the recommendation list and sends it to the user's device.

[1623] Step 5:

[1624] Choosing a donation destination

[1625] The user uses the interface on the terminal to check the recommendation list and detailed information sent from the server and select a donation destination, which is then sent to the server by the terminal.

[1626] Input: Recommendation list and detailed information received from the server

[1627] Output: Selected donation information (sent from device to server)

[1628] Specific behavior:

[1629] Users scroll through the screen, check the information for each charity, and then select the charity of their choice.

[1630] Step 6:

[1631] Completing the donation process

[1632] Once the user has decided on a donation recipient, the device will launch a mobile payment app and prompt them to enter the donation amount and payment method. The entered payment information is then sent to the server, where the actual payment is processed.

[1633] Input: Donation information, donation amount, payment method

[1634] Data processing: Payment processing via mobile payment apps

[1635] Output: Payment completion notification

[1636] Specific behavior:

[1637] Users enter the donation amount and make the payment via a mobile payment app.

[1638] Step 7:

[1639] Generate and provide a donation certificate

[1640] The server confirms that the payment has been completed and generates a donation certificate, which is then sent to the user's device, where the user can download and save it.

[1641] Input: Payment completion notification

[1642] Data processing: Generating donation certificates

[1643] Output: Generated donation certificate (sent to terminal)

[1644] Specific behavior:

[1645] The server generates a donation certificate in PDF format and sends it to the device, where the user can open it, save it, or print it.

[1646] 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.

[1647] The present invention relates to a system that uses a generative AI model to recommend appropriate donation organizations based on a user's areas of interest, and optimizes the donation experience by analyzing the user's emotional state. This system operates through the interaction of a server, a terminal, and a user.

[1648] Server Operation

[1649] 1. Receiving and storing user information

[1650] The server receives information entered by the user from their device, such as their name, email address, and areas of interest, and stores this information in a database.

[1651] 2. Recommendations using generative AI models

[1652] The server uses a generative AI model to list appropriate donation organizations based on the user's areas of interest and past donation history, and the generative AI model pulls relevant information from a database and updates it accordingly.

[1653] 3. Emotion Recognition by Emotion Engine

[1654] The server uses an emotion engine to analyze the user's emotional state. The emotion engine obtains and analyzes emotion data from the user's facial expressions and voice input, for example, to determine whether the user is excited or calm.

[1655] 4. Providing more information

[1656] The server documents detailed information for each donation organization recommended by the generative AI model and sends it to the user's device in the most optimal format, taking into account the analysis results of the emotion engine.

[1657] 5. Managing donation procedures

[1658] If the user decides to donate, the server will connect to the mobile payment app and manage the donation process. Once the payment is complete, the server will generate a donation certificate and provide it to the user.

[1659] Device behavior

[1660] 1. Providing an interface

[1661] The terminal provides an interface for user input and selection, allowing the user to select areas of interest and view information about charitable organizations.

[1662] 2. Sending and receiving information

[1663] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[1664] 3. Acquiring Emotion Data

[1665] The device captures the user's facial expressions and voice input through a camera and microphone, and sends the data to a server where it is analyzed by an emotion engine.

[1666] 4. Donation Procedures

[1667] When a user makes a donation, the device launches a mobile payment app and assists the user in entering the payment method and amount, which is then sent to the server.

[1668] User behavior

[1669] 1. Information entry and selection

[1670] Users enter their name, email address, and interests through the device's interface, which then uses the camera and microphone to provide emotional data.

[1671] 2. Review and select from the recommended list

[1672] The user checks the list of recommendations received from the server and the details of each donation organization. The information displayed is based on the analysis results of the emotion engine and is presented in the most appropriate format for the user.

[1673] 3. Completing the donation process

[1674] Users select a donation recipient, enter the donation amount, and complete the payment. The donation is officially completed once payment is made through the mobile payment app.

[1675] 4. Preservation of donation certificates

[1676] Once the donation is complete, the server will send you a donation certificate, which you can then download and save or print as needed.

