System

Abstract

A system is provided.SOLUTION: Means for inputting a field of interest of a user, means for recommending an appropriate non-profit organization using a generative AI model on the basis of the field of interest input by the user, means for explaining activity content of the recommended non-profit organization and an effect of a donation, means for providing the explanation to the user, means for inputting an amount of donation to a non-profit organization selected by the user, and means for cooperating with an electronic settlement system on the basis of the input amount of donation, the system includes a means for performing donation processing and a means for transmitting a donation completion notification to the user when the donation is successful and transmitting a receipt when the amount of donation is equal to or larger than a predetermined amount.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, interest in environmental and social issues has grown, and many people want to contribute to society. However, lack of knowledge about the organizations and activities to which donations should be made, as well as the complexity of the donation process, can be obstacles that often prevent people from actually donating. There is a need for a system that can resolve these obstacles and enable users to easily donate to reliable nonprofit organizations. [Means for solving the problem]

[0005] This invention is a system that includes a means for a user to input areas of interest, a means for recommending appropriate non-profit organizations using a generative AI model based on the areas of interest input by the user, a means for explaining the activities of the recommended non-profit organization and the effects of donations, a means for providing the explanation to the user, a means for the user to input the amount of donation to the non-profit organization selected by the user, a means for linking with an electronic payment system based on the input donation amount and processing the donation, and a means for sending the user a donation completion notification when the donation is successful and a receipt if the donation amount is above a predetermined amount.

[0006] "Area of ​​Interest" refers to the particular area or topic to which a user wishes to donate.

[0007] A "generative AI model" refers to a system that implements artificial intelligence algorithms that make predictions and recommendations based on input information.

[0008] A "non-profit organization" is an organization that carries out specific public benefit activities and does not pursue profits.

[0009] "Recommendation tool" refers to the feature that uses a generative AI model to select the most suitable nonprofit organization based on user input.

[0010] "Activities" refers to the specific activities and projects that a nonprofit organization is carrying out.

[0011] "Effectiveness of donations" refers to information showing how users' donations are used and what results they produce.

[0012] "Means for explanation" refers to information provision functions that help users understand the activities of the recommended nonprofit organization and the effects of donations.

[0013] An "electronic payment system" refers to a mechanism for making payments electronically via the Internet.

[0014] "Means for processing donations" refers to a function that links with an electronic payment system to process donations based on the nonprofit organization and donation amount selected by the user.

[0015] "Donation Completion Notification" refers to a message that informs the user that the donation process was successful.

[0016] "Receipt" means an electronic or physical receipt proving that a donation has been made. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention relates to a system that allows users to easily and effectively make donations to non-profit organizations. A specific embodiment of this system will be described below.

[0039] 1. Enter your user interests

[0040] User Device

[0041] A user accesses a dedicated application or web page and logs in. After logging in, the user enters values ​​into input fields to indicate the areas of interest (e.g., "environmental protection"), and when the user presses the submit button, this input data is sent to the server.

[0042] 2. Generative AI model recommends suitable nonprofit organizations

[0043] server

[0044] The server receives user-submitted interest data, passes this data to a generative AI model, which then recommends suitable nonprofits based on the user's interests. The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's input.

[0045] 3. Explanation of the recommendation results and the impact of the donation

[0046] server

[0047] The server receives the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from a database, and formats this information into a format that can be presented to users.

[0048] User Device

[0049] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, it may display information such as "Environmental Protection Organization A" is "carrying out tree planting activities and planting 10 trees for a donation of 3,000 yen."

[0050] 4. User Donation Choices

[0051] User Device

[0052] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[0053] 5. Donation processing through integration with electronic payment systems

[0054] server

[0055] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., PayPay) to process the donation, and receives a response from the electronic payment system confirming whether the donation was successful.

[0056] 6. Notification of donation completion and receipt issuance

[0057] server

[0058] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0059] User Device

[0060] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0061] Specific examples

[0062] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is engaged in tree planting activities, and that a donation of 3,000 yen will plant 10 trees. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, allowing the user to confirm that the donation was made validly.

[0063] This system allows users to easily and effectively donate to non-profit organizations, giving them a sense of social contribution.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] User Device

[0067] The user accesses a dedicated application or web page and logs in to their account.

[0068] Step 2:

[0069] User Device

[0070] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[0071] Step 3:

[0072] server

[0073] The server receives the area of ​​interest data sent by the user.

[0074] Step 4:

[0075] server

[0076] The server passes the received data to a generative AI model, which then uses an internal database or external API to generate a list of relevant nonprofits.

[0077] Step 5:

[0078] server

[0079] The generative AI model obtains a list of recommended nonprofit organizations, and then retrieves information about each organization's activities and the effectiveness of donations from a database.

[0080] Step 6:

[0081] server

[0082] Format and deliver information about nonprofits and the impact of donations to users.

[0083] Step 7:

[0084] server

[0085] The formatted information is sent to the user's device.

[0086] Step 8:

[0087] User Device

[0088] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[0089] Step 9:

[0090] User Device

[0091] The user selects a donation destination from the recommended nonprofit organizations, enters the donation amount in the input field, and presses the donate button.

[0092] Step 10:

[0093] server

[0094] The server receives the selected nonprofit organization and donation amount submitted by the user.

[0095] Step 11:

[0096] server

[0097] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[0098] Step 12:

[0099] Electronic payment system

[0100] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[0101] Step 13:

[0102] server

[0103] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[0104] Step 14:

[0105] server

[0106] If the donation is successful, a notification will be sent to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0107] Step 15:

[0108] User Device

[0109] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user confirms that the donation was successful and saves the receipt.

[0110] As a specific example, when a user enters "environmental protection," the generative AI model returns a list of recommendations including "environmental protection organization A" and "environmental protection organization B." If the user then selects to donate 5,000 yen to "environmental protection organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification of the completed donation.

[0111] Example 1

[0112] 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."

[0113] In modern society, users face challenges when making donations to nonprofit organizations, as it requires a lot of time and effort and information gathering. It is also difficult for users to find nonprofit organizations that fit their areas of interest. Furthermore, the donation process faces challenges due to the lack of smooth integration with electronic payment systems.

[0114] 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.

[0115] In this invention, the server includes a means for a user to input areas of interest, a means for recommending appropriate organizations using a generative AI model based on the areas of interest input by the user, and a means for explaining the activities of the recommended organizations and the effects of donations, allowing users to easily find nonprofit organizations that fit their areas of interest and making the donation process smoother.

[0116] "User" means an individual or organization that uses the System to make donations to a nonprofit organization.

[0117] "Areas of Interest" are specific categories or topics that users consider important, such as environmental protection, educational support, or medical assistance.

[0118] A "generative AI model" is a type of artificial intelligence technology that recommends suitable nonprofit organizations based on a user's areas of interest. It collects information from internal databases and external APIs to present the best candidates.

[0119] A "non-profit organization" is an organization that does not aim to make a profit but works to solve social problems or for the public good.

[0120] "Activities" refers to the specific projects and initiatives undertaken by the nonprofit organization, such as tree planting activities or educational programs.

[0121] "Effectiveness of Donations" provides detailed information about how users' donated funds are utilized and the results they produce.

[0122] An "electronic payment system" is a system for processing payments online, such as payments using electronic wallets or credit cards.

[0123] "Receipt" means the official payment confirmation issued to a User upon successful Donation.

[0124] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations.

[0125] 1. Enter your user interests

[0126] The user accesses a dedicated application or web page and logs in. After logging in, the user enters information in the field for entering their areas of interest. For example, if the user is interested in "environmental protection," they enter this information and press the "Submit" button. This data is sent from the user's device to the server.

[0127] 2. Generative AI model recommends suitable nonprofit organizations

[0128] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and the model recommends suitable nonprofit organizations based on the user's areas of interest. The generative AI model collects information from an internal database and external APIs and generates a list of the most suitable nonprofit organizations based on the user's input data.

[0129] 3. Explanation of the recommendation results and the impact of the donation

[0130] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from the database. This information is formatted and sent to the user's device. The user then checks the information displayed on the device. For example, "Environmental Protection Organization A" is described as "carrying out tree planting activities, and a donation of 3,000 yen will enable the planting of 10 trees."

[0131] 4. User Donation Choices

[0132] The user selects a nonprofit organization from the list, enters the donation amount in the input field, and then presses the "Donate" button. This action sends the data of the selected nonprofit organization and donation amount from the user's device to the server.

[0133] 5. Donation processing through integration with electronic payment systems

[0134] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0135] 6. Notification of donation completion and receipt issuance

[0136] If the donation is successful, the server will send a notification to the user that the donation has been completed. If the donation amount is above a certain amount (for example, 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt from the server and display them to the user. This will allow the user to confirm that the donation was processed successfully and save the receipt if necessary.

[0137] Examples of specific examples and prompts

[0138] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is working to plant 10 trees for a donation of 3,000 yen. If the user selects "Donate 5,000 yen to Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, and the user will be able to confirm that the donation was made validly.

[0139] Example prompt sentence:

[0140] "I'm interested in protecting the environment. What nonprofits can you recommend?"

[0141] "I would like to donate to educational support. Can you recommend any organizations?"

[0142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0143] Step 1:

[0144] User interest input

[0145] The user accesses a dedicated application or web page and logs in. The user enters their area of ​​interest (e.g., "environmental protection") in the input field and presses the submit button. The entered data is sent from the user's device to the server.

[0146] Input: User enters text of interest (e.g., "environmental protection")

[0147] Output: The submitted interest data is stored on the server.

[0148] Step 2:

[0149] Generative AI models recommend suitable nonprofits

[0150] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and has it recommend suitable nonprofit organizations. The generative AI model collects information from an internal database and external APIs to generate a list of the most suitable nonprofit organizations.

[0151] Input: User interest data

[0152] Output: A list of nonprofits according to their area of ​​interest

[0153] Specific behavior:

[0154] 1. The server queries the database to retrieve data related to the area of ​​interest.

[0155] 2. Input the acquired data into the generative AI model and receive recommendation results.

[0156] Step 3:

[0157] Explanation of recommendation results and donation effects

[0158] The server receives the list of nonprofit organizations output by the generative AI model, retrieves information about each organization's activities and the impact of donations from the database, formats this information, and sends it to the user's device. The user can then view the displayed list of nonprofit organizations and their detailed information.

[0159] Input: A list of nonprofits from a generative AI model

[0160] Output: A formatted list of nonprofits with details

[0161] Specific behavior:

[0162] 1. The server queries the database to retrieve details about each nonprofit organization.

[0163] 2. Format the acquired information and send it to the user's device.

[0164] Step 4:

[0165] User donation choices

[0166] The user selects a nonprofit organization from the list, enters the donation amount, and then presses the "Donate" button, which sends the selected nonprofit organization and donation amount data to the server.

[0167] Input: User-selected nonprofit and donation amount

[0168] Output: Nonprofit organization and donation amount data sent to the server

[0169] Step 5:

[0170] Donation processing through integration with electronic payment systems

[0171] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0172] Input: User-selected nonprofit organization and donation amount data

[0173] Output: Transaction processing results from the electronic payment system

[0174] Specific behavior:

[0175] 1. The server sends the donation amount and nonprofit organization to the payment API.

[0176] 2. Wait for a response from the electronic payment system and receive the processing result.

[0177] Step 6:

[0178] Donation completion notification and receipt issuance

[0179] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount (e.g., 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt and display them to the user.

[0180] Input: Transaction processing results from electronic payment system

[0181] Output: Donation completion notification and receipt (if applicable) to the user

[0182] Specific behavior:

[0183] 1. The server generates a donation completion notification and sends it to the user's device.

[0184] 2. For donations of 1,000 yen or more, the server automatically generates a receipt and sends it to the user.

[0185] (Application example 1)

[0186] 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."

[0187] In modern society, donations to nonprofit organizations are becoming increasingly important as a form of social contribution. However, the process of finding a nonprofit organization that matches a user's area of ​​interest and making a donation is complicated. Furthermore, if there is a lack of information about the effects of donations and the specific activities they carry out, it is difficult to attract users' attention. Furthermore, there is a need for a method to simplify the donation process by linking it with an electronic payment system. The purpose of this invention is to solve these problems and provide a system that allows users to donate to nonprofit organizations easily and effectively.

[0188] 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.

[0189] In this invention, the server includes: means for allowing a user to input their areas of interest; means for using a generative AI model to recommend appropriate nonprofit organizations based on the user's areas of interest; means for explaining the activities of the recommended nonprofit organizations and the benefits of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for linking with an electronic payment system to process the donation based on the input donation amount; means for sending the user a donation completion notification if the donation is successful and a receipt if the donation amount is above a predetermined amount; and means for integrating the entire process from inputting the user's areas of interest to notifying the electronic payment system of the completion of donation processing within a smartphone application. This allows users to easily find nonprofit organizations based on their areas of interest, understand the benefits of donations, and make donations easily.

[0190] "User" refers to an individual who uses an Electronic Device to make a donation to a nonprofit organization.

[0191] "Interest areas" refer to specific topics or issue areas that interest a user.

[0192] "Generative AI model" refers to a machine learning model that recommends suitable nonprofit organizations based on input data.

[0193] A "nonprofit organization" is a non-profit organization that pursues a specific social purpose.

[0194] "Smartphone Application" means a software application that runs on a smartphone.

[0195] "Electronic payment system" means an information technology system used to complete monetary transactions digitally.

[0196] "Donation Processing" refers to the series of steps taken to complete the transfer of money from a user to a nonprofit organization.

[0197] "Donation Completion Notification" refers to a message sent to a User to inform them that their donation has been successfully processed.

[0198] "Receipt" refers to any written or electronic evidence that proves a donation was made.

[0199] "Flow" refers to a series of operations or steps performed to achieve a specific goal.

[0200] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations. Specific embodiments of the present invention will now be described.

[0201] 1. Enter your user interests

[0202] Users input their areas of interest (e.g., "environmental protection") on the smartphone application. This input interface is provided through a dedicated input field. When the user inputs their area of ​​interest and presses the submit button, this data is sent to a server via the Internet.

[0203] 2. Generative AI model recommends suitable nonprofit organizations

[0204] The server receives the user's submitted interest data and passes it to a generative AI model, which then references an internal database and external APIs to generate a list of suitable nonprofits based on the user's input.

[0205] 3. Explanation of the recommendation results and the impact of the donation

[0206] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations. This information is formatted in a user-friendly format and provided to users through a smartphone application.

[0207] 4. User Donation Choices

[0208] The user selects a donation recipient from a list of nonprofit organizations and enters the amount of the donation. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. The user's selection and the entered donation amount are sent to the server.

[0209] 5. Donation processing through integration with electronic payment systems

[0210] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., a payment API) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0211] 6. Notification of donation completion and receipt issuance

[0212] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, a receipt will be automatically generated and sent to the user. The user can then view the notification and receipt on their smartphone application.

[0213] As a specific example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." Detailed descriptions of each organization are provided to the user, and if the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation via an electronic payment system and, if successful, sends the user a notification of donation completion and a receipt.

[0214] Example prompts to input to a generative AI model:

[0215] The user has entered the following area of ​​interest: Environmental protection. Please recommend suitable nonprofit organizations based on the following criteria:

[0216] conditions:

[0217] An organization that engages in environmental protection activities.

[0218] The specific activities and the effects of the donation must be clearly stated.

[0219] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0220] Step 1:

[0221] Users enter their areas of interest into the smartphone application, and the entered data is sent to a server via the Internet.

[0222] Input: Area of ​​interest (e.g. "Environmental protection")

[0223] Output: User interest data sent to the server

[0224] Step 2:

[0225] The server receives the user's submitted interest data, passes it to the generative AI model, and begins the process of recommending suitable nonprofit organizations.

[0226] Input: User interest data

[0227] Output: Data to be passed to the generative AI model

[0228] Step 3:

[0229] The generative AI model uses the interest data passed from the server to reference an internal database and external APIs to generate a list of suitable nonprofit organizations.

[0230] Input: Area of ​​interest data

[0231] Data Processing: Searching for nonprofit information from internal databases and external APIs

[0232] Output: A list of recommended nonprofits

[0233] Step 4:

[0234] Based on the list of nonprofit organizations received from the generative AI model, the server retrieves detailed information about each organization's activities and the impact of donations from its internal database and formats it into a form that can be provided to users.

[0235] Input: List of nominated nonprofits

[0236] Data processing: Acquisition and formatting of activity details and donation effect information from the internal database

[0237] Output: A list of nonprofits with formatted details.

[0238] Step 5:

[0239] The server then sends the formatted list of nonprofit organizations to the smartphone application and displays it to the user, who then decides which organization to donate to and how much to donate.

[0240] Input: A formatted list of nonprofits

[0241] Output: Information displayed on the smartphone application

[0242] Step 6:

[0243] The user selects the donation recipient and donation amount on the smartphone application and sends the entered data to the server.

[0244] Input: User's chosen donation destination and donation amount

[0245] Output: Donation recipient and donation amount data sent to the server

[0246] Step 7:

[0247] The server receives donation recipient and donation amount data from the user, sends the transaction to the electronic payment system, and processes the donation.

[0248] Input: Donation recipient and donation amount data

[0249] Output: Transaction data sent to electronic payment systems

[0250] Step 8:

[0251] The electronic payment system processes the transaction and sends the results back to the server, which receives the results and verifies whether the donation was successful.

[0252] Input: Transaction result data from electronic payment systems

[0253] Output: Confirmation of successful donation

[0254] Step 9:

[0255] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, the server will automatically generate a receipt and send it to the user.

[0256] Input: Donation success confirmation data

[0257] Output: Sending a donation completion notification and receipt

[0258] Step 10:

[0259] Users can check the donation completion notification and receipt on their smartphone application to confirm that their donation was successful.

[0260] Input: Donation completion notice and receipt

[0261] Output: Display on smartphone application

[0262] 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.

[0263] This invention is a system that combines an emotion engine that recognizes the user's emotions, allowing users to easily and effectively donate to non-profit organizations. Specific embodiments of this system will be described below.

[0264] 1. User interest and emotion recognition

[0265] User Device

[0266] The user accesses a dedicated application or web page and logs in to their account. After logging in, the user enters a value in an input field to indicate their area of ​​interest (e.g., "environmental protection").

[0267] Emotion Engine

[0268] Based on the user's inputted areas of interest, the emotion engine analyzes the user's emotions. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the text entered by the user.

[0269] 2. Generative AI model recommends suitable nonprofit organizations

[0270] server

[0271] The server receives the user's interest data and the results of the emotion engine analysis, and then passes the information to the generative AI model, instructing it to recommend suitable nonprofit organizations based on this data.

[0272] The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's sentiment and areas of interest. The results of the analysis by the sentiment engine provide optimal recommendations based on the user's sentiment.

