system

Abstract

We provide the system. [Solution] An input method for the user to enter information, A transmission means for sending information from the input means to a server, A generation means that generates information based on the information received from the transmission means, A presentation means for presenting the information generated by the generation means to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventional proposals for electronic payment means merely convey service contents, and it has been difficult to clearly present in what specific scenes users can utilize such services. In addition, due to the lack of proposals tailored to individual users' life scenes, it has been difficult for users to specifically understand the proposed contents and incorporate them into their actual lives. To solve this problem, a system is provided that allows users to receive specific proposals while enjoying themselves.

Means for Solving the Problems

[0005] The present invention is a system comprising an input means for a user to input information, a transmission means for transmitting the information from the input means to a server, a generation means for generating information based on the information received from the transmission means, and a presentation means for presenting the information generated by the generation means to the user. The generation means uses generative artificial intelligence to generate information based on conditions specified by the user, thereby making suggestions to users of a specific age group to utilize specific electronic payment methods in their daily lives. This makes it easier for users to understand how they can utilize electronic payment methods in specific situations and to incorporate them into their lives.

[0006] "Input means" refers to devices or interfaces that users use to input information.

[0007] "Transmission means" refers to the functions or devices used to transmit information from input means to a server.

[0008] "Generation means" refers to devices or systems used to generate new information based on received information.

[0009] "Presentation means" refers to devices or interfaces for presenting generated information to a user visually or in other formats.

[0010] "Generative artificial intelligence" refers to artificial intelligence technology that generates new information or suggestions based on input conditions, using specific algorithms or trained models.

[0011] "Electronic payment methods" refer to payment methods and systems for conducting transactions electronically.

[0012] "System" refers to an integrated device or network that combines the input means, transmission means, generation means, and presentation means described above.

[0013] A "user" refers to a typical user who uses the system to input information and receive suggestions.

[0014] "Server" refers to a central processing unit that receives information from users, processes it, and returns the results.

[0015] "Proposed scenario" refers to a specific life situation or situation in which specific electronic payment means are used.

[0016] "Specific age group" refers to users belonging to a specific age range set by the system.

[0017] "Life scene" refers to a specific scene or situation in which certain actions or activities are performed in daily life.

Brief Description of Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Modes for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[0040] System Configuration

[0041] 1. Input method

[0042] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[0043] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[0044] 2. Transmission method

[0045] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[0046] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[0047] 3. Generation means

[0048] The server uses generative artificial intelligence (AI) based on the received information to generate appropriate suggestions. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[0049] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0050] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[0051] Use electronic payment methods when making small purchases at convenience stores.

[0052] I use electronic payment methods for regular tea and cafe visits.

[0053] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[0054] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[0055] 4. Presentation means

[0056] The server sends the generated suggestions back to the terminal, which then presents the information to the user. The user can then view the specific suggestions on the screen.

[0057] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[0058] Specific example

[0059] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[0060] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[0061] 2. Use electronic payment methods when making small purchases at convenience stores.

[0062] 3. Use electronic payment methods for regular tea or cafe visits.

[0063] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[0064] Users can review these specific suggestions and understand, for example, how to scan a QR code to complete payment when purchasing groceries at a supermarket. In this way, it is possible to clearly demonstrate how users can specifically utilize electronic payment methods.

[0065] This system makes it easier for users to understand not only the details of the service, but also how they can utilize electronic payment methods in specific everyday situations. Furthermore, because the suggestions are concrete, it is expected to promote user understanding and adoption.

[0066] The following describes the processing flow.

[0067] Step 1:

[0068] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[0069] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[0070] Step 2:

[0071] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[0072] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[0073] Step 3:

[0074] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[0075] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[0076] Step 4:

[0077] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[0078] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[0079] Step 5:

[0080] The server sends the generated list of suggested scenes to the terminal. An internet connection is required for this transmission.

[0081] Example: Send the generated list of suggested scenes to the terminal.

[0082] Step 6:

[0083] The terminal displays a list of suggested scenes received from the server on its screen. The user can review the suggested scenes through this screen.

[0084] Example: A list of suggested scenarios is displayed on the screen, and it is presented with the message, "You can use electronic payment methods like this when purchasing groceries at the supermarket."

[0085] Step 7:

[0086] If a user needs more detailed information about a specific suggested scenario, they can re-enter that information and request it from the server. This is a way to obtain additional suggestions and information.

[0087] Example: The user re-enters "detailed instructions on how to use the service when purchasing groceries at the supermarket" and sends them to the server.

[0088] Step 8:

[0089] The server generates further information based on the additional request and sends it back to the terminal.

[0090] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[0091] Step 9:

[0092] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[0093] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[0094] In this way, the system can provide users with specific and practical suggestions through multiple steps. This allows users to concretely understand how to use electronic payment methods in a way that suits their daily lives and to utilize them effectively.

[0095] (Example 1)

[0096] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0097] Conventional systems had a problem in that it was difficult for users to receive suggestions for appropriate electronic payment methods based on their specific lifestyles. As a result, users had difficulty finding the optimal electronic payment method for their own lifestyles, which hindered the promotion of electronic payment usage.

[0098] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0099] In this invention, the server includes an input means for the user to input information, a transmission means for sending information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, a means for analyzing the information generated by the generation means, a means for using a generative artificial intelligence system to generate suggestions based on the information, and a means for sending the suggestions to the user's terminal. As a result, the user can receive suggestions for the most suitable electronic payment method according to specific life situations, and it is expected that the use of electronic payment methods will be promoted.

[0100] "Input means" refers to a device or system used by a user to input information. This typically includes smartphones and tablets.