[1677] Specific examples

[1678] As a concrete example, consider the case where a user makes a donation to an educational support activity. The following is the flow of the process.

[1679] 1. Entering the user's initial information

[1680] The user launches the app and selects that they are interested in "educational support." Emotional data is collected from the user's facial expressions and voice and sent to the server.

[1681] 2. Recommending donation organizations using generative AI models and emotion engines

[1682] The server uses a generative AI model and an emotion engine to list appropriate educational support organizations and send detailed information taking into account the user's emotional state.

[1683] 3. Confirm details and decide to donate

[1684] The device displays a list of recommendations and detailed information, and the user becomes interested in "Educational Support Organization B" and decides to donate.

[1685] 4. Completing the donation process

[1686] The user enters the donation amount and makes a donation of 5,000 yen using a mobile payment app. If the payment is successful, the information is sent to the server.

[1687] 5. Receiving a donation certificate

[1688] The server generates a donation certificate and sends it to the device, which the user downloads and saves.

[1689] As described above, this system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[1690] The processing flow will be explained below.

[1691] Step 1:

[1692] A user launches the app on their device and creates a new account or logs in. The user enters basic information such as their name, email address, and password.

[1693] Step 2:

[1694] The terminal sends the user's input information to the server, which stores the received information in a database and sends a registration completion notification to the terminal.

[1695] Step 3:

[1696] Users can select their area of ​​interest (e.g., environment, education, medical care, etc.) on the device screen. They can also specify their specific interests and preferences for support recipients.

[1697] Step 4:

[1698] The device sends information about the user's areas of interest to the server, which then uses a generative AI model to research appropriate donation organizations based on the received interest information.

[1699] Step 5:

[1700] The generative AI model generates a list of donation organizations that match the user's areas of interest. The server documents this recommendation list and details of each organization and sends it to the device.

[1701] Step 6:

[1702] The terminal displays the recommendation list and detailed information received from the server to the user, who then selects the organization in which they are interested from among multiple donation organizations.

[1703] Step 7:

[1704] Once the user selects a charity, the device uses an emotion engine to acquire emotional data such as the user's facial expressions and voice. This data is then sent to the server and analyzed by the emotion engine.

[1705] Step 8:

[1706] The server uses an emotion engine to analyze the user's emotional state and adjusts how the donation organization's details are displayed based on the user's emotional state, for example, highlighting key information if the user is excited.

[1707] Step 9:

[1708] The user enters the donation amount and clicks the donate button. The device launches the mobile payment app and prompts for payment information.

[1709] Step 10:

[1710] The terminal sends payment information to the server. The server calls the API to execute the payment process based on the received payment information. If the payment is successful, the server notifies the terminal that the donation has been officially completed.

[1711] Step 11:

[1712] The server generates a donation certificate and sends it to the terminal for delivery to the user. The donation certificate contains information such as the donation amount, donation recipient, and date.

[1713] Step 12:

[1714] The device displays the donation certificate to the user and gives them the option to save or print it, or the user can download the donation certificate in PDF format if desired.

[1715] This concludes the specific processing flow of our system, which combines an emotion engine, enabling users to enjoy a personalized donation experience that takes into account their emotional state.

[1716] Example 2

[1717] 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."

[1718] Existing donation systems do not take into account the user's emotional state when selecting appropriate donation organizations based on the user's areas of interest, resulting in a disorganized donation experience and making it difficult to donate efficiently. Furthermore, the complicated donation procedures and the provision of donation certificates make it difficult for users to complete the process, which prevents them from fully encouraging donation behavior.

[1719] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting the user's areas of interest, means for recommending appropriate organizations using a generative AI model, means for using an emotion engine to analyze the user's emotional state, means for providing detailed information about the recommended donation organizations, means for completing the donation procedure using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide a personalized donation experience that takes the user's emotional state into consideration, thereby improving the efficiency of the donation process and encouraging donation behavior.

[1720] "User interests" refers to the areas or topics in which a user is particularly interested when making a donation.

[1721] "Generative AI models" are algorithms and systems that use artificial intelligence techniques to recommend appropriate organizations based on a user's areas of interest.