[0273] 3. Explanation of the recommendation results and the impact of the donation

[0274] server

[0275] The server takes the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from the database, and formats this information to be presented to the user in a way that resonates with their emotions.

[0276] User Device

[0277] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. At this time, explanations and effects that correspond to the user's emotions are emphasized.

[0278] 4. User Donation Choices

[0279] User Device

[0280] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[0281] 5. Donation processing through integration with electronic payment systems

[0282] server

[0283] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to submit a transaction to the electronic payment system to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0284] 6. Notification of donation completion and receipt issuance

[0285] server

[0286] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0287] User Device

[0288] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0289] Specific examples

[0290] For example, if a user inputs that they are interested in "environmental protection," the emotion engine analyzes the user's input text. The generative AI model returns a list of recommendations: "Environmental Protection Organization A" and "Environmental Protection Organization B." Depending on the user's emotions, explanations that resonate with the user's emotions are emphasized when explaining the activities of each nonprofit organization and the effects of donations. If the user then selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[0291] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[0292] The processing flow will be explained below.

[0293] Step 1:

[0294] User Device

[0295] The user accesses a dedicated application or web page and logs in to their account.

[0296] Step 2:

[0297] User Device

[0298] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[0299] Step 3:

[0300] server

[0301] The server receives the area of ​​interest data sent by the user.

[0302] Step 4:

[0303] Emotion Engine

[0304] The emotion engine analyzes the user's input data and recognizes the user's emotion, which is then used throughout the system.

[0305] Step 5:

[0306] server

[0307] The server passes the user's interest data and the results of the sentiment engine analysis to the generative AI model, instructing it to recommend appropriate nonprofit organizations.

[0308] Step 6:

[0309] Generative AI Models

[0310] A generative AI model searches a database for relevant nonprofit listings based on the user's areas of interest and sentiment, generating the best recommendation list.

[0311] Step 7:

[0312] server

[0313] The server receives the list of nonprofit organizations returned by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from a database.

[0314] Step 8:

[0315] server

[0316] The acquired information is formatted, emphasis is added based on the user's emotions, and it is then converted into a form that can be presented to the user.

[0317] Step 9:

[0318] server

[0319] The formatted information is sent to the user's device.

[0320] Step 10:

[0321] User Device

[0322] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[0323] Step 11:

[0324] User Device

[0325] The user selects a donation destination from the recommended nonprofit organizations, enters a value in the donation amount field, and clicks the donate button.

[0326] Step 12:

[0327] server

[0328] The server receives the selected nonprofit organization and donation amount data submitted by the user.

[0329] Step 13:

[0330] server

[0331] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[0332] Step 14:

[0333] Electronic payment system

[0334] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[0335] Step 15:

[0336] server

[0337] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[0338] Step 16:

[0339] server

[0340] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0341] Step 17:

[0342] User Device

[0343] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user can confirm that the donation was successful and save the receipt if necessary.

[0344] As a concrete example, suppose a user indicates an interest in "environmental protection," and the emotion engine recognizes a "positive" emotion. The generative AI model recommends "Environmental Protection Organization A" and "Environmental Protection Organization B," explaining to the user that "Environmental Protection Organization A is engaged in tree planting activities, and a donation of 3,000 yen will allow 10 trees to be planted," while emphasizing the emotional element that "their activities will significantly contribute to preventing global warming." As a result, the user selects to donate 5,000 yen to "Environmental Protection Organization A," and the server processes the donation through the electronic payment system. If the donation is successful, a receipt is sent along with a notification of donation completion, which is displayed on the user's device. The user can confirm that their donation was made validly, and feel a sense of satisfaction.

[0345] Example 2

[0346] 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."

[0347] When users donate to nonprofit organizations, it is difficult to determine which organization is the most appropriate, and the donation process is often cumbersome, making the activity tedious. In particular, there is a concern that users' motivation to donate may decrease due to a lack of emotionally appealing explanations of the benefits and activities of donations. Therefore, there is a need for a system that can recommend appropriate nonprofit organizations based on users' emotions, simplify the donation process, and increase emotional satisfaction.

[0348] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0349] In this invention, the server includes a means for a user to input an area of ​​interest, a means for analyzing the user's emotions using an emotion recognition engine based on the area of ​​interest input by the user, and a means for recommending an appropriate business entity using a generative AI model based on the analyzed emotions and area of ​​interest. This makes it possible to recommend the most appropriate nonprofit organization according to the user's emotions, simplify the donation process, and increase the user's emotional satisfaction.

[0350] 1. "User" means an individual or organization that uses the System to make donations to a non-profit organization.

[0351] 2. "Area of ​​Interest" refers to a specific area or topic that a user is interested in.

[0352] 3. An "emotion recognition engine" is a technology that analyzes the user's input text and recognizes emotional trends.

[0353] 4. "Generative AI model" means an artificial intelligence model that recommends appropriate businesses based on a user's emotions and areas of interest.

[0354] 5. "Entity" means a nonprofit organization or other charitable organization.

[0355] 6. "Electronic Payment System" means an online payment system for conducting monetary transactions via the Internet.

[0356] 7. "Payment Interface" means a technical means for interfacing with an electronic payment system to process transactions.

[0357] 8. "Transaction processing result" means the processing result information returned from the electronic payment system.

[0358] 9. "Receipt" means a document issued to certify that a donation has been made successfully.

[0359] This invention is a system that combines an emotion recognition engine that recognizes user emotions with a generative AI model, allowing users to easily and effectively make donations to nonprofit organizations.

[0360] System Overview

[0361] The system consists of a user terminal, a server, an emotion recognition engine, a generative AI model, and an electronic payment system. The role and operation of each component are explained in detail below.

[0362] User Device

[0363] The user terminal is operated through a dedicated application or web page, where the user logs into their account and enters their area of ​​interest (e.g., "environmental protection").

[0364] Emotion Recognition Engine

[0365] The emotion recognition engine analyzes the user's emotions based on the areas of interest entered by the user. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the user's text. For example, if a user enters "I'm concerned about environmental issues," that emotion is analyzed and stored as data.

[0366] Generative AI Models

[0367] The server receives the user's interest data and the analysis results of the emotion recognition engine. Based on this data, it passes information to a generative AI model that recommends suitable nonprofit organizations. This generative AI model collects information from an internal database and external APIs and generates a list of nonprofit organizations that best fit the user's emotions and areas of interest.

[0368] Presentation of recommendation results

[0369] The server obtains the list of nonprofit organizations output by the generative AI model and collects detailed information from a database about each organization's activities and the impact of donations. This information is formatted to resonate with the user's emotions and sent to the user's device. The user's device receives the information sent from the server and displays the list of nonprofit organizations and their detailed information to the user. For example, it may display information such as "Environmental Protection Organization A" "carries out tree planting activities and plants 10 trees for a donation of 3,000 yen."

[0370] Select and enter your donation

[0371] Users select a donation destination from the recommended nonprofit organizations and enter the donation amount, which is then sent to a server and sent as transaction data to an electronic payment system.

[0372] Processing donations

[0373] The server interacts with the electronic payment system, processes the donation based on the transaction data sent, receives a response from the electronic payment system, and verifies whether the donation was successful.

[0374] Donation completion notification and receipt issuance

[0375] If the donation is successful, the server sends the user a notification of the completion of the donation, and if the donation amount is equal to or greater than a predetermined amount, it automatically generates and sends a receipt. The user's device receives this notification and receipt and displays them to the user.

[0376] Specific examples

[0377] For example, if a user inputs that they are interested in "environmental protection," the emotion recognition engine analyzes the user's input text and the generative AI model recommends appropriate nonprofit organizations. The explanation is emphasized according to the user's emotion. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system and, if successful, sends the user a receipt along with a notification of the completed donation. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[0378] Prompt Sentence Examples

[0379] "If I'm interested in protecting the environment, what nonprofits would you recommend?"

[0380] "Explain how to use an emotion recognition engine to analyze user emotions."

[0381] "What notification will be sent to users upon successful donation?"

[0382] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[0383] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0384] Step 1:

[0385] user

[0386] Users access a dedicated application or web page and log in to their account. They enter their user ID and password on the login screen, and once authentication is successful, the main screen is displayed.

[0387] Input: User ID, Password

[0388] Output: Authentication success message, main screen display

[0389] Step 2:

[0390] user

[0391] The user enters the area of ​​interest (e.g., "environmental protection") into the input field on the main screen, and then clicks the "Submit" button.

[0392] Input: Area of ​​interest (e.g., "environmental protection")

[0393] Output: Region of interest data transmission

[0394] Step 3:

[0395] Emotion Recognition Engine

[0396] The emotion recognition engine receives the area of ​​interest data sent by the user and analyzes the user's emotions using natural language processing technology. For example, it recognizes the emotion "worry" from the input "I'm worried about environmental issues."

[0397] Input: Region of interest data

[0398] Output: Sentiment analysis result (e.g. "worried")

[0399] Step 4:

[0400] server

[0401] The server receives and temporarily stores the analyzed emotion and interest data, and then passes this data to the generative AI model, which then instructs it to recommend suitable nonprofit organizations.

[0402] Input: Sentiment analysis results, area of ​​interest data

[0403] Output: Data provision instructions

[0404] Step 5:

[0405] Generative AI Models

[0406] The generative AI model uses data provided by the server, collects information from internal databases and external APIs, and generates a list of the most suitable nonprofit organizations.

[0407] Input: Sentiment analysis results, area of ​​interest data

[0408] Output: List of recommended nonprofits

[0409] Step 6:

[0410] server

[0411] The server receives the list of recommended nonprofit organizations obtained from the generative AI model, collects detailed information about each organization's activities and the impact of donations from a database, formats this information to resonate with the user's emotions, and sends it to the user's device.

[0412] Input: List of recommended nonprofit organizations

[0413] Output: Formatted organization information

[0414] Step 7:

[0415] User Device

[0416] The user device receives the list of nonprofit organizations and their details from the server and displays them to the user. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[0417] Input: Formatted organization information

[0418] Output: Group information display

[0419] Step 8:

[0420] user

[0421] Users can select a donation recipient from a list of nonprofit organizations, enter the amount they would like to donate, and then click the "Donate" button to send the selected organization and donation amount to the server.

[0422] Input: Donation destination selection, donation amount

[0423] Output: Send donation information

[0424] Step 9:

[0425] server

[0426] The server receives the donation recipient and donation amount data sent by the user and sends it to the electronic payment system as transaction data. The electronic payment system processes the donation based on this transaction data.

[0427] Input: Donation recipient, donation amount

[0428] Output: Transaction data sent

[0429] Step 10:

[0430] Electronic Payment Systems

[0431] The electronic payment system processes the donation and returns the result to the server, which receives the result and verifies whether the donation was successful.

[0432] Input: Transaction data

[0433] Output: Donation processing result

[0434] Step 11:

[0435] server

[0436] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[0437] Input: Donation processing result

[0438] Output: Donation completion notification, receipt

[0439] Step 12:

[0440] User Device

[0441] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0442] Input: Donation completion notification, receipt

[0443] Output: Notification display, receipt display

[0444] (Application example 2)

[0445] 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."

[0446] When promoting donations to nonprofit organizations, it is necessary not only to recommend appropriate organizations based on the user's areas of interest, but also to suggest donations that are tailored to the user's emotions. Furthermore, to increase the user's satisfaction after donating, it is necessary to explain the effects of donations and the activities involved in them in an emotional way. Furthermore, it is necessary to link seamlessly with an electronic payment system to simplify the donation process. The lack of an integrated system that satisfies these multiple requirements is a challenge.

[0447] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0448] In this invention, the server includes: means for allowing a user to input areas of interest; emotion recognition means for analyzing the user's input areas of interest and emotions; means for recommending appropriate nonprofit organizations using a generative AI model based on emotion data obtained from the emotion recognition means; means for explaining the activities of the recommended nonprofit organizations and the effects of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for processing the donation in cooperation with an electronic payment system based on the input donation amount; and means for sending the user a donation completion notification when the donation is successful and a receipt if the donation amount is above a predetermined amount. This makes it possible to recommend appropriate nonprofit organizations for donations based on the user's emotions and areas of interest, making the donation process simple and effective.

[0449] A "means for user input of areas of interest" is a device or software that provides an interface for users to input their areas of interest through text or options.

[0450] "Emotion recognition means for analyzing emotions" is software that has the function of analyzing emotions from text entered by a user using natural language processing technology and recognizing the emotional state as a number or category.

[0451] "Means for recommending appropriate nonprofit organizations using a generative AI model" refers to algorithms and software that utilize a generative AI model to extract appropriate nonprofit organizations and generate a recommendation list based on a user's areas of interest and emotional data.

[0452] The "means for explaining the activities of the recommended nonprofit organization and the impact of donations" is software that has the function of generating text and diagrams that clearly explain to users the activities of the recommended nonprofit organization and how donations will be used.

[0453] A "means for providing an explanation to a user" is a device or software that displays visual and textual information to a user about the recommended nonprofit organization and the impact of the donation.

[0454] A "means for a user to input a donation amount to a nonprofit organization selected by the user" is a device or software that provides an interface for a user to input a donation destination and donation amount.

[0455] The "means for processing donations in cooperation with the electronic payment system based on the entered donation amount" refers to the algorithm and software for transmitting the donation amount entered by the user to the electronic payment system, processing the payment, and receiving the transaction results.

[0456] "Means for notifying the user that a donation has been successfully completed and sending a receipt if the donation amount is equal to or greater than a specified amount" refers to software that has the functionality to notify the user that a donation has been successfully completed and to automatically generate and send a receipt if necessary.

[0457] This invention is a system for analyzing a user's areas of interest and emotions, recommending appropriate non-profit organizations, and making donations seamlessly. Specific embodiments of this system will be described below.

[0458] 1. User interest and emotion recognition

[0459] User Device

[0460] First, users access a dedicated application or website and log in to their account. After logging in, they enter their areas of interest (e.g., "environmental protection") in the input field. They can also enter comments and opinions, which are then used for emotion recognition. Sentiment analysis is performed using the Google Cloud Natural Language API.

[0461] 2. Generative AI model recommends suitable nonprofit organizations

[0462] server

[0463] The server receives interest and sentiment data submitted by the user. This data is passed to a generative AI model, such as OpenAI's GPT-3, which then recommends the most suitable nonprofit organization based on the sentiment data. An example of an input prompt for the generative AI model is as follows:

[0464] Prompt Sentence Examples

[0465] The user's area of ​​interest is environmental protection. The sentiment score is 0.8. Generate a list of recommended nonprofit organizations.

[0466] 3. Explanation of the recommendation results and the impact of the donation

[0467] server

[0468] The server retrieves the list of nonprofit organizations output by the generative AI model from the database, obtains detailed information about each organization's activities and the impact of donations, and formats it to resonate with the user's emotions.

[0469] User Device

[0470] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[0471] 4. User Donation Choices

[0472] User Device

[0473] The user selects a nonprofit organization from the list of recommended organizations, enters a value in the donation amount field, and clicks the donate button, which sends the selected organization and donation amount to the server.

[0474] 5. Donation processing through integration with electronic payment systems

[0475] server

[0476] The server receives the donation recipient and donation amount data submitted by the user, uses this information to process the donation through an electronic payment system such as Stripe, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0477] 6. Notification of donation completion and receipt issuance

[0478] server

[0479] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[0480] User Device

[0481] The user's device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0482] This system allows users to donate to nonprofit organizations easily and effectively while increasing emotional satisfaction.

[0483] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0484] Step 1:

[0485] Users access a dedicated application or website and log in to their account. At this time, a login screen appears on the user's device and the user enters their username and password. The entered login information is sent to the server for authentication. If authentication is successful, the user's dashboard is displayed.

[0486] Step 2:

[0487] The user enters the areas of interest in the input field. They can also optionally enter comments or opinions. This information is sent from the user's device to the server. A specific example of input is text such as "I'm interested in environmental protection." The server receives this information and analyzes it using emotion recognition means. The user's text is given as input, and an emotion score (e.g., 0.8) is obtained as output.

[0488] Step 3:

[0489] The server uses the Google Cloud Natural Language API to analyze the sentiment from the text entered by the user. This API analyzes the input text data and outputs a sentiment score and sentiment category (positive, negative, neutral). Based on this output, the user's sentiment data is stored on the server.

[0490] Step 4:

[0491] The server passes the emotion data and the user's areas of interest to a generative AI model. This generative AI model (for example, OpenAI GPT-3) generates a prompt based on the input data and outputs a list of the most suitable nonprofit organizations. An example of a specific prompt is as follows: "The user's area of ​​interest is environmental protection. The emotion score is 0.8. Please generate a list of recommended nonprofit organizations." This prompt is input into the AI ​​model, and a list of nonprofit organizations (for example, environmental protection organization A and environmental protection organization B) is obtained as output.

[0492] Step 5:

[0493] Based on the generated list of nonprofit organizations, the server retrieves detailed information about each organization's activities and the impact of donations from the database. This allows the server to collect information such as the specific activities of the nonprofit organization and the purpose of the donation (e.g., a donation of 3,000 yen will plant 10 trees for tree planting activities). The server formats this information to resonate with the user's emotions and sends it to the user's device.

[0494] Step 6:

[0495] The user's device displays the list of nonprofit organizations and their detailed information sent from the server. The user can review the options for multiple nonprofit organizations on the screen and decide on a specific donation recipient and donation amount (e.g., a donation of 5,000 yen to environmental protection organization A). Once the user makes a selection, the information is sent back to the server.

[0496] Step 7:

[0497] The server receives the data of the nonprofit organization and donation amount selected by the user, and processes the donation by connecting with an electronic payment system such as Stripe. This process involves sending the donation amount using a payment API, and the transaction result is returned. If successful, the donation procedure is completed.

[0498] Step 8:

[0499] If the donation is successful, the server sends the user a notification that the donation has been completed, and if the donation amount is above a certain amount, it automatically generates and sends a receipt. For example, if the donation amount is above 1,000 yen, a receipt will be sent by email. The user's device receives the notification and receipt and displays them to the user. The user can check this display and save the receipt if necessary.

[0500] 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.

[0501] 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.

[0502] 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.

[0503] [Second embodiment]

[0504] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0505] 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.

[0506] 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).

[0507] 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.

[0508] 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.

[0509] 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).

[0510] 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.

[0511] 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.

[0512] 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.

[0513] 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.

[0514] 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.

[0515] 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."

[0516] The present invention relates to a system that allows users to easily and effectively make donations to non-profit organizations. A specific embodiment of this system will be described below.

[0517] 1. Enter your user interests

[0518] User Device

[0519] A user accesses a dedicated application or web page and logs in. After logging in, the user enters values ​​into input fields to indicate the areas of interest (e.g., "environmental protection"), and when the user presses the submit button, this input data is sent to the server.