[0101] "Transmission means" refers to a device or system for transmitting information from the input means to the server. Typically, data transmission is performed via network communication.

[0102] The "generation means" is a device or system for generating information based on the information received from the transmission means. In this case, it has the function of making suggestions based on user-specified conditions using generative artificial intelligence.

[0103] "Presentation means" refers to a device or system for presenting information generated by the generation means to the user. Typically, this means provides information to the user visually through a terminal screen.

[0104] "Generative artificial intelligence" refers to systems that use artificial intelligence technology to generate information and suggestions based on user-specified conditions. It primarily includes natural language processing and machine learning algorithms.

[0105] "Analysis means" refers to a device or system for analyzing the information generated by the generation means. It performs data format verification and data analysis using an analysis algorithm.

[0106] A "suggestion" is information that indicates the optimal way to use electronic payment methods in specific everyday situations, generated based on the user's input information.

[0107] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[0108] System Configuration

[0109] 1. Input method

[0110] Users input information using their devices (smartphones or tablets). This input includes details such as the user's age and specific aspects of their daily life.

[0111] Specific example: A user uses a terminal to input information about "how people in their 30s use electronic payment methods in their daily lives."

[0112] 2. Transmission method

[0113] The terminal sends the entered information to the server via network communication. The HTTP request protocol is typically used for transmission.

[0114] Specific example: The device sends data about "how people in their 30s use electronic payment methods in their daily lives" to the server as a POST request.

[0115] 3. Generation means

[0116] The server generates appropriate suggestions based on the received information, using generative artificial intelligence (e.g., GPT-4®). This generation process utilizes natural language processing and machine learning algorithms. The server first analyzes the received data and then inputs it into the generative artificial intelligence.

[0117] Specific example: The generation AI model automatically generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0118] I use electronic payment for everyday grocery shopping.

[0119] I use electronic payment to pay at convenience stores.

[0120] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0121] 4. Presentation means

[0122] The server sends the generated suggestions back to the terminal. An HTTP request is used again for this transmission. The terminal then visually displays the received suggestions to the user.

[0123] Specific example: The application displays a list of suggestions received by the terminal from the server on the application screen, and presents to the user with a message such as, "You can use electronic payment in this way for everyday purchases at the supermarket."

[0124] Specific example

[0125] 1. Enter user information:

[0126] The user uses a terminal to input and submit information about "how people in their 30s use electronic payment methods in their daily lives."

[0127] 2. Data transmission:

[0128] The terminal sends the entered data to the server as a POST request.

[0129] 3. Information reception and analysis:

[0130] The server receives the POST request and verifies the data format (such as JSON) using a parsing tool.

[0131] 4. Proposal generation:

[0132] Using generative artificial intelligence (GPT-4), the following proposals will be automatically generated:

[0133] I use electronic payment for everyday grocery shopping.

[0134] I use electronic payment to pay at convenience stores.

[0135] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0136] 5. Submit your proposal:

[0137] The server sends the generated suggestions to the terminal in JSON format.

[0138] 6. Display of proposed content:

[0139] The device displays the suggested content received from the server on the app screen, informing the user, "You can use electronic payment in this way for everyday supermarket purchases."

[0140] Example of a prompt

[0141] "Please suggest ways in which people in their 30s use electronic payment methods in their daily lives."

[0142] This system allows users to receive suggestions for the most suitable electronic payment method tailored to their specific daily life, which is expected to promote the use of electronic payments.

[0143] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0144] Step 1:

[0145] The user enters information using a device. This information includes the user's age and details of specific daily life situations.

[0146] Input: [User information (age, details of lifestyle)]

[0147] Output: [User information entered into the terminal]

[0148] Specific action: The user enters information about "how people in their 30s use electronic payment methods in their daily lives" into an input form on their smartphone or tablet.

[0149] Step 2:

[0150] The terminal sends the entered information to the server via network communication. HTTP requests are used as the transmission protocol.

[0151] Input: [User information entered on the terminal]

[0152] Output: [User information sent to the server]

[0153] Specific operation: The terminal uses an HTTP POST request to send the entered data to the server.

[0154] Step 3:

[0155] The server analyzes the received information. It verifies the data format and uses analysis algorithms to confirm the data's content.

[0156] Input: [User information sent to the server]

[0157] Output: [Analyzed user information]

[0158] Specific operation: The server receives data in JSON format and verifies the data format. Then, it uses an analysis tool to check the contents.

[0159] Step 4:

[0160] The server generates appropriate suggestions using a generative artificial intelligence model (e.g., GPT-4) based on the analyzed information. The suggestions are automatically generated based on the user's age and lifestyle.

[0161] Input: [Analyzed user information]

[0162] Output: [Generated proposal content]

[0163] Specific operation: The server inputs the analysis results into a generative artificial intelligence model and generates suggestions such as the following:

[0164] I use electronic payment for everyday grocery shopping.

[0165] I use electronic payment to pay at convenience stores.

[0166] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0167] Step 5:

[0168] The server then sends the generated suggestions back to the terminal. The transmission protocol uses HTTP requests.

[0169] Input: [Generated proposal content]

[0170] Output: [Suggestions sent to the terminal]

[0171] Specific operation: The server sends the generated proposal to the terminal in JSON format using an HTTP POST request.

[0172] Step 6:

[0173] The terminal visually displays the suggestions received from the server to the user. The application's GUI is used for this display.

[0174] Input: [Suggestion sent to the device]

[0175] Output: [Suggestions visually displayed to the user]

[0176] Specific operation: The application screen displays the list of suggestions received by the terminal, and presents the user with the message, "You can use electronic payment in this way for everyday supermarket purchases."