[1722] "Emotion engine" refers to software or hardware for analyzing a user's emotional state, including technology that recognizes emotions using the user's facial expressions and voice data.

[1723] A "mobile payment app" is an application that allows users to complete online payments using mobile devices such as smartphones and tablets.

[1724] A "donation certificate" is a document that certifies that a donation has been completed and contains details of the donation (donation amount, donation recipient, date and time, etc.).

[1725] MODE FOR CARRYING OUT THE INVENTION

[1726] The present invention is a system that uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest, and analyzes the user's emotional state to optimize the donation experience. This system operates through the interaction of a server, a terminal, and the user.

[1727] Server Operation

[1728] The server uses the following hardware and software to implement this system:

[1729] Hardware: Server itself (including CPU, memory, and storage)

[1730] Software: MySQL database, generative AI model (e.g., GPT-4), emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API)

[1731] Specifically, the server does the following:

[1732] 1. Receiving and storing user information

[1733] The server receives information entered by the user on their device, such as their name, email address, and areas of interest, and stores this information in a MySQL database.

[1734] 2. Recommendations using generative AI models

[1735] The server retrieves the user's areas of interest and past donation history from the database and uses a generative AI model (e.g., GPT-4) to list appropriate donation organizations. An example of a prompt used here is, "The user is interested in supporting education. What organizations do you recommend for donation?"

[1736] 3. Emotion Recognition by Emotion Engine

[1737] The server receives the user's facial expression and voice data sent from the device and sends it to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API). The emotion engine's analysis results are used to determine the user's emotional state. For example, if the emotion engine determines the user's emotion to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[1738] 4. Providing more information

[1739] The server builds detailed information about the organizations recommended by the generative AI model and emotion engine and sends it to the device. The detailed information is collected using SQL queries from a database, including the organization's activities and impact.

[1740] 5. Managing donation procedures

[1741] When a user decides to donate and enters the amount on the terminal, the server connects to the mobile payment app to process the donation. After the payment is completed, a donation certificate is generated and provided to the user.

[1742] Device behavior

[1743] The device operates using the following hardware and software:

[1744] Hardware: Mobile devices (smartphones, tablets, etc.) equipped with a camera, microphone, CPU, memory, storage, etc.

[1745] Software: Mobile applications, mobile payment apps

[1746] Specifically, the terminal works as follows:

[1747] 1. Providing an interface

[1748] The device provides an interface for users to enter their name, email address, and interests, with text boxes and drop-down menus.

[1749] 2. Sending and receiving information

[1750] The device sends the information entered by the user to the server, and displays the recommendation list and detailed information received from the server. The interface is optimized based on the analysis results using an emotion engine.

[1751] 3. Acquiring Emotion Data

[1752] The device uses a camera and microphone to capture the user's facial expressions and voice data, and sends that data to a server where it is analyzed by an emotion engine.

[1753] 4. Donation Procedures

[1754] The user enters the donation amount, launches the mobile payment app, and sends the payment information to the server. Once the payment is complete, the user can download and save or print a donation certificate.

[1755] User behavior

[1756] Users use the system as follows:

[1757] 1. Information entry and selection

[1758] Through the device's interface, users enter their name, email address, and areas of interest, and provide emotional data using the camera and microphone.

[1759] 2. Review and select from the recommended list

[1760] The user checks the recommended list received from the server and the detailed information of each donation organization, and selects the organization to which the user wishes to donate.

[1761] 3. Completing the donation process

[1762] The user enters the donation amount and completes the payment using a mobile payment app.

[1763] 4. Preservation of donation certificates

[1764] After your donation is complete, you will receive a donation certificate from the server, which you can download, save, or print as needed.

[1765] As described above, this system uses a generative AI model and an emotion engine to recommend donation organizations based on the user's areas of interest, providing users with a personalized donation experience, which helps users make donations efficiently and contributes to promoting donation behavior.

[1766] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1767] Step 1:

[1768] Entering and submitting user information

[1769] Input: A user types their name, email address, or interests into a device.