[0520] 2. Generative AI model recommends suitable nonprofit organizations

[0521] server

[0522] The server receives user-submitted interest data, passes this data to a generative AI model, which then recommends suitable nonprofits based on the user's interests. The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's input.

[0523] 3. Explanation of the recommendation results and the impact of the donation

[0524] server

[0525] The server receives the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from a database, and formats this information into a format that can be presented to users.

[0526] User Device

[0527] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, it may display information such as "Environmental Protection Organization A" is "carrying out tree planting activities and planting 10 trees for a donation of 3,000 yen."

[0528] 4. User Donation Choices

[0529] User Device

[0530] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[0531] 5. Donation processing through integration with electronic payment systems

[0532] server

[0533] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., PayPay) to process the donation, and receives a response from the electronic payment system confirming whether the donation was successful.

[0534] 6. Notification of donation completion and receipt issuance

[0535] server

[0536] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0537] User Device

[0538] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0539] Specific examples

[0540] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is engaged in tree planting activities, and that a donation of 3,000 yen will plant 10 trees. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, allowing the user to confirm that the donation was made validly.

[0541] This system allows users to easily and effectively donate to non-profit organizations, giving them a sense of social contribution.

[0542] The processing flow will be explained below.

[0543] Step 1:

[0544] User Device

[0545] The user accesses a dedicated application or web page and logs in to their account.

[0546] Step 2:

[0547] User Device

[0548] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[0549] Step 3:

[0550] server

[0551] The server receives the area of ​​interest data sent by the user.

[0552] Step 4:

[0553] server

[0554] The server passes the received data to a generative AI model, which then uses an internal database or external API to generate a list of relevant nonprofits.

[0555] Step 5:

[0556] server

[0557] The generative AI model obtains a list of recommended nonprofit organizations, and then retrieves information about each organization's activities and the effectiveness of donations from a database.

[0558] Step 6:

[0559] server

[0560] Format and deliver information about nonprofits and the impact of donations to users.

[0561] Step 7:

[0562] server

[0563] The formatted information is sent to the user's device.

[0564] Step 8:

[0565] User Device

[0566] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[0567] Step 9:

[0568] User Device

[0569] The user selects a donation destination from the recommended nonprofit organizations, enters the donation amount in the input field, and presses the donate button.

[0570] Step 10:

[0571] server

[0572] The server receives the selected nonprofit organization and donation amount submitted by the user.

[0573] Step 11:

[0574] server

[0575] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[0576] Step 12:

[0577] Electronic payment system

[0578] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[0579] Step 13:

[0580] server

[0581] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[0582] Step 14:

[0583] server

[0584] If the donation is successful, a notification will be sent to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0585] Step 15:

[0586] User Device

[0587] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user confirms that the donation was successful and saves the receipt.

[0588] As a specific example, when a user enters "environmental protection," the generative AI model returns a list of recommendations including "environmental protection organization A" and "environmental protection organization B." If the user then selects to donate 5,000 yen to "environmental protection organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification of the completed donation.

[0589] Example 1

[0590] 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."

[0591] In modern society, users face challenges when making donations to nonprofit organizations, as it requires a lot of time and effort and information gathering. It is also difficult for users to find nonprofit organizations that fit their areas of interest. Furthermore, the donation process faces challenges due to the lack of smooth integration with electronic payment systems.

[0592] 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.

[0593] In this invention, the server includes a means for a user to input areas of interest, a means for recommending appropriate organizations using a generative AI model based on the areas of interest input by the user, and a means for explaining the activities of the recommended organizations and the effects of donations, allowing users to easily find nonprofit organizations that fit their areas of interest and making the donation process smoother.

[0594] "User" means an individual or organization that uses the System to make donations to a nonprofit organization.

[0595] "Areas of Interest" are specific categories or topics that users consider important, such as environmental protection, educational support, or medical assistance.

[0596] A "generative AI model" is a type of artificial intelligence technology that recommends suitable nonprofit organizations based on a user's areas of interest. It collects information from internal databases and external APIs to present the best candidates.

[0597] A "non-profit organization" is an organization that does not aim to make a profit but works to solve social problems or for the public good.

[0598] "Activities" refers to the specific projects and initiatives undertaken by the nonprofit organization, such as tree planting activities or educational programs.

[0599] "Effectiveness of Donations" provides detailed information about how users' donated funds are utilized and the results they produce.

[0600] An "electronic payment system" is a system for processing payments online, such as payments using electronic wallets or credit cards.

[0601] "Receipt" means the official payment confirmation issued to a User upon successful Donation.

[0602] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations.

[0603] 1. Enter your user interests

[0604] The user accesses a dedicated application or web page and logs in. After logging in, the user enters information in the field for entering their areas of interest. For example, if the user is interested in "environmental protection," they enter this information and press the "Submit" button. This data is sent from the user's device to the server.

[0605] 2. Generative AI model recommends suitable nonprofit organizations

[0606] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and the model recommends suitable nonprofit organizations based on the user's areas of interest. The generative AI model collects information from an internal database and external APIs and generates a list of the most suitable nonprofit organizations based on the user's input data.

[0607] 3. Explanation of the recommendation results and the impact of the donation

[0608] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from the database. This information is formatted and sent to the user's device. The user then checks the information displayed on the device. For example, "Environmental Protection Organization A" is described as "carrying out tree planting activities, and a donation of 3,000 yen will enable the planting of 10 trees."

[0609] 4. User Donation Choices

[0610] The user selects a nonprofit organization from the list, enters the donation amount in the input field, and then presses the "Donate" button. This action sends the data of the selected nonprofit organization and donation amount from the user's device to the server.

[0611] 5. Donation processing through integration with electronic payment systems

[0612] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0613] 6. Notification of donation completion and receipt issuance

[0614] If the donation is successful, the server will send a notification to the user that the donation has been completed. If the donation amount is above a certain amount (for example, 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt from the server and display them to the user. This will allow the user to confirm that the donation was processed successfully and save the receipt if necessary.

[0615] Examples of specific examples and prompts

[0616] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is working to plant 10 trees for a donation of 3,000 yen. If the user selects "Donate 5,000 yen to Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, and the user will be able to confirm that the donation was made validly.

[0617] Example prompt sentence:

[0618] "I'm interested in protecting the environment. What nonprofits can you recommend?"

[0619] "I would like to donate to educational support. Can you recommend any organizations?"

[0620] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0621] Step 1:

[0622] User interest input

[0623] The user accesses a dedicated application or web page and logs in. The user enters their area of ​​interest (e.g., "environmental protection") in the input field and presses the submit button. The entered data is sent from the user's device to the server.

[0624] Input: User enters text of interest (e.g., "environmental protection")

[0625] Output: The submitted interest data is stored on the server.

[0626] Step 2:

[0627] Generative AI models recommend suitable nonprofits

[0628] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and has it recommend suitable nonprofit organizations. The generative AI model collects information from an internal database and external APIs to generate a list of the most suitable nonprofit organizations.

[0629] Input: User interest data

[0630] Output: A list of nonprofits according to their area of ​​interest

[0631] Specific behavior:

[0632] 1. The server queries the database to retrieve data related to the area of ​​interest.

[0633] 2. Input the acquired data into the generative AI model and receive recommendation results.

[0634] Step 3:

[0635] Explanation of recommendation results and donation effects

[0636] The server receives the list of nonprofit organizations output by the generative AI model, retrieves information about each organization's activities and the impact of donations from the database, formats this information, and sends it to the user's device. The user can then view the displayed list of nonprofit organizations and their detailed information.

[0637] Input: A list of nonprofits from a generative AI model

[0638] Output: A formatted list of nonprofits with details

[0639] Specific behavior:

[0640] 1. The server queries the database to retrieve details about each nonprofit organization.

[0641] 2. Format the acquired information and send it to the user's device.

[0642] Step 4:

[0643] User donation choices

[0644] The user selects a nonprofit organization from the list, enters the donation amount, and then presses the "Donate" button, which sends the selected nonprofit organization and donation amount data to the server.

[0645] Input: User-selected nonprofit and donation amount

[0646] Output: Nonprofit organization and donation amount data sent to the server

[0647] Step 5:

[0648] Donation processing through integration with electronic payment systems

[0649] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0650] Input: User-selected nonprofit organization and donation amount data

[0651] Output: Transaction processing results from the electronic payment system

[0652] Specific behavior:

[0653] 1. The server sends the donation amount and nonprofit organization to the payment API.

[0654] 2. Wait for a response from the electronic payment system and receive the processing result.

[0655] Step 6:

[0656] Donation completion notification and receipt issuance

[0657] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount (e.g., 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt and display them to the user.

[0658] Input: Transaction processing results from electronic payment system

[0659] Output: Donation completion notification and receipt (if applicable) to the user

[0660] Specific behavior:

[0661] 1. The server generates a donation completion notification and sends it to the user's device.

[0662] 2. For donations of 1,000 yen or more, the server automatically generates a receipt and sends it to the user.

[0663] (Application example 1)

[0664] 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."

[0665] In modern society, donations to nonprofit organizations are becoming increasingly important as a form of social contribution. However, the process of finding a nonprofit organization that matches a user's area of ​​interest and making a donation is complicated. Furthermore, if there is a lack of information about the effects of donations and the specific activities they carry out, it is difficult to attract users' attention. Furthermore, there is a need for a method to simplify the donation process by linking it with an electronic payment system. The purpose of this invention is to solve these problems and provide a system that allows users to donate to nonprofit organizations easily and effectively.

[0666] 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.

[0667] In this invention, the server includes: means for allowing a user to input their areas of interest; means for using a generative AI model to recommend appropriate nonprofit organizations based on the user's areas of interest; means for explaining the activities of the recommended nonprofit organizations and the benefits of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for linking with an electronic payment system to process the donation based on the input donation amount; means for sending the user a donation completion notification if the donation is successful and a receipt if the donation amount is above a predetermined amount; and means for integrating the entire process from inputting the user's areas of interest to notifying the electronic payment system of the completion of donation processing within a smartphone application. This allows users to easily find nonprofit organizations based on their areas of interest, understand the benefits of donations, and make donations easily.

[0668] "User" refers to an individual who uses an Electronic Device to make a donation to a nonprofit organization.

[0669] "Interest areas" refer to specific topics or issue areas that interest a user.

[0670] "Generative AI model" refers to a machine learning model that recommends suitable nonprofit organizations based on input data.

[0671] A "nonprofit organization" is a non-profit organization that pursues a specific social purpose.

[0672] "Smartphone Application" means a software application that runs on a smartphone.

[0673] "Electronic payment system" means an information technology system used to complete monetary transactions digitally.

[0674] "Donation Processing" refers to the series of steps taken to complete the transfer of money from a user to a nonprofit organization.

[0675] "Donation Completion Notification" refers to a message sent to a User to inform them that their donation has been successfully processed.

[0676] "Receipt" refers to any written or electronic evidence that proves a donation was made.

[0677] "Flow" refers to a series of operations or steps performed to achieve a specific goal.

[0678] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations. Specific embodiments of the present invention will now be described.

[0679] 1. Enter your user interests

[0680] Users input their areas of interest (e.g., "environmental protection") on the smartphone application. This input interface is provided through a dedicated input field. When the user inputs their area of ​​interest and presses the submit button, this data is sent to a server via the Internet.

[0681] 2. Generative AI model recommends suitable nonprofit organizations

[0682] The server receives the user's submitted interest data and passes it to a generative AI model, which then references an internal database and external APIs to generate a list of suitable nonprofits based on the user's input.

[0683] 3. Explanation of the recommendation results and the impact of the donation

[0684] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations. This information is formatted in a user-friendly format and provided to users through a smartphone application.

[0685] 4. User Donation Choices

[0686] The user selects a donation recipient from a list of nonprofit organizations and enters the amount of the donation. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. The user's selection and the entered donation amount are sent to the server.

[0687] 5. Donation processing through integration with electronic payment systems

[0688] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., a payment API) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0689] 6. Notification of donation completion and receipt issuance

[0690] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, a receipt will be automatically generated and sent to the user. The user can then view the notification and receipt on their smartphone application.

[0691] As a specific example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." Detailed descriptions of each organization are provided to the user, and if the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation via an electronic payment system and, if successful, sends the user a notification of donation completion and a receipt.

[0692] Example prompts to input to a generative AI model:

[0693] The user has entered the following area of ​​interest: Environmental protection. Please recommend suitable nonprofit organizations based on the following criteria:

[0694] conditions:

[0695] An organization that engages in environmental protection activities.

[0696] The specific activities and the effects of the donation must be clearly stated.

[0697] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0698] Step 1:

[0699] Users enter their areas of interest into the smartphone application, and the entered data is sent to a server via the Internet.

[0700] Input: Area of ​​interest (e.g. "Environmental protection")

[0701] Output: User interest data sent to the server

[0702] Step 2:

[0703] The server receives the user's submitted interest data, passes it to the generative AI model, and begins the process of recommending suitable nonprofit organizations.

[0704] Input: User interest data

[0705] Output: Data to be passed to the generative AI model

[0706] Step 3:

[0707] The generative AI model uses the interest data passed from the server to reference an internal database and external APIs to generate a list of suitable nonprofit organizations.

[0708] Input: Area of ​​interest data

[0709] Data Processing: Searching for nonprofit information from internal databases and external APIs

[0710] Output: A list of recommended nonprofits

[0711] Step 4:

[0712] Based on the list of nonprofit organizations received from the generative AI model, the server retrieves detailed information about each organization's activities and the impact of donations from its internal database and formats it into a form that can be provided to users.

[0713] Input: List of nominated nonprofits

[0714] Data processing: Acquisition and formatting of activity details and donation effect information from the internal database

[0715] Output: A list of nonprofits with formatted details.

[0716] Step 5:

[0717] The server then sends the formatted list of nonprofit organizations to the smartphone application and displays it to the user, who then decides which organization to donate to and how much to donate.

[0718] Input: A formatted list of nonprofits

[0719] Output: Information displayed on the smartphone application

[0720] Step 6:

[0721] The user selects the donation recipient and donation amount on the smartphone application and sends the entered data to the server.

[0722] Input: User's chosen donation destination and donation amount

[0723] Output: Donation recipient and donation amount data sent to the server

[0724] Step 7:

[0725] The server receives donation recipient and donation amount data from the user, sends the transaction to the electronic payment system, and processes the donation.

[0726] Input: Donation recipient and donation amount data

[0727] Output: Transaction data sent to electronic payment systems

[0728] Step 8:

[0729] The electronic payment system processes the transaction and sends the results back to the server, which receives the results and verifies whether the donation was successful.

[0730] Input: Transaction result data from electronic payment systems

[0731] Output: Confirmation of successful donation

[0732] Step 9:

[0733] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, the server will automatically generate a receipt and send it to the user.

[0734] Input: Donation success confirmation data

[0735] Output: Sending a donation completion notification and receipt

[0736] Step 10:

[0737] Users can check the donation completion notification and receipt on their smartphone application to confirm that their donation was successful.

[0738] Input: Donation completion notice and receipt

[0739] Output: Display on smartphone application

[0740] 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.

[0741] This invention is a system that combines an emotion engine that recognizes the user's emotions, allowing users to easily and effectively donate to non-profit organizations. Specific embodiments of this system will be described below.

[0742] 1. User interest and emotion recognition

[0743] User Device

[0744] The user accesses a dedicated application or web page and logs in to their account. After logging in, the user enters a value in an input field to indicate their area of ​​interest (e.g., "environmental protection").

[0745] Emotion Engine

[0746] Based on the user's inputted areas of interest, the emotion engine analyzes the user's emotions. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the text entered by the user.

[0747] 2. Generative AI model recommends suitable nonprofit organizations

[0748] server

[0749] The server receives the user's interest data and the results of the emotion engine analysis, and then passes the information to the generative AI model, instructing it to recommend suitable nonprofit organizations based on this data.

[0750] The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's sentiment and areas of interest. The results of the analysis by the sentiment engine provide optimal recommendations based on the user's sentiment.

[0751] 3. Explanation of the recommendation results and the impact of the donation

[0752] server

[0753] The server takes the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from the database, and formats this information to be presented to the user in a way that resonates with their emotions.

[0754] User Device

[0755] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. At this time, explanations and effects that correspond to the user's emotions are emphasized.

[0756] 4. User Donation Choices

[0757] User Device

[0758] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[0759] 5. Donation processing through integration with electronic payment systems

[0760] server

[0761] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to submit a transaction to the electronic payment system to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0762] 6. Notification of donation completion and receipt issuance

[0763] server

[0764] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0765] User Device

[0766] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0767] Specific examples

[0768] For example, if a user inputs that they are interested in "environmental protection," the emotion engine analyzes the user's input text. The generative AI model returns a list of recommendations: "Environmental Protection Organization A" and "Environmental Protection Organization B." Depending on the user's emotions, explanations that resonate with the user's emotions are emphasized when explaining the activities of each nonprofit organization and the effects of donations. If the user then selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[0769] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[0770] The processing flow will be explained below.

[0771] Step 1:

[0772] User Device

[0773] The user accesses a dedicated application or web page and logs in to their account.

[0774] Step 2:

[0775] User Device

[0776] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[0777] Step 3:

[0778] server

[0779] The server receives the area of ​​interest data sent by the user.

[0780] Step 4:

[0781] Emotion Engine

[0782] The emotion engine analyzes the user's input data and recognizes the user's emotion, which is then used throughout the system.

[0783] Step 5:

[0784] server

[0785] The server passes the user's interest data and the results of the sentiment engine analysis to the generative AI model, instructing it to recommend appropriate nonprofit organizations.

[0786] Step 6:

[0787] Generative AI Models

[0788] A generative AI model searches a database for relevant nonprofit listings based on the user's areas of interest and sentiment, generating the best recommendation list.

[0789] Step 7:

[0790] server

[0791] The server receives the list of nonprofit organizations returned by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from a database.

[0792] Step 8:

[0793] server

[0794] The acquired information is formatted, emphasis is added based on the user's emotions, and it is then converted into a form that can be presented to the user.

[0795] Step 9:

[0796] server

[0797] The formatted information is sent to the user's device.

[0798] Step 10:

[0799] User Device

[0800] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[0801] Step 11:

[0802] User Device

[0803] The user selects a donation destination from the recommended nonprofit organizations, enters a value in the donation amount field, and clicks the donate button.

[0804] Step 12:

[0805] server

[0806] The server receives the selected nonprofit organization and donation amount data submitted by the user.

[0807] Step 13:

[0808] server

[0809] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[0810] Step 14:

[0811] Electronic payment system

[0812] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[0813] Step 15:

[0814] server

[0815] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[0816] Step 16:

[0817] server

[0818] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[0819] Step 17:

[0820] User Device

[0821] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user can confirm that the donation was successful and save the receipt if necessary.