[0177] Through these steps, users can receive suggestions for the most suitable electronic payment method tailored to their specific lifestyle.

[0178] (Application Example 1)

[0179] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0180] While various electronic payment methods are widespread in modern life, it can be difficult for users to choose the most suitable method for their specific needs and understand how to use it effectively. Furthermore, there are insufficient means for users to receive appropriate suggestions tailored to their age and lifestyle, preventing them from fully realizing the convenience of electronic payments.

[0181] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0182] In this invention, the server includes an input means for the user to input information about their daily life, a transmission means for sending the information from the input means to the server, a generation means for generating suggested content based on the information received from the transmission means, and a presentation means for presenting the suggested content generated by the generation means to the user. This makes it possible to provide suggestions that clearly show the user how to understand the most suitable electronic payment method for their daily life and how to use it effectively.

[0183] A "user" refers to an individual who uses the system to input information based on their own life circumstances and conditions.

[0184] "Lifestyle scene information" refers to information that shows specific scenes and situations in the user's daily life.

[0185] "Input method" refers to the interface that allows users to input information about their daily lives into the system.

[0186] "Transmission means" refers to a function for transmitting information input from the input means to the server.

[0187] "Generation means" refers to the function that generates suitable suggestions for the user using generative artificial intelligence based on the information received by the server.

[0188] "Proposed content" refers to specific recommendations regarding the optimal electronic payment method for a user's daily life, as generated by the generation method.

[0189] "Presentation means" refers to a function that displays the proposed content generated by the generation means on the user's terminal and presents it to the user.

[0190] "Generative artificial intelligence" refers to artificial intelligence technology that generates optimal suggestions based on user input.

[0191] "Electronic payment methods" refer to all payment methods that utilize digital technology.

[0192] A system for implementing this invention is built primarily using the following hardware and software.

[0193] Hardware to use

[0194] 1. Devices such as smartphones and tablets

[0195] 2. Cloud server or physical server

[0196] Software to use

[0197] 1. An application (smartphone app) for users to input information about their daily life.

[0198] 2. Network communication function for sending and receiving data

[0199] 3. Server-side software for operating generative artificial intelligence models

[0200] 4. Applications (smartphone apps) for presenting information to users.

[0201] System Operation Overview

[0202] User side

[0203] 1. Inputting information about daily life scenes:

[0204] Users use their smartphones to input information about their daily lives (e.g., grocery shopping, payments made during their commute) through the application. The application is designed to allow users to easily input information.

[0205] Transmission method

[0206] 2. Sending data:

[0207] Lifestyle information is sent to a cloud server using the smartphone's network communication function.

[0208] Server side

[0209] 3. Generating the proposal:

[0210] The cloud server uses a generative artificial intelligence model to generate the most suitable electronic payment method for the user based on the received lifestyle data. This model dynamically generates suggestions based on the input information.

[0211] For example, if you provide a scenario where "a user in their 30s buys a magazine at a train station kiosk on their way to work," the generative AI will suggest the most suitable electronic payment method for that scenario.

[0212] As a concrete example, consider the following prompt as input to a generative artificial intelligence model:

[0213] Prompt: "User information: Age 30, Lifestyle: Purchasing a magazine at a train station kiosk during commute. Please suggest an appropriate electronic payment method."

[0214] Presentation to the user

[0215] 4. Presentation of the proposal:

[0216] The generated suggestions are sent back to the smartphone from the cloud server and presented through the user's application. Users can review the specific suggestions and understand how they should utilize electronic payment methods in their daily lives.

[0217] This system enhances user convenience and contributes to the widespread adoption of electronic payments by dynamically suggesting electronic payment methods based on information entered by the user. The problem-solving means provided by the invention are realized through the specific operation flow described above.

[0218] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0219] Step 1:

[0220] The user opens the smartphone application and enters information about their age and daily life. For example, the user might enter information such as "in their 30s, buys a magazine at a station kiosk on their way to work." The entered information is then structured by the application as JSON data.

[0221] Step 2:

[0222] The device (smartphone) sends structured JSON data to a cloud server. This data is securely transmitted using network communication (e.g., the HTTPS protocol). It receives data containing age and lifestyle information as input and sends it to the cloud server as output.

[0223] Step 3:

[0224] The server parses the received JSON data and extracts the necessary information. Specifically, it stores the user's age and lifestyle information in a database and generates prompts to input into a generative artificial intelligence model. For example, it might generate a prompt like, "User information: Age 30, Lifestyle: Buying a magazine at a station kiosk on the way to work. Please suggest an appropriate electronic payment method."

[0225] Step 4:

[0226] A generative artificial intelligence model is input with prompt text, and it generates suggestions for the most suitable electronic payment method for the user. Using the generated prompt text as input, the AI ​​model performs data calculations and outputs suggestions, including electronic payment methods, that are appropriate for the user's lifestyle.

[0227] Step 5:

[0228] The server converts the generated suggestions back into JSON format and sends them to the user's smartphone over the network. It receives output data from the AI ​​model as input and converts it into an appropriate data format for sending to the smartphone as output.

[0229] Step 6:

[0230] The terminal displays suggestions received from the server via an application. For example, a specific suggestion such as, "When purchasing magazines at a station kiosk on your commute, QR code payment is convenient," might be displayed on the screen. This allows users to intuitively understand how to utilize electronic payment methods in their daily lives.

[0231] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0232] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function where the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user. Furthermore, the system incorporates an emotion engine to recognize the user's emotions and adds a function to adjust the suggestions according to the user's feelings.