[1770] Specific operation: The user uses the device interface to enter the required information for each form. For example, the user enters "Yamada Taro" as the name, "taro@example.com" as the email address, and "educational support" as the area of ​​interest.

[1771] Output: The device checks the entered information and sends it to the server.

[1772] Step 2:

[1773] Receiving and storing user information

[1774] Input: User information sent from your device (name, email address, interests).

[1775] Specific behavior: The server receives the information and performs initial validation to ensure the data format is correct. For example, it checks whether the email address format is correct. Then it executes an SQL query (e.g., "INSERT INTO user_info (name, email, interest) VALUES ('Yamada Taro', 'taro@example.com', 'Education Support')") to save the information to the MySQL database.

[1776] Output: User information is saved in the database.

[1777] Step 3:

[1778] Recommendations based on generative AI models

[1779] Input: User's areas of interest and past donation history retrieved from our database.

[1780] Specific operation: The server generates a prompt based on the user's areas of interest and inputs it into a generative AI model (e.g., GPT-4). Example prompt: "The user is interested in supporting education. What organizations do you recommend for donation?" The output returned by the model is analyzed and a list of appropriate donation organizations is generated.

[1781] Output: A list of recommended donor organizations.

[1782] Step 4:

[1783] Emotion recognition by emotion engine

[1784] Input: The user's facial and voice data sent from the device.

[1785] Specific operation: The server sends the received data to an emotion engine (e.g., Microsoft Azure Cognitive Services' Emotion API) and receives emotion data in response. For example, if the emotion engine judges the response to be "positive," it will use that information to recommend the most appropriate organization to donate to.

[1786] Output: Analysis of the user's emotional state.

[1787] Step 5:

[1788] Providing more information

[1789] Input: A list of recommended donation organizations and the results of an analysis of the user's emotional state.

[1790] What it does: The server retrieves details of each donation organization from the database and formats them according to the user's emotional state. For example, it executes the SQL query "SELECT FROM donation_organizations WHERE id IN (1, 2, 3)" to retrieve the details. The format of the information is adjusted according to the user's emotional state (positive, negative, neutral).

[1791] Output: Optimized detailed information sent to the terminal.

[1792] Step 6:

[1793] Displaying Information

[1794] Input: Optimized details sent by the server.

[1795] What it does: The device receives the details and displays them in the interface. The user can review the information and choose the organization to donate to.

[1796] Output: The charitable organization selected by the user.

[1797] Step 7:

[1798] Completing the donation process

[1799] Input: User-selected charitable organization and donation amount.

[1800] Specific operation: The terminal launches the mobile payment app, and the user inputs the donation amount (for example, "5,000 yen"), presses the "Donate" button, and completes the payment. The payment information is sent to the server.

[1801] Output: Payment information is sent to the server and the donation is executed.

[1802] Step 8:

[1803] Generate and send a donation certificate

[1804] Input: Donation information after payment is completed.

[1805] Specific operation: The server generates a donation certificate and sends it to the user's email address. The certificate contains the user's name, the name of the donation organization, the donation amount, and the date and time. For example, "The donation certificate will state a donation of 5,000 yen to 'Yamada Taro' and 'Educational Support Organization B'."

[1806] Output: A donation certificate is provided to the user.

[1807] Through these processing steps, the system recommends donation organizations that match the user's areas of interest and uses an emotion engine to provide a more personalized donation experience, allowing users to make donations easily and efficiently and maximize the impact of their donations.

[1808] (Application example 2)

[1809] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1810] While conventional donation systems had the ability to recommend organizations that matched a user's areas of interest, there were no systems that made recommendations that took into account the user's emotional state. Furthermore, there was a lack of sentiment analysis to optimize the donation experience, and the lack of real-time detailed information provided, which meant that users' motivation to donate and their satisfaction were not sufficiently improved.