[0822] As a concrete example, suppose a user indicates an interest in "environmental protection," and the emotion engine recognizes a "positive" emotion. The generative AI model recommends "Environmental Protection Organization A" and "Environmental Protection Organization B," explaining to the user that "Environmental Protection Organization A is engaged in tree planting activities, and a donation of 3,000 yen will allow 10 trees to be planted," while emphasizing the emotional element that "their activities will significantly contribute to preventing global warming." As a result, the user selects to donate 5,000 yen to "Environmental Protection Organization A," and the server processes the donation through the electronic payment system. If the donation is successful, a receipt is sent along with a notification of donation completion, which is displayed on the user's device. The user can confirm that their donation was made validly, and feel a sense of satisfaction.

[0823] Example 2

[0824] 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."

[0825] When users donate to nonprofit organizations, it is difficult to determine which organization is the most appropriate, and the donation process is often cumbersome, making the activity tedious. In particular, there is a concern that users' motivation to donate may decrease due to a lack of emotionally appealing explanations of the benefits and activities of donations. Therefore, there is a need for a system that can recommend appropriate nonprofit organizations based on users' emotions, simplify the donation process, and increase emotional satisfaction.

[0826] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0827] In this invention, the server includes a means for a user to input an area of ​​interest, a means for analyzing the user's emotions using an emotion recognition engine based on the area of ​​interest input by the user, and a means for recommending an appropriate business entity using a generative AI model based on the analyzed emotions and area of ​​interest. This makes it possible to recommend the most appropriate nonprofit organization according to the user's emotions, simplify the donation process, and increase the user's emotional satisfaction.

[0828] 1. "User" means an individual or organization that uses the System to make donations to a non-profit organization.

[0829] 2. "Area of ​​Interest" refers to a specific area or topic that a user is interested in.

[0830] 3. An "emotion recognition engine" is a technology that analyzes the user's input text and recognizes emotional trends.

[0831] 4. "Generative AI model" means an artificial intelligence model that recommends appropriate businesses based on a user's emotions and areas of interest.

[0832] 5. "Entity" means a nonprofit organization or other charitable organization.

[0833] 6. "Electronic Payment System" means an online payment system for conducting monetary transactions via the Internet.

[0834] 7. "Payment Interface" means a technical means for interfacing with an electronic payment system to process transactions.

[0835] 8. "Transaction processing result" means the processing result information returned from the electronic payment system.

[0836] 9. "Receipt" means a document issued to certify that a donation has been made successfully.

[0837] This invention is a system that combines an emotion recognition engine that recognizes user emotions with a generative AI model, allowing users to easily and effectively make donations to nonprofit organizations.

[0838] System Overview

[0839] The system consists of a user terminal, a server, an emotion recognition engine, a generative AI model, and an electronic payment system. The role and operation of each component are explained in detail below.

[0840] User Device

[0841] The user terminal is operated through a dedicated application or web page, where the user logs into their account and enters their area of ​​interest (e.g., "environmental protection").

[0842] Emotion Recognition Engine

[0843] The emotion recognition engine analyzes the user's emotions based on the areas of interest entered by the user. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the user's text. For example, if a user enters "I'm concerned about environmental issues," that emotion is analyzed and stored as data.

[0844] Generative AI Models

[0845] The server receives the user's interest data and the analysis results of the emotion recognition engine. Based on this data, it passes information to a generative AI model that recommends suitable nonprofit organizations. This generative AI model collects information from an internal database and external APIs and generates a list of nonprofit organizations that best fit the user's emotions and areas of interest.

[0846] Presentation of recommendation results

[0847] The server obtains the list of nonprofit organizations output by the generative AI model and collects detailed information from a database about each organization's activities and the impact of donations. This information is formatted to resonate with the user's emotions and sent to the user's device. The user's device receives the information sent from the server and displays the list of nonprofit organizations and their detailed information to the user. For example, it may display information such as "Environmental Protection Organization A" "carries out tree planting activities and plants 10 trees for a donation of 3,000 yen."

[0848] Select and enter your donation

[0849] Users select a donation destination from the recommended nonprofit organizations and enter the donation amount, which is then sent to a server and sent as transaction data to an electronic payment system.

[0850] Processing donations

[0851] The server interacts with the electronic payment system, processes the donation based on the transaction data sent, receives a response from the electronic payment system, and verifies whether the donation was successful.

[0852] Donation completion notification and receipt issuance

[0853] If the donation is successful, the server sends the user a notification of the completion of the donation, and if the donation amount is equal to or greater than a predetermined amount, it automatically generates and sends a receipt. The user's device receives this notification and receipt and displays them to the user.

[0854] Specific examples

[0855] For example, if a user inputs that they are interested in "environmental protection," the emotion recognition engine analyzes the user's input text and the generative AI model recommends appropriate nonprofit organizations. The explanation is emphasized according to the user's emotion. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system and, if successful, sends the user a receipt along with a notification of the completed donation. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[0856] Prompt Sentence Examples

[0857] "If I'm interested in protecting the environment, what nonprofits would you recommend?"

[0858] "Explain how to use an emotion recognition engine to analyze user emotions."

[0859] "What notification will be sent to users upon successful donation?"

[0860] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[0861] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0862] Step 1:

[0863] user

[0864] Users access a dedicated application or web page and log in to their account. They enter their user ID and password on the login screen, and once authentication is successful, the main screen is displayed.

[0865] Input: User ID, Password

[0866] Output: Authentication success message, main screen display

[0867] Step 2:

[0868] user

[0869] The user enters the area of ​​interest (e.g., "environmental protection") into the input field on the main screen, and then clicks the "Submit" button.

[0870] Input: Area of ​​interest (e.g., "environmental protection")

[0871] Output: Region of interest data transmission

[0872] Step 3:

[0873] Emotion Recognition Engine

[0874] The emotion recognition engine receives the area of ​​interest data sent by the user and analyzes the user's emotions using natural language processing technology. For example, it recognizes the emotion "worry" from the input "I'm worried about environmental issues."

[0875] Input: Region of interest data

[0876] Output: Sentiment analysis result (e.g. "worried")

[0877] Step 4:

[0878] server

[0879] The server receives and temporarily stores the analyzed emotion and interest data, and then passes this data to the generative AI model, which then instructs it to recommend suitable nonprofit organizations.

[0880] Input: Sentiment analysis results, area of ​​interest data

[0881] Output: Data provision instructions

[0882] Step 5:

[0883] Generative AI Models

[0884] The generative AI model uses data provided by the server, collects information from internal databases and external APIs, and generates a list of the most suitable nonprofit organizations.

[0885] Input: Sentiment analysis results, area of ​​interest data

[0886] Output: List of recommended nonprofits

[0887] Step 6:

[0888] server

[0889] The server receives the list of recommended nonprofit organizations obtained from the generative AI model, collects detailed information about each organization's activities and the impact of donations from a database, formats this information to resonate with the user's emotions, and sends it to the user's device.

[0890] Input: List of recommended nonprofit organizations

[0891] Output: Formatted organization information

[0892] Step 7:

[0893] User Device

[0894] The user device receives the list of nonprofit organizations and their details from the server and displays them to the user. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[0895] Input: Formatted organization information

[0896] Output: Group information display

[0897] Step 8:

[0898] user

[0899] Users can select a donation recipient from a list of nonprofit organizations, enter the amount they would like to donate, and then click the "Donate" button to send the selected organization and donation amount to the server.

[0900] Input: Donation destination selection, donation amount

[0901] Output: Send donation information

[0902] Step 9:

[0903] server

[0904] The server receives the donation recipient and donation amount data sent by the user and sends it to the electronic payment system as transaction data. The electronic payment system processes the donation based on this transaction data.

[0905] Input: Donation recipient, donation amount

[0906] Output: Transaction data sent

[0907] Step 10:

[0908] Electronic Payment Systems

[0909] The electronic payment system processes the donation and returns the result to the server, which receives the result and verifies whether the donation was successful.

[0910] Input: Transaction data

[0911] Output: Donation processing result

[0912] Step 11:

[0913] server

[0914] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[0915] Input: Donation processing result

[0916] Output: Donation completion notification, receipt

[0917] Step 12:

[0918] User Device

[0919] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0920] Input: Donation completion notification, receipt

[0921] Output: Notification display, receipt display

[0922] (Application example 2)

[0923] 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."

[0924] When promoting donations to nonprofit organizations, it is necessary not only to recommend appropriate organizations based on the user's areas of interest, but also to suggest donations that are tailored to the user's emotions. Furthermore, to increase the user's satisfaction after donating, it is necessary to explain the effects of donations and the activities involved in them in an emotional way. Furthermore, it is necessary to link seamlessly with an electronic payment system to simplify the donation process. The lack of an integrated system that satisfies these multiple requirements is a challenge.

[0925] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0926] In this invention, the server includes: means for allowing a user to input areas of interest; emotion recognition means for analyzing the user's input areas of interest and emotions; means for recommending appropriate nonprofit organizations using a generative AI model based on emotion data obtained from the emotion recognition means; means for explaining the activities of the recommended nonprofit organizations and the effects of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for processing the donation in cooperation with an electronic payment system based on the input donation amount; and means for sending the user a donation completion notification when the donation is successful and a receipt if the donation amount is above a predetermined amount. This makes it possible to recommend appropriate nonprofit organizations for donations based on the user's emotions and areas of interest, making the donation process simple and effective.

[0927] A "means for user input of areas of interest" is a device or software that provides an interface for users to input their areas of interest through text or options.

[0928] "Emotion recognition means for analyzing emotions" is software that has the function of analyzing emotions from text entered by a user using natural language processing technology and recognizing the emotional state as a number or category.

[0929] "Means for recommending appropriate nonprofit organizations using a generative AI model" refers to algorithms and software that utilize a generative AI model to extract appropriate nonprofit organizations and generate a recommendation list based on a user's areas of interest and emotional data.

[0930] The "means for explaining the activities of the recommended nonprofit organization and the impact of donations" is software that has the function of generating text and diagrams that clearly explain to users the activities of the recommended nonprofit organization and how donations will be used.

[0931] A "means for providing an explanation to a user" is a device or software that displays visual and textual information to a user about the recommended nonprofit organization and the impact of the donation.

[0932] A "means for a user to input a donation amount to a nonprofit organization selected by the user" is a device or software that provides an interface for a user to input a donation destination and donation amount.

[0933] The "means for processing donations in cooperation with the electronic payment system based on the entered donation amount" refers to the algorithm and software for transmitting the donation amount entered by the user to the electronic payment system, processing the payment, and receiving the transaction results.

[0934] "Means for notifying the user that a donation has been successfully completed and sending a receipt if the donation amount is equal to or greater than a specified amount" refers to software that has the functionality to notify the user that a donation has been successfully completed and to automatically generate and send a receipt if necessary.

[0935] This invention is a system for analyzing a user's areas of interest and emotions, recommending appropriate non-profit organizations, and making donations seamlessly. Specific embodiments of this system will be described below.

[0936] 1. User interest and emotion recognition

[0937] User Device

[0938] First, users access a dedicated application or website and log in to their account. After logging in, they enter their areas of interest (e.g., "environmental protection") in the input field. They can also enter comments and opinions, which are then used for emotion recognition. Sentiment analysis is performed using the Google Cloud Natural Language API.

[0939] 2. Generative AI model recommends suitable nonprofit organizations

[0940] server

[0941] The server receives interest and sentiment data submitted by the user. This data is passed to a generative AI model, such as OpenAI's GPT-3, which then recommends the most suitable nonprofit organization based on the sentiment data. An example of an input prompt for the generative AI model is as follows:

[0942] Prompt Sentence Examples

[0943] The user's area of ​​interest is environmental protection. The sentiment score is 0.8. Generate a list of recommended nonprofit organizations.

[0944] 3. Explanation of the recommendation results and the impact of the donation

[0945] server

[0946] The server retrieves the list of nonprofit organizations output by the generative AI model from the database, obtains detailed information about each organization's activities and the impact of donations, and formats it to resonate with the user's emotions.

[0947] User Device

[0948] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[0949] 4. User Donation Choices

[0950] User Device

[0951] The user selects a nonprofit organization from the list of recommended organizations, enters a value in the donation amount field, and clicks the donate button, which sends the selected organization and donation amount to the server.

[0952] 5. Donation processing through integration with electronic payment systems

[0953] server

[0954] The server receives the donation recipient and donation amount data submitted by the user, uses this information to process the donation through an electronic payment system such as Stripe, and receives a response from the electronic payment system to confirm whether the donation was successful.

[0955] 6. Notification of donation completion and receipt issuance

[0956] server

[0957] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[0958] User Device

[0959] The user's device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[0960] This system allows users to donate to nonprofit organizations easily and effectively while increasing emotional satisfaction.

[0961] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0962] Step 1:

[0963] Users access a dedicated application or website and log in to their account. At this time, a login screen appears on the user's device and the user enters their username and password. The entered login information is sent to the server for authentication. If authentication is successful, the user's dashboard is displayed.

[0964] Step 2:

[0965] The user enters the areas of interest in the input field. They can also optionally enter comments or opinions. This information is sent from the user's device to the server. A specific example of input is text such as "I'm interested in environmental protection." The server receives this information and analyzes it using emotion recognition means. The user's text is given as input, and an emotion score (e.g., 0.8) is obtained as output.

[0966] Step 3:

[0967] The server uses the Google Cloud Natural Language API to analyze the sentiment from the text entered by the user. This API analyzes the input text data and outputs a sentiment score and sentiment category (positive, negative, neutral). Based on this output, the user's sentiment data is stored on the server.

[0968] Step 4:

[0969] The server passes the emotion data and the user's areas of interest to a generative AI model. This generative AI model (for example, OpenAI GPT-3) generates a prompt based on the input data and outputs a list of the most suitable nonprofit organizations. An example of a specific prompt is as follows: "The user's area of ​​interest is environmental protection. The emotion score is 0.8. Please generate a list of recommended nonprofit organizations." This prompt is input into the AI ​​model, and a list of nonprofit organizations (for example, environmental protection organization A and environmental protection organization B) is obtained as output.

[0970] Step 5:

[0971] Based on the generated list of nonprofit organizations, the server retrieves detailed information about each organization's activities and the impact of donations from the database. This allows the server to collect information such as the specific activities of the nonprofit organization and the purpose of the donation (e.g., a donation of 3,000 yen will plant 10 trees for tree planting activities). The server formats this information to resonate with the user's emotions and sends it to the user's device.

[0972] Step 6:

[0973] The user's device displays the list of nonprofit organizations and their detailed information sent from the server. The user can review the options for multiple nonprofit organizations on the screen and decide on a specific donation recipient and donation amount (e.g., a donation of 5,000 yen to environmental protection organization A). Once the user makes a selection, the information is sent back to the server.

[0974] Step 7:

[0975] The server receives the data of the nonprofit organization and donation amount selected by the user, and processes the donation by connecting with an electronic payment system such as Stripe. This process involves sending the donation amount using a payment API, and the transaction result is returned. If successful, the donation procedure is completed.

[0976] Step 8:

[0977] If the donation is successful, the server sends the user a notification that the donation has been completed, and if the donation amount is above a certain amount, it automatically generates and sends a receipt. For example, if the donation amount is above 1,000 yen, a receipt will be sent by email. The user's device receives the notification and receipt and displays them to the user. The user can check this display and save the receipt if necessary.

[0978] 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.

[0979] 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.

[0980] 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.

[0981] [Third embodiment]

[0982] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0983] 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.

[0984] 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).

[0985] 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.

[0986] 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.

[0987] 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).

[0988] 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.

[0989] 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.

[0990] 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.

[0991] 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.

[0992] 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.

[0993] 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."

[0994] The present invention relates to a system that allows users to easily and effectively make donations to non-profit organizations. A specific embodiment of this system will be described below.

[0995] 1. Enter your user interests

[0996] User Device

[0997] A user accesses a dedicated application or web page and logs in. After logging in, the user enters values ​​into input fields to indicate the areas of interest (e.g., "environmental protection"), and when the user presses the submit button, this input data is sent to the server.

[0998] 2. Generative AI model recommends suitable nonprofit organizations

[0999] server

[1000] The server receives user-submitted interest data, passes this data to a generative AI model, which then recommends suitable nonprofits based on the user's interests. The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's input.

[1001] 3. Explanation of the recommendation results and the impact of the donation

[1002] server

[1003] The server receives the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from a database, and formats this information into a format that can be presented to users.

[1004] User Device

[1005] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, it may display information such as "Environmental Protection Organization A" is "carrying out tree planting activities and planting 10 trees for a donation of 3,000 yen."

[1006] 4. User Donation Choices

[1007] User Device

[1008] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[1009] 5. Donation processing through integration with electronic payment systems

[1010] server

[1011] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., PayPay) to process the donation, and receives a response from the electronic payment system confirming whether the donation was successful.

[1012] 6. Notification of donation completion and receipt issuance

[1013] server

[1014] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1015] User Device

[1016] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1017] Specific examples

[1018] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is engaged in tree planting activities, and that a donation of 3,000 yen will plant 10 trees. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, allowing the user to confirm that the donation was made validly.

[1019] This system allows users to easily and effectively donate to non-profit organizations, giving them a sense of social contribution.

[1020] The processing flow will be explained below.

[1021] Step 1:

[1022] User Device

[1023] The user accesses a dedicated application or web page and logs in to their account.

[1024] Step 2:

[1025] User Device

[1026] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[1027] Step 3:

[1028] server

[1029] The server receives the area of ​​interest data sent by the user.

[1030] Step 4:

[1031] server

[1032] The server passes the received data to a generative AI model, which then uses an internal database or external API to generate a list of relevant nonprofits.

[1033] Step 5:

[1034] server

[1035] The generative AI model obtains a list of recommended nonprofit organizations, and then retrieves information about each organization's activities and the effectiveness of donations from a database.

[1036] Step 6:

[1037] server

[1038] Format and deliver information about nonprofits and the impact of donations to users.

[1039] Step 7:

[1040] server

[1041] The formatted information is sent to the user's device.

[1042] Step 8:

[1043] User Device

[1044] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[1045] Step 9:

[1046] User Device

[1047] The user selects a donation destination from the recommended nonprofit organizations, enters the donation amount in the input field, and presses the donate button.

[1048] Step 10:

[1049] server

[1050] The server receives the selected nonprofit organization and donation amount submitted by the user.

[1051] Step 11:

[1052] server

[1053] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[1054] Step 12:

[1055] Electronic payment system

[1056] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[1057] Step 13:

[1058] server

[1059] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[1060] Step 14:

[1061] server

[1062] If the donation is successful, a notification will be sent to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1063] Step 15:

[1064] User Device

[1065] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user confirms that the donation was successful and saves the receipt.