[0233] System Configuration

[0234] 1. Input method

[0235] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[0236] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[0237] 2. Transmission method

[0238] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[0239] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[0240] 3. Generation means

[0241] The server uses generative artificial intelligence (AI) to generate appropriate suggestions based on the received information. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[0242] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0243] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[0244] Use electronic payment methods when making small purchases at convenience stores.

[0245] I use electronic payment methods for regular tea and cafe visits.

[0246] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[0247] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[0248] 4. Emotional Engine

[0249] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice, facial expressions, and physiological data to recognize emotions.

[0250] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[0251] 5. Emotion-based adjustment

[0252] The server modifies the tone and expression of suggestions based on the user's emotions as recognized by the emotion engine. For example, if the user is interested, it will provide detailed and proactive suggestions, while if they are confused, it will provide simpler and easier-to-understand suggestions.

[0253] Example: If you recognize that the user is confused, briefly explain "the procedure for purchasing groceries at a supermarket."

[0254] 6. Presentation means

[0255] The server sends information to the terminal, adjusted based on the generated suggested scenes and emotions, and the terminal presents this information to the user. The user can then view the specific suggestions on the screen.

[0256] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[0257] Specific example

[0258] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[0259] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[0260] 2. Use electronic payment methods when making small purchases at convenience stores.

[0261] 3. Use electronic payment methods for regular tea or cafe visits.

[0262] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[0263] Simultaneously, the emotion engine analyzes the user's reactions, reading their emotions from their facial expressions and voice. For example, if the user indicates "confusion," the server adjusts the suggestions to make them clearer and more concise. Finally, the device displays these suggestions on the screen, presenting them in a format that is easy for the user to understand.

[0264] In this way, users can more easily understand how to use electronic payment methods in relation to specific everyday situations, and further promotion of their use can be expected through adjustments based on their emotions.

[0265] The following describes the processing flow.

[0266] Step 1:

[0267] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[0268] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[0269] Step 2:

[0270] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[0271] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[0272] Step 3:

[0273] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[0274] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[0275] Step 4:

[0276] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[0277] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[0278] Step 5:

[0279] During the process of generating suggested scenes, the server uses an emotion engine to recognize the user's emotions. The emotion engine recognizes emotions by analyzing the user's voice, facial expressions, and physiological data.

[0280] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[0281] Step 6:

[0282] The server adjusts the proposed content based on the emotions recognized by the emotion engine. For example, if the user shows interest, detailed and positive proposals are made, and if the user is confused, the proposals are changed to simpler and more understandable ones.

[0283] Example: If it is recognized that the user is confused, it is adjusted to content that briefly explains "the procedure for purchasing food ingredients at the supermarket".

[0284] Step 7:

[0285] The server transmits the proposed scene list generated by the server and the information adjusted based on the emotions to the terminal. The Internet connection is used for transmission.

[0286] Example: The generated proposed scene list is transmitted to the terminal.

[0287] Step 8:

[0288] The terminal displays the proposed scene list received from the server on the screen. The user can check the proposed content through this screen.

[0289] Example: The proposed scene list is displayed on the screen, presenting "You can use electronic payment methods like this when purchasing food ingredients at your daily supermarket".

[0290] Step 9:

[0291] If the user needs more detailed information about a specific proposed scene, the user can re-enter the information and request it from the server. This is a means to obtain additional proposals and information.

[0292] Example: The user re-enters "detailed usage method when purchasing food ingredients at the supermarket" and transmits it to the server.

[0293] Step 10:

[0294] The server generates further information based on the additional request and sends it back to the terminal.

[0295] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[0296] Step 11:

[0297] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[0298] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[0299] In this way, the system can provide users with specific and practical suggestions through multiple steps. By utilizing the emotion engine, optimal suggestions are made according to the user's emotions, which is expected to further promote its use.

[0300] (Example 2)

[0301] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0302] Conventional suggestion systems have struggled to flexibly provide electronic payment methods suited to users' emotions and specific life situations. Furthermore, they lacked adjustments to account for diverse user emotional states, resulting in a uniform and inefficient user experience. Additionally, suggestions based on pre-set templates were insufficient to meet individual user needs.

[0303] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting the information from the input means, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the emotion of the user, and an adjustment means for adjusting the information based on the emotion recognized by the emotion recognition means. Thereby, it becomes possible to make a flexible proposal according to the individual needs of the user, and by further adjusting the proposal content according to the emotional state of the user, it becomes possible to provide a more personalized and efficient user experience.

[0304] The "input means" is a device or interface used by the user to input their own information or requests.

[0305] The "transmission means" is a device or protocol having a communication function for transmitting the information obtained from the input means to the server.

[0306] The "generation means" is a function or system for generating appropriate proposals or information using a generation AI model based on the information received by the server.

[0307] The "presentation means" is a device or interface for visually or audibly presenting the information generated by the generation means to the user.

[0308] The "emotion recognition means" is a system or algorithm for analyzing data such as the user's expression and voice to recognize the emotional state of the user.

[0309] The "adjustment means" is a function or system for adjusting the generated proposal content based on the emotion of the user recognized by the emotion recognition means.

[0310] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system is composed of a combination of multiple hardware and software elements.

[0311] First, the user inputs information using an input device. A smartphone or tablet is preferred as the input device. For example, the user might input information such as "How people in their 30s use electronic payment methods in their daily lives." In this case, text input can be done using the device's touchscreen.

[0312] Next, the terminal uses a transmission method to send the information entered by the user to the server. This transmission utilizes network communication, and typically, data is sent to the server using an HTTP POST request. The transmitted data is in a common data format such as JSON.