[1811] The identification processing 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 collecting a user's areas of interest, means for using a generative AI model to recommend appropriate donation organizations based on the areas of interest, means for analyzing the user's emotional state, means for providing detailed information about the donation organizations recommended by the generative AI model based on the user's emotional state, means for acquiring emotional data using a camera and microphone, means for performing donation procedures using a mobile payment app, and means for generating and providing a donation certificate to the user after the donation is completed. This makes it possible to provide an optimized donation experience based on the user's emotional state.

[1812] "User Interests" are the topics or areas in which a donor has an interest or concern.

[1813] A "generative AI model" is a model that uses artificial intelligence to generate appropriate outputs based on specific input information.

[1814] "User emotional state" refers to the psychological and emotional state of the donor as estimated from their facial expressions and voice.

[1815] The "facial expression recognition API" is a program interface for analyzing a person's facial expressions from image data and estimating their emotional state.

[1816] The "Voice Emotion Analysis API" is a program interface for analyzing a speaker's emotional state from voice data.

[1817] "Detailed information" refers to specific information about the activities, achievements, and effects of the donation organization.

[1818] "Camera and microphone" refers to hardware devices that capture images and audio and use them as input data for sentiment analysis.

[1819] A "mobile payment app" is software that allows users to conduct online financial transactions using a smartphone.

[1820] A "donation process" is a series of steps that a user takes to transfer money to a donation organization of their choice.

[1821] A "certificate of donation" is an official document that certifies that a donation has been completed.

[1822] This invention relates to a system that recommends appropriate donation organizations that match a user's field of interest based on the user's emotional state. The specific system configuration and operation procedure are described below.

[1823] 1.Collection of User Information

[1824] The server provides a means to collect the user's interests. The user uses the smartphone interface to input their name, email address, and interests. They also use the camera and microphone to provide emotional data through facial expressions and voice.

[1825] 2. Recommendations using generative AI models

[1826] The server uses a generative AI model to recommend appropriate donation organizations based on the user's areas of interest. This generative AI model analyzes the user's areas of interest and past donation history to list relevant donation organizations. OpenAI GPT-4 is used as the generative AI model.

[1827] 3.Analysis of Emotional Data

[1828] The server analyzes the user's emotional state using an emotion engine. This emotion engine uses facial expression recognition APIs and voice emotion analysis APIs (e.g., Microsoft Azure Emotion API) to obtain and analyze emotional data from the user's facial expressions and voice.

[1829] 4. Provide detailed information

[1830] The server provides detailed information about the charity organizations recommended by the generative AI model. This detailed information is displayed in an optimal format based on the user's emotional state. Depending on the user's emotions, the server provides detailed information about the charity organization's activities, specific support activities, and achievements.

[1831] 5. Completing the donation process

[1832] If the user decides to donate, the server executes the donation process using a mobile payment app, which can be a common payment platform (e.g., Stripe or PayPal).

[1833] 6. Generate a donation certificate

[1834] Once the donation is complete, the server generates a donation certificate and provides it to the user. The donation certificate is generated electronically and can be received by email or other means.

[1835] Specific examples

[1836] For example, if a user is interested in "educational support," the system operates in the following steps:

[1837] 1. The user launches the smartphone app, inputs their interest in "educational support," and provides emotional data using the camera and microphone.

[1838] 2. The server uses the generative AI model to list donation organizations related to educational support, while simultaneously analyzing the user's emotional state using facial expression recognition APIs and voice emotion analysis APIs.

[1839] 3. The server provides the details of the charitable organizations listed by the generative AI model based on the analyzed emotional state. For example, if the user is in a positive emotional state, success stories and thank-you messages will be displayed.

[1840] 4. The user decides to donate 5,000 yen to a specific charity and completes the process using a mobile payment app.

[1841] 5. Once the payment is complete, the server generates a donation certificate and emails it to the user.

[1842] Example prompt sentence:

[1843] When a user enters "I'm interested in education" and provides emotional data (e.g., facial expression photo or voice message), the smartphone app uses a generative AI model to display a list of educational support organizations based on the user's emotional state, and also provides real-time information tailored to the user's specific preferences. For example, "organizations that provide learning materials" or "organizations that support teachers" are displayed. After the user selects a donation of 5,000 yen, the donation is completed through the Stripe payment system. A donation certificate is then sent to the user electronically.