[1066] As a specific example, when a user enters "environmental protection," the generative AI model returns a list of recommendations including "environmental protection organization A" and "environmental protection organization B." If the user then selects to donate 5,000 yen to "environmental protection organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification of the completed donation.

[1067] Example 1

[1068] 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."

[1069] In modern society, users face challenges when making donations to nonprofit organizations, as it requires a lot of time and effort and information gathering. It is also difficult for users to find nonprofit organizations that fit their areas of interest. Furthermore, the donation process faces challenges due to the lack of smooth integration with electronic payment systems.

[1070] 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.

[1071] In this invention, the server includes a means for a user to input areas of interest, a means for recommending appropriate organizations using a generative AI model based on the areas of interest input by the user, and a means for explaining the activities of the recommended organizations and the effects of donations, allowing users to easily find nonprofit organizations that fit their areas of interest and making the donation process smoother.

[1072] "User" means an individual or organization that uses the System to make donations to a nonprofit organization.

[1073] "Areas of Interest" are specific categories or topics that users consider important, such as environmental protection, educational support, or medical assistance.

[1074] A "generative AI model" is a type of artificial intelligence technology that recommends suitable nonprofit organizations based on a user's areas of interest. It collects information from internal databases and external APIs to present the best candidates.

[1075] A "non-profit organization" is an organization that does not aim to make a profit but works to solve social problems or for the public good.

[1076] "Activities" refers to the specific projects and initiatives undertaken by the nonprofit organization, such as tree planting activities or educational programs.

[1077] "Effectiveness of Donations" provides detailed information about how users' donated funds are utilized and the results they produce.

[1078] An "electronic payment system" is a system for processing payments online, such as payments using electronic wallets or credit cards.

[1079] "Receipt" means the official payment confirmation issued to a User upon successful Donation.

[1080] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations.

[1081] 1. Enter your user interests

[1082] The user accesses a dedicated application or web page and logs in. After logging in, the user enters information in the field for entering their areas of interest. For example, if the user is interested in "environmental protection," they enter this information and press the "Submit" button. This data is sent from the user's device to the server.

[1083] 2. Generative AI model recommends suitable nonprofit organizations

[1084] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and the model recommends suitable nonprofit organizations based on the user's areas of interest. The generative AI model collects information from an internal database and external APIs and generates a list of the most suitable nonprofit organizations based on the user's input data.

[1085] 3. Explanation of the recommendation results and the impact of the donation

[1086] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from the database. This information is formatted and sent to the user's device. The user then checks the information displayed on the device. For example, "Environmental Protection Organization A" is described as "carrying out tree planting activities, and a donation of 3,000 yen will enable the planting of 10 trees."

[1087] 4. User Donation Choices

[1088] The user selects a nonprofit organization from the list, enters the donation amount in the input field, and then presses the "Donate" button. This action sends the data of the selected nonprofit organization and donation amount from the user's device to the server.

[1089] 5. Donation processing through integration with electronic payment systems

[1090] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1091] 6. Notification of donation completion and receipt issuance

[1092] If the donation is successful, the server will send a notification to the user that the donation has been completed. If the donation amount is above a certain amount (for example, 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt from the server and display them to the user. This will allow the user to confirm that the donation was processed successfully and save the receipt if necessary.

[1093] Examples of specific examples and prompts

[1094] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is working to plant 10 trees for a donation of 3,000 yen. If the user selects "Donate 5,000 yen to Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, and the user will be able to confirm that the donation was made validly.

[1095] Example prompt sentence:

[1096] "I'm interested in protecting the environment. What nonprofits can you recommend?"

[1097] "I would like to donate to educational support. Can you recommend any organizations?"

[1098] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1099] Step 1:

[1100] User interest input

[1101] The user accesses a dedicated application or web page and logs in. The user enters their area of ​​interest (e.g., "environmental protection") in the input field and presses the submit button. The entered data is sent from the user's device to the server.

[1102] Input: User enters text of interest (e.g., "environmental protection")

[1103] Output: The submitted interest data is stored on the server.

[1104] Step 2:

[1105] Generative AI models recommend suitable nonprofits

[1106] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and has it recommend suitable nonprofit organizations. The generative AI model collects information from an internal database and external APIs to generate a list of the most suitable nonprofit organizations.

[1107] Input: User interest data

[1108] Output: A list of nonprofits according to their area of ​​interest

[1109] Specific behavior:

[1110] 1. The server queries the database to retrieve data related to the area of ​​interest.

[1111] 2. Input the acquired data into the generative AI model and receive recommendation results.

[1112] Step 3:

[1113] Explanation of recommendation results and donation effects

[1114] The server receives the list of nonprofit organizations output by the generative AI model, retrieves information about each organization's activities and the impact of donations from the database, formats this information, and sends it to the user's device. The user can then view the displayed list of nonprofit organizations and their detailed information.

[1115] Input: A list of nonprofits from a generative AI model

[1116] Output: A formatted list of nonprofits with details

[1117] Specific behavior:

[1118] 1. The server queries the database to retrieve details about each nonprofit organization.

[1119] 2. Format the acquired information and send it to the user's device.

[1120] Step 4:

[1121] User donation choices

[1122] The user selects a nonprofit organization from the list, enters the donation amount, and then presses the "Donate" button, which sends the selected nonprofit organization and donation amount data to the server.

[1123] Input: User-selected nonprofit and donation amount

[1124] Output: Nonprofit organization and donation amount data sent to the server

[1125] Step 5:

[1126] Donation processing through integration with electronic payment systems

[1127] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1128] Input: User-selected nonprofit organization and donation amount data

[1129] Output: Transaction processing results from the electronic payment system

[1130] Specific behavior:

[1131] 1. The server sends the donation amount and nonprofit organization to the payment API.

[1132] 2. Wait for a response from the electronic payment system and receive the processing result.

[1133] Step 6:

[1134] Donation completion notification and receipt issuance

[1135] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount (e.g., 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt and display them to the user.

[1136] Input: Transaction processing results from electronic payment system

[1137] Output: Donation completion notification and receipt (if applicable) to the user

[1138] Specific behavior:

[1139] 1. The server generates a donation completion notification and sends it to the user's device.

[1140] 2. For donations of 1,000 yen or more, the server automatically generates a receipt and sends it to the user.

[1141] (Application example 1)

[1142] 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."

[1143] In modern society, donations to nonprofit organizations are becoming increasingly important as a form of social contribution. However, the process of finding a nonprofit organization that matches a user's area of ​​interest and making a donation is complicated. Furthermore, if there is a lack of information about the effects of donations and the specific activities they carry out, it is difficult to attract users' attention. Furthermore, there is a need for a method to simplify the donation process by linking it with an electronic payment system. The purpose of this invention is to solve these problems and provide a system that allows users to donate to nonprofit organizations easily and effectively.

[1144] 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.

[1145] In this invention, the server includes: means for allowing a user to input their areas of interest; means for using a generative AI model to recommend appropriate nonprofit organizations based on the user's areas of interest; means for explaining the activities of the recommended nonprofit organizations and the benefits of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for linking with an electronic payment system to process the donation based on the input donation amount; means for sending the user a donation completion notification if the donation is successful and a receipt if the donation amount is above a predetermined amount; and means for integrating the entire process from inputting the user's areas of interest to notifying the electronic payment system of the completion of donation processing within a smartphone application. This allows users to easily find nonprofit organizations based on their areas of interest, understand the benefits of donations, and make donations easily.

[1146] "User" refers to an individual who uses an Electronic Device to make a donation to a nonprofit organization.

[1147] "Interest areas" refer to specific topics or issue areas that interest a user.

[1148] "Generative AI model" refers to a machine learning model that recommends suitable nonprofit organizations based on input data.

[1149] A "nonprofit organization" is a non-profit organization that pursues a specific social purpose.

[1150] "Smartphone Application" means a software application that runs on a smartphone.

[1151] "Electronic payment system" means an information technology system used to complete monetary transactions digitally.

[1152] "Donation Processing" refers to the series of steps taken to complete the transfer of money from a user to a nonprofit organization.

[1153] "Donation Completion Notification" refers to a message sent to a User to inform them that their donation has been successfully processed.

[1154] "Receipt" refers to any written or electronic evidence that proves a donation was made.

[1155] "Flow" refers to a series of operations or steps performed to achieve a specific goal.

[1156] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations. Specific embodiments of the present invention will now be described.

[1157] 1. Enter your user interests

[1158] Users input their areas of interest (e.g., "environmental protection") on the smartphone application. This input interface is provided through a dedicated input field. When the user inputs their area of ​​interest and presses the submit button, this data is sent to a server via the Internet.

[1159] 2. Generative AI model recommends suitable nonprofit organizations

[1160] The server receives the user's submitted interest data and passes it to a generative AI model, which then references an internal database and external APIs to generate a list of suitable nonprofits based on the user's input.

[1161] 3. Explanation of the recommendation results and the impact of the donation

[1162] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations. This information is formatted in a user-friendly format and provided to users through a smartphone application.

[1163] 4. User Donation Choices

[1164] The user selects a donation recipient from a list of nonprofit organizations and enters the amount of the donation. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. The user's selection and the entered donation amount are sent to the server.

[1165] 5. Donation processing through integration with electronic payment systems

[1166] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., a payment API) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1167] 6. Notification of donation completion and receipt issuance

[1168] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, a receipt will be automatically generated and sent to the user. The user can then view the notification and receipt on their smartphone application.

[1169] As a specific example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." Detailed descriptions of each organization are provided to the user, and if the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation via an electronic payment system and, if successful, sends the user a notification of donation completion and a receipt.

[1170] Example prompts to input to a generative AI model:

[1171] The user has entered the following area of ​​interest: Environmental protection. Please recommend suitable nonprofit organizations based on the following criteria:

[1172] conditions:

[1173] An organization that engages in environmental protection activities.

[1174] The specific activities and the effects of the donation must be clearly stated.

[1175] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1176] Step 1:

[1177] Users enter their areas of interest into the smartphone application, and the entered data is sent to a server via the Internet.

[1178] Input: Area of ​​interest (e.g. "Environmental protection")

[1179] Output: User interest data sent to the server

[1180] Step 2:

[1181] The server receives the user's submitted interest data, passes it to the generative AI model, and begins the process of recommending suitable nonprofit organizations.

[1182] Input: User interest data

[1183] Output: Data to be passed to the generative AI model

[1184] Step 3:

[1185] The generative AI model uses the interest data passed from the server to reference an internal database and external APIs to generate a list of suitable nonprofit organizations.

[1186] Input: Area of ​​interest data

[1187] Data Processing: Searching for nonprofit information from internal databases and external APIs

[1188] Output: A list of recommended nonprofits

[1189] Step 4:

[1190] Based on the list of nonprofit organizations received from the generative AI model, the server retrieves detailed information about each organization's activities and the impact of donations from its internal database and formats it into a form that can be provided to users.

[1191] Input: List of nominated nonprofits

[1192] Data processing: Acquisition and formatting of activity details and donation effect information from the internal database

[1193] Output: A list of nonprofits with formatted details.

[1194] Step 5:

[1195] The server then sends the formatted list of nonprofit organizations to the smartphone application and displays it to the user, who then decides which organization to donate to and how much to donate.

[1196] Input: A formatted list of nonprofits

[1197] Output: Information displayed on the smartphone application

[1198] Step 6:

[1199] The user selects the donation recipient and donation amount on the smartphone application and sends the entered data to the server.

[1200] Input: User's chosen donation destination and donation amount

[1201] Output: Donation recipient and donation amount data sent to the server

[1202] Step 7:

[1203] The server receives donation recipient and donation amount data from the user, sends the transaction to the electronic payment system, and processes the donation.

[1204] Input: Donation recipient and donation amount data

[1205] Output: Transaction data sent to electronic payment systems

[1206] Step 8:

[1207] The electronic payment system processes the transaction and sends the results back to the server, which receives the results and verifies whether the donation was successful.

[1208] Input: Transaction result data from electronic payment systems

[1209] Output: Confirmation of successful donation

[1210] Step 9:

[1211] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, the server will automatically generate a receipt and send it to the user.

[1212] Input: Donation success confirmation data

[1213] Output: Sending a donation completion notification and receipt

[1214] Step 10:

[1215] Users can check the donation completion notification and receipt on their smartphone application to confirm that their donation was successful.

[1216] Input: Donation completion notice and receipt

[1217] Output: Display on smartphone application

[1218] 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.

[1219] This invention is a system that combines an emotion engine that recognizes the user's emotions, allowing users to easily and effectively donate to non-profit organizations. Specific embodiments of this system will be described below.

[1220] 1. User interest and emotion recognition

[1221] User Device

[1222] The user accesses a dedicated application or web page and logs in to their account. After logging in, the user enters a value in an input field to indicate their area of ​​interest (e.g., "environmental protection").

[1223] Emotion Engine

[1224] Based on the user's inputted areas of interest, the emotion engine analyzes the user's emotions. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the text entered by the user.

[1225] 2. Generative AI model recommends suitable nonprofit organizations

[1226] server

[1227] The server receives the user's interest data and the results of the emotion engine analysis, and then passes the information to the generative AI model, instructing it to recommend suitable nonprofit organizations based on this data.

[1228] The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's sentiment and areas of interest. The results of the analysis by the sentiment engine provide optimal recommendations based on the user's sentiment.

[1229] 3. Explanation of the recommendation results and the impact of the donation

[1230] server

[1231] The server takes the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from the database, and formats this information to be presented to the user in a way that resonates with their emotions.

[1232] User Device

[1233] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. At this time, explanations and effects that correspond to the user's emotions are emphasized.

[1234] 4. User Donation Choices

[1235] User Device

[1236] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[1237] 5. Donation processing through integration with electronic payment systems

[1238] server

[1239] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to submit a transaction to the electronic payment system to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1240] 6. Notification of donation completion and receipt issuance

[1241] server

[1242] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1243] User Device

[1244] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1245] Specific examples

[1246] For example, if a user inputs that they are interested in "environmental protection," the emotion engine analyzes the user's input text. The generative AI model returns a list of recommendations: "Environmental Protection Organization A" and "Environmental Protection Organization B." Depending on the user's emotions, explanations that resonate with the user's emotions are emphasized when explaining the activities of each nonprofit organization and the effects of donations. If the user then selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[1247] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[1248] The processing flow will be explained below.

[1249] Step 1:

[1250] User Device

[1251] The user accesses a dedicated application or web page and logs in to their account.

[1252] Step 2:

[1253] User Device

[1254] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[1255] Step 3:

[1256] server

[1257] The server receives the area of ​​interest data sent by the user.

[1258] Step 4:

[1259] Emotion Engine

[1260] The emotion engine analyzes the user's input data and recognizes the user's emotion, which is then used throughout the system.

[1261] Step 5:

[1262] server

[1263] The server passes the user's interest data and the results of the sentiment engine analysis to the generative AI model, instructing it to recommend appropriate nonprofit organizations.

[1264] Step 6:

[1265] Generative AI Models

[1266] A generative AI model searches a database for relevant nonprofit listings based on the user's areas of interest and sentiment, generating the best recommendation list.

[1267] Step 7:

[1268] server

[1269] The server receives the list of nonprofit organizations returned by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from a database.

[1270] Step 8:

[1271] server

[1272] The acquired information is formatted, emphasis is added based on the user's emotions, and it is then converted into a form that can be presented to the user.

[1273] Step 9:

[1274] server

[1275] The formatted information is sent to the user's device.

[1276] Step 10:

[1277] User Device

[1278] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[1279] Step 11:

[1280] User Device

[1281] The user selects a donation destination from the recommended nonprofit organizations, enters a value in the donation amount field, and clicks the donate button.

[1282] Step 12:

[1283] server

[1284] The server receives the selected nonprofit organization and donation amount data submitted by the user.

[1285] Step 13:

[1286] server

[1287] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[1288] Step 14:

[1289] Electronic payment system

[1290] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[1291] Step 15:

[1292] server

[1293] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[1294] Step 16:

[1295] server

[1296] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1297] Step 17:

[1298] User Device

[1299] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user can confirm that the donation was successful and save the receipt if necessary.

[1300] As a concrete example, suppose a user indicates an interest in "environmental protection," and the emotion engine recognizes a "positive" emotion. The generative AI model recommends "Environmental Protection Organization A" and "Environmental Protection Organization B," explaining to the user that "Environmental Protection Organization A is engaged in tree planting activities, and a donation of 3,000 yen will allow 10 trees to be planted," while emphasizing the emotional element that "their activities will significantly contribute to preventing global warming." As a result, the user selects to donate 5,000 yen to "Environmental Protection Organization A," and the server processes the donation through the electronic payment system. If the donation is successful, a receipt is sent along with a notification of donation completion, which is displayed on the user's device. The user can confirm that their donation was made validly, and feel a sense of satisfaction.

[1301] Example 2

[1302] 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."

[1303] When users donate to nonprofit organizations, it is difficult to determine which organization is the most appropriate, and the donation process is often cumbersome, making the activity tedious. In particular, there is a concern that users' motivation to donate may decrease due to a lack of emotionally appealing explanations of the benefits and activities of donations. Therefore, there is a need for a system that can recommend appropriate nonprofit organizations based on users' emotions, simplify the donation process, and increase emotional satisfaction.

[1304] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1305] In this invention, the server includes a means for a user to input an area of ​​interest, a means for analyzing the user's emotions using an emotion recognition engine based on the area of ​​interest input by the user, and a means for recommending an appropriate business entity using a generative AI model based on the analyzed emotions and area of ​​interest. This makes it possible to recommend the most appropriate nonprofit organization according to the user's emotions, simplify the donation process, and increase the user's emotional satisfaction.

[1306] 1. "User" means an individual or organization that uses the System to make donations to a non-profit organization.

[1307] 2. "Area of ​​Interest" refers to a specific area or topic that a user is interested in.

[1308] 3. An "emotion recognition engine" is a technology that analyzes the user's input text and recognizes emotional trends.

[1309] 4. "Generative AI model" means an artificial intelligence model that recommends appropriate businesses based on a user's emotions and areas of interest.

[1310] 5. "Entity" means a nonprofit organization or other charitable organization.

[1311] 6. "Electronic Payment System" means an online payment system for conducting monetary transactions via the Internet.

[1312] 7. "Payment Interface" means a technical means for interfacing with an electronic payment system to process transactions.

[1313] 8. "Transaction processing result" means the processing result information returned from the electronic payment system.

[1314] 9. "Receipt" means a document issued to certify that a donation has been made successfully.