[0313] The server generates suggestions based on the information received using a generation mechanism. The generation mechanism utilizes a generative AI model, such as OpenAI's GPT-4. The server generates specific electronic payment scenarios based on the conditions entered by the user. Examples of generated suggestions include:

[0314] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[0315] Use electronic payment methods when making small purchases at convenience stores.

[0316] I use electronic payment methods for regular tea and cafe visits.

[0317] Furthermore, the server uses emotion recognition tools to recognize the user's emotions. This utilizes emotion recognition engines such as Microsoft® Azure® Cognitive Services and Google® Cloud Vision. These engines analyze data acquired from the camera and microphone to determine emotions such as "interest," "dissatisfaction," and "confusion" from the user's facial expressions and voice tone.

[0318] Based on the emotions determined by the emotion recognition system, the server adjusts the suggested content using an adjustment system. For example, if the user is confused, the suggested content is adjusted to be more concise and easier to understand. This adjustment improves the likelihood of the suggested content being accepted.

[0319] Finally, the terminal uses a presentation mechanism to display the adjusted suggestions to the user. The suggestions are displayed on the terminal screen, and the user can review and use them.

[0320] Examples of specific prompt messages include the following:

[0321] "Please generate suggestions for specific ways in which people in their 30s use electronic payment methods in their daily lives. Consider the following scenarios: buying groceries at a supermarket, shopping at a convenience store, and paying at a cafe. If the user is confused, please provide a brief explanation."

[0322] Thus, this invention proposes an electronic payment method suitable for the user's specific daily life scenarios and can be further adjusted according to the user's emotional state. This can improve the user experience.

[0323] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0324] Step 1:

[0325] The user inputs information using a device. The user uses input devices such as smartphones or tablets to input information such as their age, lifestyle, and various other conditions in text format. This input information becomes data transmitted to the server via the device's transmission mechanism.

[0326] Specific actions:

[0327] The user enters text into an input form displayed on the device screen.

[0328] The user confirms the information by pressing the "Submit" button.

[0329] Input: Detailed information about the user's age and lifestyle.

[0330] Output: Text data entered into the terminal

[0331] Step 2:

[0332] The terminal sends information entered by the user to the server. The terminal sends data to the server via the network using a transmission method.

[0333] Specific actions:

[0334] The terminal converts the entered text data into JSON format or another format.

[0335] The device sends data to the server using an HTTP POST request.

[0336] Input: Text data of user information entered in the input form.

[0337] Output: User information in JSON format sent to the server

[0338] Step 3:

[0339] Based on the data received by the server, an AI model is used to generate appropriate suggestions. The server generates prompt sentences based on the user's age and lifestyle, and inputs them into the AI ​​model.

[0340] Specific actions:

[0341] The server generates prompt messages based on the user's age and lifestyle.

[0342] The server sends a prompt message to the AI ​​model that generates the response, and receives the generated response.

[0343] Input: User information in JSON format received by the server

[0344] Output: Text data of the proposed content generated based on the generative AI model.

[0345] Step 4:

[0346] The server uses an emotion recognition engine to recognize the user's emotions. The emotion recognition means analyzes audio and video data acquired from the camera and microphone to determine the user's emotional state.

[0347] Specific actions:

[0348] The server acquires the user's facial expressions and voice data through the camera and microphone.

[0349] The server uses an emotion recognition algorithm to determine the emotional state (e.g., "interested," "dissatisfied," "confused").

[0350] Input: User's facial expressions and voice data obtained from the device.

[0351] Output: Analyzed user emotional state data

[0352] Step 5:

[0353] The server adjusts the suggestions based on the recognized emotions. The adjustment mechanism changes the tone of the suggestions and reconstructs the information according to the user's emotional state.

[0354] Specific actions:

[0355] The server analyzes the user's emotional state data and regenerates the suggested content as needed.

[0356] If it is determined that the person is confused, the proposal will be changed to a simpler and easier-to-understand format.

[0357] Input: Generated suggestions, analyzed user emotional state data

[0358] Output: Text data of the adjusted proposal.

[0359] Step 6:

[0360] The server sends the adjusted proposal to the terminal, and the terminal presents it to the user. The adjusted proposal is displayed on the screen using the presentation method.

[0361] Specific actions:

[0362] The server sends the adjusted proposal to the terminal.

[0363] The device displays the data it has received and presents it to the user.

[0364] Input: Adjusted proposal sent from the server

[0365] Output: Screen display of the suggested content presented to the user.

[0366] The above outlines the specific processing flow of this system's program. This allows users to receive suggestions for electronic payment methods suitable for their lifestyle, and these suggestions are adjusted according to the user's feelings, enabling more appropriate and effective use.

[0367] (Application Example 2)

[0368] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0369] In modern society, users increasingly rely on electronic payment methods in various aspects of their daily lives. However, systems that automatically provide suggestions tailored to the user's age and lifestyle are not yet widespread, often leading to confusion in actual use. Furthermore, there is a lack of consideration for user emotions in the approach to suggesting electronic payment methods, resulting in a lack of suggestions that users find satisfactory.

[0370] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for the user to input information, a transmission means for sending the information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the user's emotions, and an adjustment means for adjusting the format of information representation based on the emotions recognized by the emotion recognition means. As a result, the user can receive suggestions for electronic payment methods that are suitable for them, and furthermore, because adjustments are made according to the user's emotions, they can receive suggestions that are more intuitive and convincing.

[0371] An "input method" is a means by which a user can input information such as their age and details of their lifestyle.

[0372] "Transmission means" refers to means for transmitting information obtained from the input means to the server.

[0373] "Generation means" refers to means for generating information using generative artificial intelligence based on information received from the transmission means.

[0374] "Presentation means" refers to means for presenting the information generated by the generation means to the user.