[1844] This allows for a donation experience that is optimized based on the user's emotional state.

[1845] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1846] Step 1:

[1847] Users enter their interests and provide sentiment data

[1848] Users launch the smartphone application and enter their name, email address, and areas of interest, while simultaneously providing facial expressions and voice messages using the camera and microphone. This data is then transmitted from the device to the server.

[1849] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[1850] Output: User information and emotion data sent to the server

[1851] Step 2:

[1852] Storing user information and emotional data

[1853] The server stores the received user's name, email address, and areas of interest in a database, and also processes the facial expression photo and voice message into data to be sent to the emotion analysis API.

[1854] Input: User's name, email address, area of ​​interest, facial expression photo, voice message

[1855] Output: User information stored in the database, data for the sentiment analysis API

[1856] Step 3:

[1857] Sentiment Data Analysis

[1858] The server uses the facial expression recognition API and the voice emotion analysis API to obtain emotional data from the user's facial expression photo and voice message, and analyzes the user's emotional state.

[1859] Input: facial expression photo, voice message

[1860] Output: User emotional state as an analysis result of the sentiment analysis API

[1861] Step 4:

[1862] Recommending a charitable organization

[1863] The server uses a generative AI model based on the user's areas of interest and emotional state to list relevant donation organizations. The generative AI model analyzes the user's areas of interest and past donation history to recommend appropriate organizations.

[1864] Input: User's areas of interest, emotional state

[1865] Output: List of recommended donors

[1866] Step 5:

[1867] Providing more information

[1868] The server retrieves detailed information about the charity recommended by the generative AI model and sends it to the device in an optimal format based on the user's emotional state. For example, if the user is in a positive emotional state, success stories and messages of gratitude will be highlighted.

[1869] Input: List of recommended charitable organizations, user's emotional state

[1870] Output: Details of the donation organization sent to the user's device

[1871] Step 6:

[1872] Completing the donation process

[1873] If the user decides to donate, the terminal will launch the mobile payment app, and the user will input the donation amount. The payment information will be sent to the server, which will then process the donation through the payment platform.

[1874] Input: User's donation choice, donation amount

[1875] Output: Payment completion information, donation process execution

[1876] Step 7:

[1877] Generate and provide a donation certificate

[1878] Once the donation process is complete, the server generates a donation certificate and provides it to the user via email or download link.

[1879] Input: Payment completion information

[1880] Output: Donation certificate provided to the user

[1881] Through these steps, the system is able to provide an optimal donation experience based on the user's emotional state.

[1882] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1883] 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.

[1884] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1885] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1886] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1887] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1888] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1889] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, motorcycles, and other devices, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1890] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1891] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1892] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1893] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1894] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1895] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1896] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1897] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1898] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1899] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1900] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1901] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1902] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1903] The following is further disclosed regarding the above embodiment.

[1904] (Claim 1)

[1905] Collecting user interests

[1906] Means and

[1907] Use a generative AI model that recommends appropriate donation organizations based on the areas of interest.

[1908] Means and

[1909] Provide detailed information about the charitable organizations recommended by the generative AI model

[1910] Means and

[1911] Complete the donation process using a mobile payment app

[1912] Means and

[1913] Once the donation is complete, a donation certificate will be generated and provided to the user.

[1914] Means and

[1915] A system including:

[1916] (Claim 2)

[1917] The generative AI model provides an easy-to-understand explanation of the activities and effects of donation organizations.

[1918] means for detecting a temperature difference between the first and second electrodes;

[1919] 10. The system of claim 1.

[1920] (Claim 3)

[1921] Waive the fee for the donation procedure

[1922] means for detecting a temperature difference between the first and second electrodes;

[1923] 10. The system of claim 1.

[1924] "Example 1"

[1925] (Claim 1)

[1926] Collecting user interests

[1927] Means and

[1928] Use a generative AI model that recommends appropriate donation organizations based on the areas of interest.