[1315] This invention is a system that combines an emotion recognition engine that recognizes user emotions with a generative AI model, allowing users to easily and effectively make donations to nonprofit organizations.

[1316] System Overview

[1317] The system consists of a user terminal, a server, an emotion recognition engine, a generative AI model, and an electronic payment system. The role and operation of each component are explained in detail below.

[1318] User Device

[1319] The user terminal is operated through a dedicated application or web page, where the user logs into their account and enters their area of ​​interest (e.g., "environmental protection").

[1320] Emotion Recognition Engine

[1321] The emotion recognition engine analyzes the user's emotions based on the areas of interest entered by the user. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the user's text. For example, if a user enters "I'm concerned about environmental issues," that emotion is analyzed and stored as data.

[1322] Generative AI Models

[1323] The server receives the user's interest data and the analysis results of the emotion recognition engine. Based on this data, it passes information to a generative AI model that recommends suitable nonprofit organizations. This generative AI model collects information from an internal database and external APIs and generates a list of nonprofit organizations that best fit the user's emotions and areas of interest.

[1324] Presentation of recommendation results

[1325] The server obtains the list of nonprofit organizations output by the generative AI model and collects detailed information from a database about each organization's activities and the impact of donations. This information is formatted to resonate with the user's emotions and sent to the user's device. The user's device receives the information sent from the server and displays the list of nonprofit organizations and their detailed information to the user. For example, it may display information such as "Environmental Protection Organization A" "carries out tree planting activities and plants 10 trees for a donation of 3,000 yen."

[1326] Select and enter your donation

[1327] Users select a donation destination from the recommended nonprofit organizations and enter the donation amount, which is then sent to a server and sent as transaction data to an electronic payment system.

[1328] Processing donations

[1329] The server interacts with the electronic payment system, processes the donation based on the transaction data sent, receives a response from the electronic payment system, and verifies whether the donation was successful.

[1330] Donation completion notification and receipt issuance

[1331] If the donation is successful, the server sends the user a notification of the completion of the donation, and if the donation amount is equal to or greater than a predetermined amount, it automatically generates and sends a receipt. The user's device receives this notification and receipt and displays them to the user.

[1332] Specific examples

[1333] For example, if a user inputs that they are interested in "environmental protection," the emotion recognition engine analyzes the user's input text and the generative AI model recommends appropriate nonprofit organizations. The explanation is emphasized according to the user's emotion. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system and, if successful, sends the user a receipt along with a notification of the completed donation. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[1334] Prompt Sentence Examples

[1335] "If I'm interested in protecting the environment, what nonprofits would you recommend?"

[1336] "Explain how to use an emotion recognition engine to analyze user emotions."

[1337] "What notification will be sent to users upon successful donation?"

[1338] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[1339] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1340] Step 1:

[1341] user

[1342] Users access a dedicated application or web page and log in to their account. They enter their user ID and password on the login screen, and once authentication is successful, the main screen is displayed.

[1343] Input: User ID, Password

[1344] Output: Authentication success message, main screen display

[1345] Step 2:

[1346] user

[1347] The user enters the area of ​​interest (e.g., "environmental protection") into the input field on the main screen, and then clicks the "Submit" button.

[1348] Input: Area of ​​interest (e.g., "environmental protection")

[1349] Output: Region of interest data transmission

[1350] Step 3:

[1351] Emotion Recognition Engine

[1352] The emotion recognition engine receives the area of ​​interest data sent by the user and analyzes the user's emotions using natural language processing technology. For example, it recognizes the emotion "worry" from the input "I'm worried about environmental issues."

[1353] Input: Region of interest data

[1354] Output: Sentiment analysis result (e.g. "worried")

[1355] Step 4:

[1356] server

[1357] The server receives and temporarily stores the analyzed emotion and interest data, and then passes this data to the generative AI model, which then instructs it to recommend suitable nonprofit organizations.

[1358] Input: Sentiment analysis results, area of ​​interest data

[1359] Output: Data provision instructions

[1360] Step 5:

[1361] Generative AI Models

[1362] The generative AI model uses data provided by the server, collects information from internal databases and external APIs, and generates a list of the most suitable nonprofit organizations.

[1363] Input: Sentiment analysis results, area of ​​interest data

[1364] Output: List of recommended nonprofits

[1365] Step 6:

[1366] server

[1367] The server receives the list of recommended nonprofit organizations obtained from the generative AI model, collects detailed information about each organization's activities and the impact of donations from a database, formats this information to resonate with the user's emotions, and sends it to the user's device.

[1368] Input: List of recommended nonprofit organizations

[1369] Output: Formatted organization information

[1370] Step 7:

[1371] User Device

[1372] The user device receives the list of nonprofit organizations and their details from the server and displays them to the user. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[1373] Input: Formatted organization information

[1374] Output: Group information display

[1375] Step 8:

[1376] user

[1377] Users can select a donation recipient from a list of nonprofit organizations, enter the amount they would like to donate, and then click the "Donate" button to send the selected organization and donation amount to the server.

[1378] Input: Donation destination selection, donation amount

[1379] Output: Send donation information

[1380] Step 9:

[1381] server

[1382] The server receives the donation recipient and donation amount data sent by the user and sends it to the electronic payment system as transaction data. The electronic payment system processes the donation based on this transaction data.

[1383] Input: Donation recipient, donation amount

[1384] Output: Transaction data sent

[1385] Step 10:

[1386] Electronic Payment Systems

[1387] The electronic payment system processes the donation and returns the result to the server, which receives the result and verifies whether the donation was successful.

[1388] Input: Transaction data

[1389] Output: Donation processing result

[1390] Step 11:

[1391] server

[1392] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[1393] Input: Donation processing result

[1394] Output: Donation completion notification, receipt

[1395] Step 12:

[1396] User Device

[1397] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1398] Input: Donation completion notification, receipt

[1399] Output: Notification display, receipt display

[1400] (Application example 2)

[1401] 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."

[1402] When promoting donations to nonprofit organizations, it is necessary not only to recommend appropriate organizations based on the user's areas of interest, but also to suggest donations that are tailored to the user's emotions. Furthermore, to increase the user's satisfaction after donating, it is necessary to explain the effects of donations and the activities involved in them in an emotional way. Furthermore, it is necessary to link seamlessly with an electronic payment system to simplify the donation process. The lack of an integrated system that satisfies these multiple requirements is a challenge.

[1403] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1404] In this invention, the server includes: means for allowing a user to input areas of interest; emotion recognition means for analyzing the user's input areas of interest and emotions; means for recommending appropriate nonprofit organizations using a generative AI model based on emotion data obtained from the emotion recognition means; means for explaining the activities of the recommended nonprofit organizations and the effects of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for processing the donation in cooperation with an electronic payment system based on the input donation amount; and means for sending the user a donation completion notification when the donation is successful and a receipt if the donation amount is above a predetermined amount. This makes it possible to recommend appropriate nonprofit organizations for donations based on the user's emotions and areas of interest, making the donation process simple and effective.

[1405] A "means for user input of areas of interest" is a device or software that provides an interface for users to input their areas of interest through text or options.

[1406] "Emotion recognition means for analyzing emotions" is software that has the function of analyzing emotions from text entered by a user using natural language processing technology and recognizing the emotional state as a number or category.

[1407] "Means for recommending appropriate nonprofit organizations using a generative AI model" refers to algorithms and software that utilize a generative AI model to extract appropriate nonprofit organizations and generate a recommendation list based on a user's areas of interest and emotional data.

[1408] The "means for explaining the activities of the recommended nonprofit organization and the impact of donations" is software that has the function of generating text and diagrams that clearly explain to users the activities of the recommended nonprofit organization and how donations will be used.

[1409] A "means for providing an explanation to a user" is a device or software that displays visual and textual information to a user about the recommended nonprofit organization and the impact of the donation.

[1410] A "means for a user to input a donation amount to a nonprofit organization selected by the user" is a device or software that provides an interface for a user to input a donation destination and donation amount.

[1411] The "means for processing donations in cooperation with the electronic payment system based on the entered donation amount" refers to the algorithm and software for transmitting the donation amount entered by the user to the electronic payment system, processing the payment, and receiving the transaction results.

[1412] "Means for notifying the user that a donation has been successfully completed and sending a receipt if the donation amount is equal to or greater than a specified amount" refers to software that has the functionality to notify the user that a donation has been successfully completed and to automatically generate and send a receipt if necessary.

[1413] This invention is a system for analyzing a user's areas of interest and emotions, recommending appropriate non-profit organizations, and making donations seamlessly. Specific embodiments of this system will be described below.

[1414] 1. User interest and emotion recognition

[1415] User Device

[1416] First, users access a dedicated application or website and log in to their account. After logging in, they enter their areas of interest (e.g., "environmental protection") in the input field. They can also enter comments and opinions, which are then used for emotion recognition. Sentiment analysis is performed using the Google Cloud Natural Language API.

[1417] 2. Generative AI model recommends suitable nonprofit organizations

[1418] server

[1419] The server receives interest and sentiment data submitted by the user. This data is passed to a generative AI model, such as OpenAI's GPT-3, which then recommends the most suitable nonprofit organization based on the sentiment data. An example of an input prompt for the generative AI model is as follows:

[1420] Prompt Sentence Examples

[1421] The user's area of ​​interest is environmental protection. The sentiment score is 0.8. Generate a list of recommended nonprofit organizations.

[1422] 3. Explanation of the recommendation results and the impact of the donation

[1423] server

[1424] The server retrieves the list of nonprofit organizations output by the generative AI model from the database, obtains detailed information about each organization's activities and the impact of donations, and formats it to resonate with the user's emotions.

[1425] User Device

[1426] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[1427] 4. User Donation Choices

[1428] User Device

[1429] The user selects a nonprofit organization from the list of recommended organizations, enters a value in the donation amount field, and clicks the donate button, which sends the selected organization and donation amount to the server.

[1430] 5. Donation processing through integration with electronic payment systems

[1431] server

[1432] The server receives the donation recipient and donation amount data submitted by the user, uses this information to process the donation through an electronic payment system such as Stripe, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1433] 6. Notification of donation completion and receipt issuance

[1434] server

[1435] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[1436] User Device

[1437] The user's device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1438] This system allows users to donate to nonprofit organizations easily and effectively while increasing emotional satisfaction.

[1439] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1440] Step 1:

[1441] Users access a dedicated application or website and log in to their account. At this time, a login screen appears on the user's device and the user enters their username and password. The entered login information is sent to the server for authentication. If authentication is successful, the user's dashboard is displayed.

[1442] Step 2:

[1443] The user enters the areas of interest in the input field. They can also optionally enter comments or opinions. This information is sent from the user's device to the server. A specific example of input is text such as "I'm interested in environmental protection." The server receives this information and analyzes it using emotion recognition means. The user's text is given as input, and an emotion score (e.g., 0.8) is obtained as output.

[1444] Step 3:

[1445] The server uses the Google Cloud Natural Language API to analyze the sentiment from the text entered by the user. This API analyzes the input text data and outputs a sentiment score and sentiment category (positive, negative, neutral). Based on this output, the user's sentiment data is stored on the server.

[1446] Step 4:

[1447] The server passes the emotion data and the user's areas of interest to a generative AI model. This generative AI model (for example, OpenAI GPT-3) generates a prompt based on the input data and outputs a list of the most suitable nonprofit organizations. An example of a specific prompt is as follows: "The user's area of ​​interest is environmental protection. The emotion score is 0.8. Please generate a list of recommended nonprofit organizations." This prompt is input into the AI ​​model, and a list of nonprofit organizations (for example, environmental protection organization A and environmental protection organization B) is obtained as output.

[1448] Step 5:

[1449] Based on the generated list of nonprofit organizations, the server retrieves detailed information about each organization's activities and the impact of donations from the database. This allows the server to collect information such as the specific activities of the nonprofit organization and the purpose of the donation (e.g., a donation of 3,000 yen will plant 10 trees for tree planting activities). The server formats this information to resonate with the user's emotions and sends it to the user's device.

[1450] Step 6:

[1451] The user's device displays the list of nonprofit organizations and their detailed information sent from the server. The user can review the options for multiple nonprofit organizations on the screen and decide on a specific donation recipient and donation amount (e.g., a donation of 5,000 yen to environmental protection organization A). Once the user makes a selection, the information is sent back to the server.

[1452] Step 7:

[1453] The server receives the data of the nonprofit organization and donation amount selected by the user, and processes the donation by connecting with an electronic payment system such as Stripe. This process involves sending the donation amount using a payment API, and the transaction result is returned. If successful, the donation procedure is completed.

[1454] Step 8:

[1455] If the donation is successful, the server sends the user a notification that the donation has been completed, and if the donation amount is above a certain amount, it automatically generates and sends a receipt. For example, if the donation amount is above 1,000 yen, a receipt will be sent by email. The user's device receives the notification and receipt and displays them to the user. The user can check this display and save the receipt if necessary.

[1456] 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.

[1457] 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.

[1458] 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.

[1459] [Fourth embodiment]

[1460] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1461] 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.

[1462] 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).

[1463] 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.

[1464] 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.

[1465] 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).

[1466] 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.

[1467] 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.

[1468] 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.

[1469] 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.

[1470] 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.

[1471] 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.

[1472] 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."

[1473] The present invention relates to a system that allows users to easily and effectively make donations to non-profit organizations. A specific embodiment of this system will be described below.

[1474] 1. Enter your user interests

[1475] User Device

[1476] A user accesses a dedicated application or web page and logs in. After logging in, the user enters values ​​into input fields to indicate the areas of interest (e.g., "environmental protection"), and when the user presses the submit button, this input data is sent to the server.

[1477] 2. Generative AI model recommends suitable nonprofit organizations

[1478] server

[1479] The server receives user-submitted interest data, passes this data to a generative AI model, which then recommends suitable nonprofits based on the user's interests. The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's input.

[1480] 3. Explanation of the recommendation results and the impact of the donation

[1481] server

[1482] The server receives the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from a database, and formats this information into a format that can be presented to users.

[1483] User Device

[1484] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, it may display information such as "Environmental Protection Organization A" is "carrying out tree planting activities and planting 10 trees for a donation of 3,000 yen."

[1485] 4. User Donation Choices

[1486] User Device

[1487] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[1488] 5. Donation processing through integration with electronic payment systems

[1489] server

[1490] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., PayPay) to process the donation, and receives a response from the electronic payment system confirming whether the donation was successful.

[1491] 6. Notification of donation completion and receipt issuance

[1492] server

[1493] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1494] User Device

[1495] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1496] Specific examples

[1497] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is engaged in tree planting activities, and that a donation of 3,000 yen will plant 10 trees. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, allowing the user to confirm that the donation was made validly.

[1498] This system allows users to easily and effectively donate to non-profit organizations, giving them a sense of social contribution.

[1499] The processing flow will be explained below.

[1500] Step 1:

[1501] User Device

[1502] The user accesses a dedicated application or web page and logs in to their account.

[1503] Step 2:

[1504] User Device

[1505] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[1506] Step 3:

[1507] server

[1508] The server receives the area of ​​interest data sent by the user.

[1509] Step 4:

[1510] server

[1511] The server passes the received data to a generative AI model, which then uses an internal database or external API to generate a list of relevant nonprofits.

[1512] Step 5:

[1513] server

[1514] The generative AI model obtains a list of recommended nonprofit organizations, and then retrieves information about each organization's activities and the effectiveness of donations from a database.

[1515] Step 6:

[1516] server

[1517] Format and deliver information about nonprofits and the impact of donations to users.

[1518] Step 7:

[1519] server

[1520] The formatted information is sent to the user's device.

[1521] Step 8:

[1522] User Device

[1523] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[1524] Step 9:

[1525] User Device

[1526] The user selects a donation destination from the recommended nonprofit organizations, enters the donation amount in the input field, and presses the donate button.

[1527] Step 10:

[1528] server

[1529] The server receives the selected nonprofit organization and donation amount submitted by the user.

[1530] Step 11:

[1531] server

[1532] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[1533] Step 12:

[1534] Electronic payment system

[1535] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[1536] Step 13:

[1537] server

[1538] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[1539] Step 14:

[1540] server

[1541] If the donation is successful, a notification will be sent to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1542] Step 15:

[1543] User Device

[1544] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user confirms that the donation was successful and saves the receipt.

[1545] As a specific example, when a user enters "environmental protection," the generative AI model returns a list of recommendations including "environmental protection organization A" and "environmental protection organization B." If the user then selects to donate 5,000 yen to "environmental protection organization A," the server processes the donation through an electronic payment system, and if successful, sends the user a receipt along with a notification of the completed donation.

[1546] Example 1

[1547] 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."

[1548] In modern society, users face challenges when making donations to nonprofit organizations, as it requires a lot of time and effort and information gathering. It is also difficult for users to find nonprofit organizations that fit their areas of interest. Furthermore, the donation process faces challenges due to the lack of smooth integration with electronic payment systems.

[1549] 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.

[1550] In this invention, the server includes a means for a user to input areas of interest, a means for recommending appropriate organizations using a generative AI model based on the areas of interest input by the user, and a means for explaining the activities of the recommended organizations and the effects of donations, allowing users to easily find nonprofit organizations that fit their areas of interest and making the donation process smoother.

[1551] "User" means an individual or organization that uses the System to make donations to a nonprofit organization.

[1552] "Areas of Interest" are specific categories or topics that users consider important, such as environmental protection, educational support, or medical assistance.

[1553] A "generative AI model" is a type of artificial intelligence technology that recommends suitable nonprofit organizations based on a user's areas of interest. It collects information from internal databases and external APIs to present the best candidates.

[1554] A "non-profit organization" is an organization that does not aim to make a profit but works to solve social problems or for the public good.

[1555] "Activities" refers to the specific projects and initiatives undertaken by the nonprofit organization, such as tree planting activities or educational programs.

[1556] "Effectiveness of Donations" provides detailed information about how users' donated funds are utilized and the results they produce.

[1557] An "electronic payment system" is a system for processing payments online, such as payments using electronic wallets or credit cards.

[1558] "Receipt" means the official payment confirmation issued to a User upon successful Donation.

[1559] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations.

[1560] 1. Enter your user interests

[1561] The user accesses a dedicated application or web page and logs in. After logging in, the user enters information in the field for entering their areas of interest. For example, if the user is interested in "environmental protection," they enter this information and press the "Submit" button. This data is sent from the user's device to the server.

[1562] 2. Generative AI model recommends suitable nonprofit organizations

[1563] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and the model recommends suitable nonprofit organizations based on the user's areas of interest. The generative AI model collects information from an internal database and external APIs and generates a list of the most suitable nonprofit organizations based on the user's input data.

[1564] 3. Explanation of the recommendation results and the impact of the donation

[1565] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from the database. This information is formatted and sent to the user's device. The user then checks the information displayed on the device. For example, "Environmental Protection Organization A" is described as "carrying out tree planting activities, and a donation of 3,000 yen will enable the planting of 10 trees."