[0375] "Emotion recognition means" are methods for recognizing a user's emotions, and involve analyzing facial expressions, voice tone, and physiological data using cameras and microphones.

[0376] "Adjustment means" refers to means for adjusting the expression format and tone of information based on the emotions recognized by the emotion recognition means.

[0377] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. To realize this system, a program configured as follows is required.

[0378] The system includes input means, transmission means, generation means, presentation means, emotion recognition means, and adjustment means.

[0379] 1. Input method

[0380] Users enter details about their age and lifestyle using devices such as smartphones and tablets. This information is registered in the system as a user profile.

[0381] 2. Transmission method

[0382] The entered user information is transmitted to the server via network communication. Here, the data entered by the user is encrypted and transmitted securely.

[0383] 3. Generation means

[0384] The server uses generative artificial intelligence (generative AI model) based on the received user information to generate suggestions for the most suitable electronic payment method. This generative AI model has the ability to automatically generate suggestions tailored to the user's age and lifestyle. Furthermore, the suggestions are easy for the user to understand and are relevant to specific daily life situations.

[0385] 4. Emotion recognition means

[0386] In addition to user input, the system monitors the user's facial expressions and voice using a camera and microphone, and analyzes the user's emotions using an emotion engine. This analysis data is then sent to a server.

[0387] 5. Adjustment means

[0388] The server adjusts the tone and expression of the generated suggestions based on the emotion data obtained from the emotion recognition system. For example, if the server recognizes that the user is confused, the suggestions will be made simpler and more specific.

[0389] 6. Presentation means

[0390] Finally, the adjusted proposal is sent back to the user's device and displayed on the screen. The user can then see this and understand how to utilize electronic payment methods in specific scenarios.

[0391] Specific example

[0392] This system considers the scenario where a businessman in his 30s wants to know how to use electronic payment methods at a train station kiosk during his commute. First, the user uses a terminal to input information about his age and specific daily life.

[0393] Please begin entering your user information. Enter your age, and then provide detailed information about how you use electronic payment methods in specific daily life situations. For example, "As a businessman in his 30s, how do I use electronic payment methods at a train station kiosk during my commute?"

[0394] Next, the server uses generative artificial intelligence to generate suggestions. For example, these might include "a method of electronic payment using a QR code when purchasing magazines at a train station kiosk" or "an electronic payment method that can be used for regular beverage purchases."

[0395] Simultaneously, emotion recognition analyzes the user's facial expressions and voice, and if the user appears confused, adjusts the suggestions to be clearer and more concise. Finally, the adjusted suggestions are displayed on the user's device, allowing the user to understand how to effectively use electronic payment methods in specific scenarios.

[0396] In this way, users can receive suggestions for the most suitable electronic payment method tailored to their lifestyle, and because these suggestions are adjusted based on the user's feelings, they become easier to understand.

[0397] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0398] Step 1:

[0399] The user enters information using a terminal.

[0400] Input: The user enters details such as age and lifestyle (e.g., a businessman in his 30s wants to know "how to use electronic payment methods at a train station kiosk during his commute").

[0401] Processing: The terminal collects the input data and formats it for transmission to the server.

[0402] Output: Formatted user information is generated and ready for transmission.

[0403] Step 2:

[0404] The device sends user information to the server.

[0405] Input: Formalized user information.

[0406] Processing: The terminal encrypts information over the network and securely transmits it to the server.

[0407] Output: The server receives encrypted user information and decrypts it.

[0408] Step 3:

[0409] The server uses generative artificial intelligence to generate proposals.

[0410] Input: Decoded user information (e.g., a businessman in his 30s, and his electronic payment method at a train station kiosk during his commute).

[0411] Processing: The AI ​​model on the server generates suggestions for the most suitable electronic payment method based on user information.

[0412] Output: Specific suggestions (e.g., how to purchase magazines at station kiosks using QR codes) are generated.

[0413] Step 4:

[0414] The server uses emotion recognition means to recognize the user's emotions.

[0415] Input: User voice and facial expression data obtained using a camera and microphone.

[0416] Processing: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state (e.g., interest, confusion).

[0417] Output: Emotion recognition results are generated.

[0418] Step 5:

[0419] The server adjusts the tone and expression of the suggestions based on the emotions it recognizes.

[0420] Input: Generated suggestions and sentiment recognition results.

[0421] Processing: The server adjusts the proposed content to be clear and concise based on the emotion recognition result (e.g., confusion).

[0422] Output: A revised proposal (e.g., a QR code payment method with detailed steps) is generated.

[0423] Step 6:

[0424] The server sends the adjusted proposal to the terminal.

[0425] Input: Adjusted proposal content.

[0426] Processing: The server encrypts the adjusted proposal and sends it to the terminal over the network.

[0427] Output: The terminal securely receives and decodes the adjusted proposal.

[0428] Step 7:

[0429] The device presents suggestions to the user.

[0430] Input: Decoded and adjusted proposal content.

[0431] Processing: The terminal displays the suggested content and presents it in a way that is easy for the user to understand.

[0432] Output: Users can view and actually use electronic payment methods in specific everyday situations through the screen.

[0433] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0434] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0435] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0436] [Second Embodiment]

[0437] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0438] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0439] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0440] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0441] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0442] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0443] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0444] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0445] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0446] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0447] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0448] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0449] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[0450] System Configuration

[0451] 1. Input method

[0452] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[0453] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[0454] 2. Transmission method

[0455] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[0456] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[0457] 3. Generation means

[0458] The server uses generative artificial intelligence (AI) based on the received information to generate appropriate suggestions. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[0459] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0460] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[0461] Use electronic payment methods when making small purchases at convenience stores.