[1929] Means and

[1930] A prompt is input into the generative AI model to list multiple donation organizations.

[1931] Means and

[1932] Provide detailed information about the charitable organizations recommended by the generative AI model

[1933] Means and

[1934] Complete the donation process using a mobile payment app

[1935] Means and

[1936] Once the donation is complete, a donation certificate will be generated and provided to the user.

[1937] Means and

[1938] A system including:

[1939] (Claim 2)

[1940] The generative AI model further includes a means for clearly explaining the activities and effects of the donation organization.

[1941] 10. The system of claim 1.

[1942] (Claim 3)

[1943] Further comprising a means for waiving the handling fee for the donation procedure.

[1944] 10. The system of claim 1.

[1945] "Application Example 1"

[1946] (Claim 1)

[1947] Collect relevant information about the user

[1948] Means and

[1949] Use a generative AI model that recommends appropriate donation organizations based on the areas of interest.

[1950] Means and

[1951] Provide specific information about the charitable organizations recommended by the generative AI model

[1952] Means and

[1953] Use mobile payment technology to process donations

[1954] Means and

[1955] Once the donation is complete, a donation certificate will be generated and provided to the user.

[1956] Means and

[1957] A system including:

[1958] (Claim 2)

[1959] Based on the information entered by the user, areas of interest are identified, and the AI ​​model generates and recommends the most suitable donation destination based on those areas of interest.

[1960] and a training means used by the generative AI model when learning field of interest data and generating a recommendation list.

[1961] 10. The system of claim 1.

[1962] (Claim 3)

[1963] Waive transaction fees for the donation process

[1964] means,

[1965] 10. The system of claim 1.

[1966] "Example 2: Combining Emotion Engines"

[1967] (Claim 1)

[1968] A means of collecting user interests;

[1969] means for using a generative AI model to recommend appropriate entities based on said areas of interest;

[1970] a means for using an emotion engine to analyze the emotional state of a user;

[1971] means for providing detailed information about the donation organizations recommended by the generative AI model and the emotion engine;

[1972] A means for carrying out a donation procedure using a mobile payment app;

[1973] A means for generating and providing a donation certificate to the user after the donation is completed;

[1974] A system including:

[1975] (Claim 2)

[1976] The system of claim 1 , wherein the generative AI model further includes means for providing an easy-to-understand explanation of the activities and effects of an organization.

[1977] (Claim 3)

[1978] The system of claim 1, further comprising means for waiving a processing fee for the donation process.

[1979] "Application example 2 when combining emotion engines"

[1980] (Claim 1)

[1981] A means of collecting user interests;

[1982] means for using a generative AI model to recommend appropriate donation organizations based on said areas of interest;

[1983] a means for analyzing the emotional state of a user;

[1984] means for providing detailed information about the donation organizations recommended by the generative AI model based on the user's emotional state;

[1985] means for acquiring emotion data using a camera and a microphone;

[1986] A means for carrying out a donation procedure using a mobile payment app;

[1987] A means for generating and providing a donation certificate to the user after the donation is completed;

[1988] A system including:

[1989] (Claim 2)

[1990] The system of claim 1 , wherein the generative AI model further includes means for providing an easy-to-understand explanation of the activities and effects of the donation organization.

[1991] (Claim 3)

[1992] The system of claim 1 , further comprising: means for utilizing a facial expression recognition API and a voice emotion analysis API to analyze the emotional state. [Explanation of symbols]

[1993] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. Collecting user interests Means and Use a generative AI model that recommends appropriate donation organizations based on the areas of interest. Means and Provide detailed information about the charitable organizations recommended by the generative AI model Means and Complete the donation process using a mobile payment app Means and Once the donation is complete, a donation certificate will be generated and provided to the user. Means and A system including:

2. The generative AI model provides an easy-to-understand explanation of the activities and effects of donation organizations. means for detecting a temperature difference between the The system of claim 1 .

3. Waive the fee for the donation procedure means for detecting a temperature difference between the The system of claim 1 .

Images