[1566] 4. User Donation Choices

[1567] The user selects a nonprofit organization from the list, enters the donation amount in the input field, and then presses the "Donate" button. This action sends the data of the selected nonprofit organization and donation amount from the user's device to the server.

[1568] 5. Donation processing through integration with electronic payment systems

[1569] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1570] 6. Notification of donation completion and receipt issuance

[1571] If the donation is successful, the server will send a notification to the user that the donation has been completed. If the donation amount is above a certain amount (for example, 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt from the server and display them to the user. This will allow the user to confirm that the donation was processed successfully and save the receipt if necessary.

[1572] Examples of specific examples and prompts

[1573] For example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." For each organization, it will explain that "Environmental Protection Organization A" is working to plant 10 trees for a donation of 3,000 yen. If the user selects "Donate 5,000 yen to Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information will be displayed on the user's device, and the user will be able to confirm that the donation was made validly.

[1574] Example prompt sentence:

[1575] "I'm interested in protecting the environment. What nonprofits can you recommend?"

[1576] "I would like to donate to educational support. Can you recommend any organizations?"

[1577] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1578] Step 1:

[1579] User interest input

[1580] The user accesses a dedicated application or web page and logs in. The user enters their area of ​​interest (e.g., "environmental protection") in the input field and presses the submit button. The entered data is sent from the user's device to the server.

[1581] Input: User enters text of interest (e.g., "environmental protection")

[1582] Output: The submitted interest data is stored on the server.

[1583] Step 2:

[1584] Generative AI models recommend suitable nonprofits

[1585] The server receives data on areas of interest submitted by users, passes the data to a generative AI model, and has it recommend suitable nonprofit organizations. The generative AI model collects information from an internal database and external APIs to generate a list of the most suitable nonprofit organizations.

[1586] Input: User interest data

[1587] Output: A list of nonprofits according to their area of ​​interest

[1588] Specific behavior:

[1589] 1. The server queries the database to retrieve data related to the area of ​​interest.

[1590] 2. Input the acquired data into the generative AI model and receive recommendation results.

[1591] Step 3:

[1592] Explanation of recommendation results and donation effects

[1593] The server receives the list of nonprofit organizations output by the generative AI model, retrieves information about each organization's activities and the impact of donations from the database, formats this information, and sends it to the user's device. The user can then view the displayed list of nonprofit organizations and their detailed information.

[1594] Input: A list of nonprofits from a generative AI model

[1595] Output: A formatted list of nonprofits with details

[1596] Specific behavior:

[1597] 1. The server queries the database to retrieve details about each nonprofit organization.

[1598] 2. Format the acquired information and send it to the user's device.

[1599] Step 4:

[1600] User donation choices

[1601] The user selects a nonprofit organization from the list, enters the donation amount, and then presses the "Donate" button, which sends the selected nonprofit organization and donation amount data to the server.

[1602] Input: User-selected nonprofit and donation amount

[1603] Output: Nonprofit organization and donation amount data sent to the server

[1604] Step 5:

[1605] Donation processing through integration with electronic payment systems

[1606] The server receives the donation amount and the selected nonprofit organization data submitted by the user, uses this data to send a transaction to an electronic payment system (e.g., an electronic wallet system) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1607] Input: User-selected nonprofit organization and donation amount data

[1608] Output: Transaction processing results from the electronic payment system

[1609] Specific behavior:

[1610] 1. The server sends the donation amount and nonprofit organization to the payment API.

[1611] 2. Wait for a response from the electronic payment system and receive the processing result.

[1612] Step 6:

[1613] Donation completion notification and receipt issuance

[1614] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount (e.g., 1,000 yen), the server will automatically generate a receipt and send it to the user. The user's device will receive the notification and receipt and display them to the user.

[1615] Input: Transaction processing results from electronic payment system

[1616] Output: Donation completion notification and receipt (if applicable) to the user

[1617] Specific behavior:

[1618] 1. The server generates a donation completion notification and sends it to the user's device.

[1619] 2. For donations of 1,000 yen or more, the server automatically generates a receipt and sends it to the user.

[1620] (Application example 1)

[1621] 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."

[1622] In modern society, donations to nonprofit organizations are becoming increasingly important as a form of social contribution. However, the process of finding a nonprofit organization that matches a user's area of ​​interest and making a donation is complicated. Furthermore, if there is a lack of information about the effects of donations and the specific activities they carry out, it is difficult to attract users' attention. Furthermore, there is a need for a method to simplify the donation process by linking it with an electronic payment system. The purpose of this invention is to solve these problems and provide a system that allows users to donate to nonprofit organizations easily and effectively.

[1623] 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.

[1624] In this invention, the server includes: means for allowing a user to input their areas of interest; means for using a generative AI model to recommend appropriate nonprofit organizations based on the user's areas of interest; means for explaining the activities of the recommended nonprofit organizations and the benefits of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for linking with an electronic payment system to process the donation based on the input donation amount; means for sending the user a donation completion notification if the donation is successful and a receipt if the donation amount is above a predetermined amount; and means for integrating the entire process from inputting the user's areas of interest to notifying the electronic payment system of the completion of donation processing within a smartphone application. This allows users to easily find nonprofit organizations based on their areas of interest, understand the benefits of donations, and make donations easily.

[1625] "User" refers to an individual who uses an Electronic Device to make a donation to a nonprofit organization.

[1626] "Interest areas" refer to specific topics or issue areas that interest a user.

[1627] "Generative AI model" refers to a machine learning model that recommends suitable nonprofit organizations based on input data.

[1628] A "nonprofit organization" is a non-profit organization that pursues a specific social purpose.

[1629] "Smartphone Application" means a software application that runs on a smartphone.

[1630] "Electronic payment system" means an information technology system used to complete monetary transactions digitally.

[1631] "Donation Processing" refers to the series of steps taken to complete the transfer of money from a user to a nonprofit organization.

[1632] "Donation Completion Notification" refers to a message sent to a User to inform them that their donation has been successfully processed.

[1633] "Receipt" refers to any written or electronic evidence that proves a donation was made.

[1634] "Flow" refers to a series of operations or steps performed to achieve a specific goal.

[1635] The present invention relates to a system that enables users to easily and effectively make donations to non-profit organizations. Specific embodiments of the present invention will now be described.

[1636] 1. Enter your user interests

[1637] Users input their areas of interest (e.g., "environmental protection") on the smartphone application. This input interface is provided through a dedicated input field. When the user inputs their area of ​​interest and presses the submit button, this data is sent to a server via the Internet.

[1638] 2. Generative AI model recommends suitable nonprofit organizations

[1639] The server receives the user's submitted interest data and passes it to a generative AI model, which then references an internal database and external APIs to generate a list of suitable nonprofits based on the user's input.

[1640] 3. Explanation of the recommendation results and the impact of the donation

[1641] The server receives the list of nonprofit organizations output by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations. This information is formatted in a user-friendly format and provided to users through a smartphone application.

[1642] 4. User Donation Choices

[1643] The user selects a donation recipient from a list of nonprofit organizations and enters the amount of the donation. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. The user's selection and the entered donation amount are sent to the server.

[1644] 5. Donation processing through integration with electronic payment systems

[1645] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to send a transaction to an electronic payment system (e.g., a payment API) to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1646] 6. Notification of donation completion and receipt issuance

[1647] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, a receipt will be automatically generated and sent to the user. The user can then view the notification and receipt on their smartphone application.

[1648] As a specific example, if a user inputs that they are interested in "environmental protection," the generative AI model will recommend "Environmental Protection Organization A" and "Environmental Protection Organization B." Detailed descriptions of each organization are provided to the user, and if the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation via an electronic payment system and, if successful, sends the user a notification of donation completion and a receipt.

[1649] Example prompts to input to a generative AI model:

[1650] The user has entered the following area of ​​interest: Environmental protection. Please recommend suitable nonprofit organizations based on the following criteria:

[1651] conditions:

[1652] An organization that engages in environmental protection activities.

[1653] The specific activities and the effects of the donation must be clearly stated.

[1654] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1655] Step 1:

[1656] Users enter their areas of interest into the smartphone application, and the entered data is sent to a server via the Internet.

[1657] Input: Area of ​​interest (e.g. "Environmental protection")

[1658] Output: User interest data sent to the server

[1659] Step 2:

[1660] The server receives the user's submitted interest data, passes it to the generative AI model, and begins the process of recommending suitable nonprofit organizations.

[1661] Input: User interest data

[1662] Output: Data to be passed to the generative AI model

[1663] Step 3:

[1664] The generative AI model uses the interest data passed from the server to reference an internal database and external APIs to generate a list of suitable nonprofit organizations.

[1665] Input: Area of ​​interest data

[1666] Data Processing: Searching for nonprofit information from internal databases and external APIs

[1667] Output: A list of recommended nonprofits

[1668] Step 4:

[1669] Based on the list of nonprofit organizations received from the generative AI model, the server retrieves detailed information about each organization's activities and the impact of donations from its internal database and formats it into a form that can be provided to users.

[1670] Input: List of nominated nonprofits

[1671] Data processing: Acquisition and formatting of activity details and donation effect information from the internal database

[1672] Output: A list of nonprofits with formatted details.

[1673] Step 5:

[1674] The server then sends the formatted list of nonprofit organizations to the smartphone application and displays it to the user, who then decides which organization to donate to and how much to donate.

[1675] Input: A formatted list of nonprofits

[1676] Output: Information displayed on the smartphone application

[1677] Step 6:

[1678] The user selects the donation recipient and donation amount on the smartphone application and sends the entered data to the server.

[1679] Input: User's chosen donation destination and donation amount

[1680] Output: Donation recipient and donation amount data sent to the server

[1681] Step 7:

[1682] The server receives donation recipient and donation amount data from the user, sends the transaction to the electronic payment system, and processes the donation.

[1683] Input: Donation recipient and donation amount data

[1684] Output: Transaction data sent to electronic payment systems

[1685] Step 8:

[1686] The electronic payment system processes the transaction and sends the results back to the server, which receives the results and verifies whether the donation was successful.

[1687] Input: Transaction result data from electronic payment systems

[1688] Output: Confirmation of successful donation

[1689] Step 9:

[1690] If the donation is successful, the server will send a notification to the user. If the donation amount is above a certain amount, the server will automatically generate a receipt and send it to the user.

[1691] Input: Donation success confirmation data

[1692] Output: Sending a donation completion notification and receipt

[1693] Step 10:

[1694] Users can check the donation completion notification and receipt on their smartphone application to confirm that their donation was successful.

[1695] Input: Donation completion notice and receipt

[1696] Output: Display on smartphone application

[1697] 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.

[1698] This invention is a system that combines an emotion engine that recognizes the user's emotions, allowing users to easily and effectively donate to non-profit organizations. Specific embodiments of this system will be described below.

[1699] 1. User interest and emotion recognition

[1700] User Device

[1701] The user accesses a dedicated application or web page and logs in to their account. After logging in, the user enters a value in an input field to indicate their area of ​​interest (e.g., "environmental protection").

[1702] Emotion Engine

[1703] Based on the user's inputted areas of interest, the emotion engine analyzes the user's emotions. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the text entered by the user.

[1704] 2. Generative AI model recommends suitable nonprofit organizations

[1705] server

[1706] The server receives the user's interest data and the results of the emotion engine analysis, and then passes the information to the generative AI model, instructing it to recommend suitable nonprofit organizations based on this data.

[1707] The generative AI model uses information from an internal database and external APIs to generate a list of nonprofits that best fit the user's sentiment and areas of interest. The results of the analysis by the sentiment engine provide optimal recommendations based on the user's sentiment.

[1708] 3. Explanation of the recommendation results and the impact of the donation

[1709] server

[1710] The server takes the list of nonprofits output by the generative AI model, retrieves detailed information about each organization's activities and the impact of donations from the database, and formats this information to be presented to the user in a way that resonates with their emotions.

[1711] User Device

[1712] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details to the user. For example, information such as "Environmental Protection Organization A" will "carry out tree planting activities and plant 10 trees for a donation of 3,000 yen" will be displayed. At this time, explanations and effects that correspond to the user's emotions are emphasized.

[1713] 4. User Donation Choices

[1714] User Device

[1715] The user selects a donation recipient from the recommended nonprofit organizations, enters a value in the donation amount field, and presses the donate button, which sends the selected nonprofit organization and donation amount to the server.

[1716] 5. Donation processing through integration with electronic payment systems

[1717] server

[1718] The server receives the user's data on the selected nonprofit organization and donation amount, uses this data to submit a transaction to the electronic payment system to process the donation, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1719] 6. Notification of donation completion and receipt issuance

[1720] server

[1721] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1722] User Device

[1723] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1724] Specific examples

[1725] For example, if a user inputs that they are interested in "environmental protection," the emotion engine analyzes the user's input text. The generative AI model returns a list of recommendations: "Environmental Protection Organization A" and "Environmental Protection Organization B." Depending on the user's emotions, explanations that resonate with the user's emotions are emphasized when explaining the activities of each nonprofit organization and the effects of donations. If the user then selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system, and if successful, sends the user a receipt along with a notification that the donation has been completed. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[1726] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[1727] The processing flow will be explained below.

[1728] Step 1:

[1729] User Device

[1730] The user accesses a dedicated application or web page and logs in to their account.

[1731] Step 2:

[1732] User Device

[1733] The user enters their area of ​​interest (e.g., "environmental protection") into the input field and presses the submit button.

[1734] Step 3:

[1735] server

[1736] The server receives the area of ​​interest data sent by the user.

[1737] Step 4:

[1738] Emotion Engine

[1739] The emotion engine analyzes the user's input data and recognizes the user's emotion, which is then used throughout the system.

[1740] Step 5:

[1741] server

[1742] The server passes the user's interest data and the results of the sentiment engine analysis to the generative AI model, instructing it to recommend appropriate nonprofit organizations.

[1743] Step 6:

[1744] Generative AI Models

[1745] A generative AI model searches a database for relevant nonprofit listings based on the user's areas of interest and sentiment, generating the best recommendation list.

[1746] Step 7:

[1747] server

[1748] The server receives the list of nonprofit organizations returned by the generative AI model and retrieves detailed information about each organization's activities and the impact of donations from a database.

[1749] Step 8:

[1750] server

[1751] The acquired information is formatted, emphasis is added based on the user's emotions, and it is then converted into a form that can be presented to the user.

[1752] Step 9:

[1753] server

[1754] The formatted information is sent to the user's device.

[1755] Step 10:

[1756] User Device

[1757] The user's device displays the received information, and from the list of nonprofit organizations displayed, the user can check the details of each organization's activities and the impact of donations.

[1758] Step 11:

[1759] User Device

[1760] The user selects a donation destination from the recommended nonprofit organizations, enters a value in the donation amount field, and clicks the donate button.

[1761] Step 12:

[1762] server

[1763] The server receives the selected nonprofit organization and donation amount data submitted by the user.

[1764] Step 13:

[1765] server

[1766] The server sends the donation information to the electronic payment system (e.g., PayPay) and instructs it to process the transaction.

[1767] Step 14:

[1768] Electronic payment system

[1769] The electronic payment system receives the donation amount, executes the transaction to process the donation, and sends the result of the transaction back to the server.

[1770] Step 15:

[1771] server

[1772] The server receives a response from the electronic payment system and verifies whether the donation was successful.

[1773] Step 16:

[1774] server

[1775] If the donation is successful, the server will send a notification to the user. If the donation amount is 1000 yen or more, a receipt will be automatically generated and sent to the user.

[1776] Step 17:

[1777] User Device

[1778] The user's device receives a notification of the donation completion and a receipt, which are then displayed to the user. The user can confirm that the donation was successful and save the receipt if necessary.

[1779] As a concrete example, suppose a user indicates an interest in "environmental protection," and the emotion engine recognizes a "positive" emotion. The generative AI model recommends "Environmental Protection Organization A" and "Environmental Protection Organization B," explaining to the user that "Environmental Protection Organization A is engaged in tree planting activities, and a donation of 3,000 yen will allow 10 trees to be planted," while emphasizing the emotional element that "their activities will significantly contribute to preventing global warming." As a result, the user selects to donate 5,000 yen to "Environmental Protection Organization A," and the server processes the donation through the electronic payment system. If the donation is successful, a receipt is sent along with a notification of donation completion, which is displayed on the user's device. The user can confirm that their donation was made validly, and feel a sense of satisfaction.

[1780] Example 2

[1781] 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."

[1782] When users donate to nonprofit organizations, it is difficult to determine which organization is the most appropriate, and the donation process is often cumbersome, making the activity tedious. In particular, there is a concern that users' motivation to donate may decrease due to a lack of emotionally appealing explanations of the benefits and activities of donations. Therefore, there is a need for a system that can recommend appropriate nonprofit organizations based on users' emotions, simplify the donation process, and increase emotional satisfaction.

[1783] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1784] In this invention, the server includes a means for a user to input an area of ​​interest, a means for analyzing the user's emotions using an emotion recognition engine based on the area of ​​interest input by the user, and a means for recommending an appropriate business entity using a generative AI model based on the analyzed emotions and area of ​​interest. This makes it possible to recommend the most appropriate nonprofit organization according to the user's emotions, simplify the donation process, and increase the user's emotional satisfaction.

[1785] 1. "User" means an individual or organization that uses the System to make donations to a non-profit organization.

[1786] 2. "Area of ​​Interest" refers to a specific area or topic that a user is interested in.

[1787] 3. An "emotion recognition engine" is a technology that analyzes the user's input text and recognizes emotional trends.

[1788] 4. "Generative AI model" means an artificial intelligence model that recommends appropriate businesses based on a user's emotions and areas of interest.

[1789] 5. "Entity" means a nonprofit organization or other charitable organization.

[1790] 6. "Electronic Payment System" means an online payment system for conducting monetary transactions via the Internet.

[1791] 7. "Payment Interface" means a technical means for interfacing with an electronic payment system to process transactions.

[1792] 8. "Transaction processing result" means the processing result information returned from the electronic payment system.

[1793] 9. "Receipt" means a document issued to certify that a donation has been made successfully.

[1794] This invention is a system that combines an emotion recognition engine that recognizes user emotions with a generative AI model, allowing users to easily and effectively make donations to nonprofit organizations.

[1795] System Overview

[1796] The system consists of a user terminal, a server, an emotion recognition engine, a generative AI model, and an electronic payment system. The role and operation of each component are explained in detail below.

[1797] User Device

[1798] The user terminal is operated through a dedicated application or web page, where the user logs into their account and enters their area of ​​interest (e.g., "environmental protection").