[0462] I use electronic payment methods for regular tea and cafe visits.

[0463] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[0464] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[0465] 4. Presentation means

[0466] The server sends the generated suggestions back to the terminal, which then presents the information to the user. The user can then view the specific suggestions on the screen.

[0467] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[0468] Specific example

[0469] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[0470] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[0471] 2. Use electronic payment methods when making small purchases at convenience stores.

[0472] 3. Use electronic payment methods for regular tea or cafe visits.

[0473] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[0474] Users can review these specific suggestions and understand, for example, how to scan a QR code and complete payment when purchasing groceries at a supermarket. In this way, it becomes clear how users can specifically utilize electronic payment methods.

[0475] This system makes it easier for users to understand not only the details of the service, but also how they can utilize electronic payment methods in specific everyday situations. Furthermore, because the suggestions are concrete, it is expected to promote user understanding and adoption.

[0476] The following describes the processing flow.

[0477] Step 1:

[0478] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[0479] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[0480] Step 2:

[0481] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[0482] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[0483] Step 3:

[0484] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[0485] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[0486] Step 4:

[0487] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[0488] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[0489] Step 5:

[0490] The server sends the generated list of suggested scenes to the terminal. An internet connection is required for this transmission.

[0491] Example: Send the generated list of suggested scenes to the terminal.

[0492] Step 6:

[0493] The terminal displays a list of suggested scenes received from the server on its screen. The user can review the suggested scenes through this screen.

[0494] Example: A list of suggested scenarios is displayed on the screen, and it is presented with the message, "You can use electronic payment methods like this when purchasing groceries at the supermarket."

[0495] Step 7:

[0496] If a user needs more detailed information about a specific suggested scenario, they can re-enter that information and request it from the server. This is a way to obtain additional suggestions and information.

[0497] Example: The user re-enters "detailed instructions on how to use the service when purchasing groceries at the supermarket" and sends them to the server.

[0498] Step 8:

[0499] The server generates further information based on the additional request and sends it back to the terminal.

[0500] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[0501] Step 9:

[0502] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[0503] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[0504] In this way, the system can provide users with specific and practical suggestions through multiple steps. This allows users to concretely understand how to use electronic payment methods in a way that suits their daily lives and to utilize them effectively.

[0505] (Example 1)

[0506] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0507] Conventional systems had a problem in that it was difficult for users to receive suggestions for appropriate electronic payment methods based on their specific lifestyles. As a result, users had difficulty finding the optimal electronic payment method for their own lifestyles, which hindered the promotion of electronic payment usage.

[0508] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0509] In this invention, the server includes an input means for the user to input information, a transmission means for sending information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, a means for analyzing the information generated by the generation means, a means for using a generative artificial intelligence system to generate suggestions based on the information, and a means for sending the suggestions to the user's terminal. As a result, the user can receive suggestions for the most suitable electronic payment method according to specific life situations, and it is expected that the use of electronic payment methods will be promoted.

[0510] "Input means" refers to a device or system used by a user to input information. This typically includes smartphones and tablets.

[0511] "Transmission means" refers to a device or system for transmitting information from the input means to the server. Typically, data transmission is performed via network communication.

[0512] The "generation means" is a device or system for generating information based on the information received from the transmission means. In this case, it has the function of making suggestions based on user-specified conditions using generative artificial intelligence.

[0513] "Presentation means" refers to a device or system for presenting information generated by the generation means to the user. Typically, this means provides information to the user visually through a terminal screen.

[0514] "Generative artificial intelligence" refers to systems that use artificial intelligence technology to generate information and suggestions based on user-specified conditions. It primarily includes natural language processing and machine learning algorithms.

[0515] "Analysis means" refers to a device or system for analyzing the information generated by the generation means. It performs data format verification and data analysis using an analysis algorithm.

[0516] A "suggestion" is information that indicates the optimal way to use electronic payment methods in specific everyday situations, generated based on the user's input information.

[0517] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[0518] System Configuration

[0519] 1. Input method

[0520] Users input information using their devices (smartphones or tablets). This input includes details such as the user's age and specific aspects of their daily life.

[0521] Specific example: A user uses a terminal to input information about "how people in their 30s use electronic payment methods in their daily lives."

[0522] 2. Transmission method

[0523] The terminal sends the entered information to the server via network communication. The HTTP request protocol is typically used for transmission.

[0524] Specific example: The device sends data about "how people in their 30s use electronic payment methods in their daily lives" to the server as a POST request.

[0525] 3. Generation means

[0526] The server generates appropriate suggestions using generative artificial intelligence (e.g., GPT-4) based on the received information. This generation process utilizes natural language processing and machine learning algorithms. The server first analyzes the received data and then inputs it into the generative artificial intelligence.

[0527] Specific example: The generation AI model automatically generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0528] I use electronic payment for everyday grocery shopping.

[0529] I use electronic payment to pay at convenience stores.

[0530] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0531] 4. Presentation means

[0532] The server sends the generated suggestions back to the terminal. An HTTP request is used again for this transmission. The terminal then visually displays the received suggestions to the user.

[0533] Specific example: The application displays a list of suggestions received by the terminal from the server on the application screen, and presents to the user with a message such as, "You can use electronic payment in this way for everyday purchases at the supermarket."

[0534] Specific example

[0535] 1. Enter user information:

[0536] The user uses a terminal to input and submit information about "how people in their 30s use electronic payment methods in their daily lives."

[0537] 2. Data transmission:

[0538] The terminal sends the entered data to the server as a POST request.

[0539] 3. Information reception and analysis:

[0540] The server receives the POST request and verifies the data format (such as JSON) using a parsing tool.