[1799] Emotion Recognition Engine

[1800] The emotion recognition engine analyzes the user's emotions based on the areas of interest entered by the user. This emotion analysis is performed using natural language processing technology to recognize emotional trends from the user's text. For example, if a user enters "I'm concerned about environmental issues," that emotion is analyzed and stored as data.

[1801] Generative AI Models

[1802] The server receives the user's interest data and the analysis results of the emotion recognition engine. Based on this data, it passes information to a generative AI model that recommends suitable nonprofit organizations. This generative AI model collects information from an internal database and external APIs and generates a list of nonprofit organizations that best fit the user's emotions and areas of interest.

[1803] Presentation of recommendation results

[1804] The server obtains the list of nonprofit organizations output by the generative AI model and collects detailed information from a database about each organization's activities and the impact of donations. This information is formatted to resonate with the user's emotions and sent to the user's device. The user's device receives the information sent from the server and displays the list of nonprofit organizations and their detailed information to the user. For example, it may display information such as "Environmental Protection Organization A" "carries out tree planting activities and plants 10 trees for a donation of 3,000 yen."

[1805] Select and enter your donation

[1806] Users select a donation destination from the recommended nonprofit organizations and enter the donation amount, which is then sent to a server and sent as transaction data to an electronic payment system.

[1807] Processing donations

[1808] The server interacts with the electronic payment system, processes the donation based on the transaction data sent, receives a response from the electronic payment system, and verifies whether the donation was successful.

[1809] Donation completion notification and receipt issuance

[1810] If the donation is successful, the server sends the user a notification of the completion of the donation, and if the donation amount is equal to or greater than a predetermined amount, it automatically generates and sends a receipt. The user's device receives this notification and receipt and displays them to the user.

[1811] Specific examples

[1812] For example, if a user inputs that they are interested in "environmental protection," the emotion recognition engine analyzes the user's input text and the generative AI model recommends appropriate nonprofit organizations. The explanation is emphasized according to the user's emotion. If the user selects to donate 5,000 yen to "Environmental Protection Organization A," the server processes the donation through the electronic payment system and, if successful, sends the user a receipt along with a notification of the completed donation. This information is displayed on the user's device, allowing the user to confirm that the donation was made validly.

[1813] Prompt Sentence Examples

[1814] "If I'm interested in protecting the environment, what nonprofits would you recommend?"

[1815] "Explain how to use an emotion recognition engine to analyze user emotions."

[1816] "What notification will be sent to users upon successful donation?"

[1817] This system allows users to donate to nonprofit organizations easily and effectively, while also increasing emotional satisfaction.

[1818] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1819] Step 1:

[1820] user

[1821] Users access a dedicated application or web page and log in to their account. They enter their user ID and password on the login screen, and once authentication is successful, the main screen is displayed.

[1822] Input: User ID, Password

[1823] Output: Authentication success message, main screen display

[1824] Step 2:

[1825] user

[1826] The user enters the area of ​​interest (e.g., "environmental protection") into the input field on the main screen, and then clicks the "Submit" button.

[1827] Input: Area of ​​interest (e.g., "environmental protection")

[1828] Output: Region of interest data transmission

[1829] Step 3:

[1830] Emotion Recognition Engine

[1831] The emotion recognition engine receives the area of ​​interest data sent by the user and analyzes the user's emotions using natural language processing technology. For example, it recognizes the emotion "worry" from the input "I'm worried about environmental issues."

[1832] Input: Region of interest data

[1833] Output: Sentiment analysis result (e.g. "worried")

[1834] Step 4:

[1835] server

[1836] The server receives and temporarily stores the analyzed emotion and interest data, and then passes this data to the generative AI model, which then instructs it to recommend suitable nonprofit organizations.

[1837] Input: Sentiment analysis results, area of ​​interest data

[1838] Output: Data provision instructions

[1839] Step 5:

[1840] Generative AI Models

[1841] The generative AI model uses data provided by the server, collects information from internal databases and external APIs, and generates a list of the most suitable nonprofit organizations.

[1842] Input: Sentiment analysis results, area of ​​interest data

[1843] Output: List of recommended nonprofits

[1844] Step 6:

[1845] server

[1846] The server receives the list of recommended nonprofit organizations obtained from the generative AI model, collects detailed information about each organization's activities and the impact of donations from a database, formats this information to resonate with the user's emotions, and sends it to the user's device.

[1847] Input: List of recommended nonprofit organizations

[1848] Output: Formatted organization information

[1849] Step 7:

[1850] User Device

[1851] The user device receives the list of nonprofit organizations and their details from the server and displays them to the user. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[1852] Input: Formatted organization information

[1853] Output: Group information display

[1854] Step 8:

[1855] user

[1856] Users can select a donation recipient from a list of nonprofit organizations, enter the amount they would like to donate, and then click the "Donate" button to send the selected organization and donation amount to the server.

[1857] Input: Donation destination selection, donation amount

[1858] Output: Send donation information

[1859] Step 9:

[1860] server

[1861] The server receives the donation recipient and donation amount data sent by the user and sends it to the electronic payment system as transaction data. The electronic payment system processes the donation based on this transaction data.

[1862] Input: Donation recipient, donation amount

[1863] Output: Transaction data sent

[1864] Step 10:

[1865] Electronic Payment Systems

[1866] The electronic payment system processes the donation and returns the result to the server, which receives the result and verifies whether the donation was successful.

[1867] Input: Transaction data

[1868] Output: Donation processing result

[1869] Step 11:

[1870] server

[1871] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[1872] Input: Donation processing result

[1873] Output: Donation completion notification, receipt

[1874] Step 12:

[1875] User Device

[1876] The user device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1877] Input: Donation completion notification, receipt

[1878] Output: Notification display, receipt display

[1879] (Application example 2)

[1880] 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."

[1881] When promoting donations to nonprofit organizations, it is necessary not only to recommend appropriate organizations based on the user's areas of interest, but also to suggest donations that are tailored to the user's emotions. Furthermore, to increase the user's satisfaction after donating, it is necessary to explain the effects of donations and the activities involved in them in an emotional way. Furthermore, it is necessary to link seamlessly with an electronic payment system to simplify the donation process. The lack of an integrated system that satisfies these multiple requirements is a challenge.

[1882] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1883] In this invention, the server includes: means for allowing a user to input areas of interest; emotion recognition means for analyzing the user's input areas of interest and emotions; means for recommending appropriate nonprofit organizations using a generative AI model based on emotion data obtained from the emotion recognition means; means for explaining the activities of the recommended nonprofit organizations and the effects of donations; means for providing the explanation to the user; means for allowing the user to input a donation amount to the nonprofit organization selected by the user; means for processing the donation in cooperation with an electronic payment system based on the input donation amount; and means for sending the user a donation completion notification when the donation is successful and a receipt if the donation amount is above a predetermined amount. This makes it possible to recommend appropriate nonprofit organizations for donations based on the user's emotions and areas of interest, making the donation process simple and effective.

[1884] A "means for user input of areas of interest" is a device or software that provides an interface for users to input their areas of interest through text or options.

[1885] "Emotion recognition means for analyzing emotions" is software that has the function of analyzing emotions from text entered by a user using natural language processing technology and recognizing the emotional state as a number or category.

[1886] "Means for recommending appropriate nonprofit organizations using a generative AI model" refers to algorithms and software that utilize a generative AI model to extract appropriate nonprofit organizations and generate a recommendation list based on a user's areas of interest and emotional data.

[1887] The "means for explaining the activities of the recommended nonprofit organization and the impact of donations" is software that has the function of generating text and diagrams that clearly explain to users the activities of the recommended nonprofit organization and how donations will be used.

[1888] A "means for providing an explanation to a user" is a device or software that displays visual and textual information to a user about the recommended nonprofit organization and the impact of the donation.

[1889] A "means for a user to input a donation amount to a nonprofit organization selected by the user" is a device or software that provides an interface for a user to input a donation destination and donation amount.

[1890] The "means for processing donations in cooperation with the electronic payment system based on the entered donation amount" refers to the algorithm and software for transmitting the donation amount entered by the user to the electronic payment system, processing the payment, and receiving the transaction results.

[1891] "Means for notifying the user that a donation has been successfully completed and sending a receipt if the donation amount is equal to or greater than a specified amount" refers to software that has the functionality to notify the user that a donation has been successfully completed and to automatically generate and send a receipt if necessary.

[1892] This invention is a system for analyzing a user's areas of interest and emotions, recommending appropriate non-profit organizations, and making donations seamlessly. Specific embodiments of this system will be described below.

[1893] 1. User interest and emotion recognition

[1894] User Device

[1895] First, users access a dedicated application or website and log in to their account. After logging in, they enter their areas of interest (e.g., "environmental protection") in the input field. They can also enter comments and opinions, which are then used for emotion recognition. Sentiment analysis is performed using the Google Cloud Natural Language API.

[1896] 2. Generative AI model recommends suitable nonprofit organizations

[1897] server

[1898] The server receives interest and sentiment data submitted by the user. This data is passed to a generative AI model, such as OpenAI's GPT-3, which then recommends the most suitable nonprofit organization based on the sentiment data. An example of an input prompt for the generative AI model is as follows:

[1899] Prompt Sentence Examples

[1900] The user's area of ​​interest is environmental protection. The sentiment score is 0.8. Generate a list of recommended nonprofit organizations.

[1901] 3. Explanation of the recommendation results and the impact of the donation

[1902] server

[1903] The server retrieves the list of nonprofit organizations output by the generative AI model from the database, obtains detailed information about each organization's activities and the impact of donations, and formats it to resonate with the user's emotions.

[1904] User Device

[1905] The user's device receives the information sent from the server and displays a list of nonprofit organizations and their details. For example, it displays information such as "Environmental Protection Organization A" is "carrying out tree planting activities and will plant 10 trees for a donation of 3,000 yen."

[1906] 4. User Donation Choices

[1907] User Device

[1908] The user selects a nonprofit organization from the list of recommended organizations, enters a value in the donation amount field, and clicks the donate button, which sends the selected organization and donation amount to the server.

[1909] 5. Donation processing through integration with electronic payment systems

[1910] server

[1911] The server receives the donation recipient and donation amount data submitted by the user, uses this information to process the donation through an electronic payment system such as Stripe, and receives a response from the electronic payment system to confirm whether the donation was successful.

[1912] 6. Notification of donation completion and receipt issuance

[1913] server

[1914] If the donation is successful, the server will send a notification to the user. If the donation amount is more than a certain amount, the server will automatically generate a receipt and send it to the user.

[1915] User Device

[1916] The user's device receives the notification and receipt from the server and displays them to the user, allowing the user to confirm that the donation was successful and to save the receipt if desired.

[1917] This system allows users to donate to nonprofit organizations easily and effectively while increasing emotional satisfaction.

[1918] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1919] Step 1:

[1920] Users access a dedicated application or website and log in to their account. At this time, a login screen appears on the user's device and the user enters their username and password. The entered login information is sent to the server for authentication. If authentication is successful, the user's dashboard is displayed.

[1921] Step 2:

[1922] The user enters the areas of interest in the input field. They can also optionally enter comments or opinions. This information is sent from the user's device to the server. A specific example of input is text such as "I'm interested in environmental protection." The server receives this information and analyzes it using emotion recognition means. The user's text is given as input, and an emotion score (e.g., 0.8) is obtained as output.

[1923] Step 3:

[1924] The server uses the Google Cloud Natural Language API to analyze the sentiment from the text entered by the user. This API analyzes the input text data and outputs a sentiment score and sentiment category (positive, negative, neutral). Based on this output, the user's sentiment data is stored on the server.

[1925] Step 4:

[1926] The server passes the emotion data and the user's areas of interest to a generative AI model. This generative AI model (for example, OpenAI GPT-3) generates a prompt based on the input data and outputs a list of the most suitable nonprofit organizations. An example of a specific prompt is as follows: "The user's area of ​​interest is environmental protection. The emotion score is 0.8. Please generate a list of recommended nonprofit organizations." This prompt is input into the AI ​​model, and a list of nonprofit organizations (for example, environmental protection organization A and environmental protection organization B) is obtained as output.

[1927] Step 5:

[1928] Based on the generated list of nonprofit organizations, the server retrieves detailed information about each organization's activities and the impact of donations from the database. This allows the server to collect information such as the specific activities of the nonprofit organization and the purpose of the donation (e.g., a donation of 3,000 yen will plant 10 trees for tree planting activities). The server formats this information to resonate with the user's emotions and sends it to the user's device.

[1929] Step 6:

[1930] The user's device displays the list of nonprofit organizations and their detailed information sent from the server. The user can review the options for multiple nonprofit organizations on the screen and decide on a specific donation recipient and donation amount (e.g., a donation of 5,000 yen to environmental protection organization A). Once the user makes a selection, the information is sent back to the server.

[1931] Step 7:

[1932] The server receives the data of the nonprofit organization and donation amount selected by the user, and processes the donation by connecting with an electronic payment system such as Stripe. This process involves sending the donation amount using a payment API, and the transaction result is returned. If successful, the donation procedure is completed.

[1933] Step 8:

[1934] If the donation is successful, the server sends the user a notification that the donation has been completed, and if the donation amount is above a certain amount, it automatically generates and sends a receipt. For example, if the donation amount is above 1,000 yen, a receipt will be sent by email. The user's device receives the notification and receipt and displays them to the user. The user can check this display and save the receipt if necessary.

[1935] 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.

[1936] 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.

[1937] 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.

[1938] 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.

[1939] 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.

[1940] 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.

[1941] 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).

[1942] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1943] 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."

[1944] 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.

[1945] 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).

[1946] 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.

[1947] 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.

[1948] 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.

[1949] 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.

[1950] 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.

[1951] 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.

[1952] 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.

[1953] 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.

[1954] 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.

[1955] 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.

[1956] The following is further disclosed regarding the above embodiment.

[1957] (Claim 1)

[1958] a means for a user to input areas of interest;

[1959] a means for recommending suitable nonprofit organizations using a generative AI model based on the user's input areas of interest;

[1960] A means of explaining the activities of the nominated nonprofit organization and the impact of the donation;

[1961] means for providing said description to a user;

[1962] a means for the user to input a donation amount to a selected nonprofit organization;

[1963] a means for processing donations in cooperation with an electronic payment system based on the input donation amount;

[1964] a means for sending a notification of completion of donation to the user when the donation is successful and a receipt if the donation amount is equal to or greater than a predetermined amount;

[1965] A system including:

[1966] (Claim 2)

[1967] The system of claim 1, wherein the means for recommending appropriate nonprofit organizations using a generative AI model searches a database for a list of nonprofit organizations that correspond to the input area of ​​interest and generates the list.

[1968] (Claim 3)

[1969] The system of claim 1, wherein the means for linking with the electronic payment system and processing donations transmits the user's selection and input donation amount to the electronic payment system using a payment API and receives the transaction processing result.

[1970] "Example 1"

[1971] (Claim 1)

[1972] a means for a user to input areas of interest;

[1973] A means for recommending suitable organizations using a generative AI model based on the user's inputted areas of interest;

[1974] A means of explaining the activities of the nominated organization and the impact of the donation;

[1975] means for providing said description to a user;

[1976] a means for the user to input a donation amount to a selected organization;

[1977] a means for processing donations in cooperation with an electronic payment system based on the input donation amount;

[1978] a means for sending a notification of completion of donation to the user when the donation is successful and a receipt if the donation amount is equal to or exceeds a predetermined amount;

[1979] A system including:

[1980] (Claim 2)

[1981] The system of claim 1, wherein the means for recommending appropriate organizations using a generative AI model searches a database for a list of organizations that correspond to the input field of interest and generates the list.

[1982] (Claim 3)

[1983] The system of claim 1, wherein the means for linking with the electronic payment system and processing donations transmits the user's selection and input donation amount to the electronic payment system using a payment API and receives the transaction processing result.

[1984] "Application Example 1"

[1985] (Claim 1)

[1986] a means for a user to input areas of interest;

[1987] a means for recommending suitable nonprofit organizations using a generative AI model based on the user's input areas of interest;

[1988] A means of explaining the activities of the nominated nonprofit organization and the impact of the donation;

[1989] means for providing said description to a user;

[1990] a means for the user to input a donation amount to a selected nonprofit organization;

[1991] a means for processing donations in cooperation with an electronic payment system based on the input donation amount;

[1992] a means for sending a notification of completion of donation to the user when the donation is successful and a receipt if the donation amount is equal to or greater than a predetermined amount;

[1993] A means for processing a series of steps from inputting a user's area of ​​interest to notification of completion of donation processing in an electronic payment system in an integrated manner within a smartphone application;

[1994] A system including:

[1995] (Claim 2)

[1996] The system of claim 1, wherein the means for recommending appropriate nonprofit organizations using a generative AI model searches a database for a list of nonprofit organizations that correspond to the input area of ​​interest and generates the list.

[1997] (Claim 3)

[1998] The system according to claim 1, wherein the means for processing donations in cooperation with the electronic payment system transmits the user's selection and input donation amount to the electronic payment system using a payment API and receives the transaction processing result.

[1999] "Example 2: Combining Emotion Engines"

[2000] (Claim 1)

[2001] means for a user to input an area of ​​interest;

[2002] means for analyzing the user's emotions using an emotion recognition engine based on the area of ​​interest input by the user;

[2003] A means for recommending suitable entities using a generative AI model based on the analyzed emotions and areas of interest;

[2004] A means of explaining the activities of the nominated entity and the impact of the donation;

[2005] means for providing said description to a user;

[2006] a means for the user to input a donation amount to a selected entity;

[2007] a means for processing donations in cooperation with an electronic payment system based on the input donation amount;

[2008] a means for sending a notification of completion of donation to the user when the donation is successful and a receipt if the donation amount is equal to or greater than a predetermined amount;

[2009] A system including:

[2010] (Claim 2)

[2011] The system of claim 1 uses an emotion recognition engine to analyze the user's emotions, and ...

Claims

1. a means for a user to input areas of interest; a means for recommending suitable nonprofit organizations using a generative AI model based on the user's input areas of interest; A means of explaining the activities of the nominated nonprofit organization and the impact of the donation; means for providing said description to a user; a means for the user to input a donation amount to a selected nonprofit organization; a means for processing donations in cooperation with an electronic payment system based on the input donation amount; a means for sending a notification of completion of donation to the user when the donation is successful and a receipt if the donation amount is equal to or greater than a predetermined amount; A system including:

2. The system of claim 1, wherein the means for recommending suitable nonprofit organizations using a generative AI model searches a database for a list of nonprofit organizations that correspond to the input area of ​​interest and generates the list.

3. The system of claim 1, wherein the means for linking with the electronic payment system and processing donations transmits the user's selection and input donation amount to the electronic payment system using a payment API and receives the transaction processing result.

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