[0541] 4. Proposal generation:

[0542] Using generative artificial intelligence (GPT-4), the following proposals will be automatically generated:

[0543] I use electronic payment for everyday grocery shopping.

[0544] I use electronic payment to pay at convenience stores.

[0545] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0546] 5. Submit your proposal:

[0547] The server sends the generated suggestions to the terminal in JSON format.

[0548] 6. Display of proposed content:

[0549] The device displays the suggested content received from the server on the app screen, informing the user, "You can use electronic payment in this way for everyday supermarket purchases."

[0550] Example of a prompt

[0551] "Please suggest ways in which people in their 30s use electronic payment methods in their daily lives."

[0552] This system allows users to receive suggestions for the most suitable electronic payment method tailored to their specific daily life, which is expected to promote the use of electronic payments.

[0553] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0554] Step 1:

[0555] The user enters information using a device. This information includes the user's age and details of specific daily life situations.

[0556] Input: [User information (age, details of lifestyle)]

[0557] Output: [User information entered into the terminal]

[0558] Specific action: The user enters information about "how people in their 30s use electronic payment methods in their daily lives" into an input form on their smartphone or tablet.

[0559] Step 2:

[0560] The terminal sends the entered information to the server via network communication. HTTP requests are used as the transmission protocol.

[0561] Input: [User information entered on the terminal]

[0562] Output: [User information sent to the server]

[0563] Specific operation: The terminal uses an HTTP POST request to send the entered data to the server.

[0564] Step 3:

[0565] The server analyzes the received information. It verifies the data format and uses analysis algorithms to confirm the data's content.

[0566] Input: [User information sent to the server]

[0567] Output: [Analyzed user information]

[0568] Specific operation: The server receives data in JSON format and verifies the data format. Then, it uses an analysis tool to check the contents.

[0569] Step 4:

[0570] The server generates appropriate suggestions using a generative artificial intelligence model (e.g., GPT-4) based on the analyzed information. The suggestions are automatically generated based on the user's age and lifestyle.

[0571] Input: [Analyzed user information]

[0572] Output: [Generated proposal content]

[0573] Specific operation: The server inputs the analysis results into a generative artificial intelligence model and generates suggestions such as the following:

[0574] I use electronic payment for everyday grocery shopping.

[0575] I use electronic payment to pay at convenience stores.

[0576] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0577] Step 5:

[0578] The server then sends the generated suggestions back to the terminal. The transmission protocol uses HTTP requests.

[0579] Input: [Generated proposal content]

[0580] Output: [Suggestions sent to the terminal]

[0581] Specific operation: The server sends the generated proposal to the terminal in JSON format using an HTTP POST request.

[0582] Step 6:

[0583] The terminal visually displays the suggestions received from the server to the user. The application's GUI is used for this display.

[0584] Input: [Suggestion sent to the device]

[0585] Output: [Suggestions displayed visually to the user]

[0586] Specific operation: The application screen displays the list of suggestions received by the terminal, and the user is shown, "You can use electronic payment in this way for everyday supermarket purchases."

[0587] Through these steps, users can receive suggestions for the most suitable electronic payment method tailored to their specific lifestyle.

[0588] (Application Example 1)

[0589] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0590] While various electronic payment methods are widespread in modern life, it can be difficult for users to choose the most suitable method for their specific needs and understand how to use it effectively. Furthermore, there are insufficient means for users to receive appropriate suggestions tailored to their age and lifestyle, preventing them from fully realizing the convenience of electronic payments.

[0591] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0592] In this invention, the server includes an input means for the user to input information about their daily life, a transmission means for sending the information from the input means to the server, a generation means for generating suggested content based on the information received from the transmission means, and a presentation means for presenting the suggested content generated by the generation means to the user. This makes it possible to provide suggestions that clearly show the user how to understand the most suitable electronic payment method for their daily life and how to use it effectively.

[0593] A "user" refers to an individual who uses the system to input information based on their own life circumstances and conditions.

[0594] "Lifestyle scene information" refers to information that shows specific scenes and situations in the user's daily life.

[0595] "Input method" refers to the interface that allows users to input information about their daily lives into the system.

[0596] "Transmission means" refers to a function for transmitting information input from the input means to the server.

[0597] "Generation means" refers to the function that generates suitable suggestions for the user using generative artificial intelligence based on the information received by the server.

[0598] "Proposed content" refers to specific recommendations regarding the optimal electronic payment method for a user's daily life, as generated by the generation method.

[0599] "Presentation means" refers to a function that displays the proposed content generated by the generation means on the user's terminal and presents it to the user.

[0600] "Generative artificial intelligence" refers to artificial intelligence technology that generates optimal suggestions based on user input.

[0601] "Electronic payment methods" refer to all payment methods that utilize digital technology.

[0602] A system for implementing this invention is built primarily using the following hardware and software.

[0603] Hardware to use

[0604] 1. Devices such as smartphones and tablets

[0605] 2. Cloud server or physical server

[0606] Software to use

[0607] 1. An application (smartphone app) for users to input information about their daily life.

[0608] 2. Network communication function for sending and receiving data

[0609] 3. Server-side software for operating generative artificial intelligence models

[0610] 4. Applications (smartphone apps) for presenting information to users.

[0611] System Operation Overview

[0612] User side

[0613] 1. Inputting information about daily life scenes:

[0614] Users use their smartphones to input information about their daily lives (e.g., grocery shopping, payments made during their commute) through the application. The application is designed to allow users to easily input information.

[0615] Transmission method

[0616] 2. Sending data:

[0617] Lifestyle information is sent to a cloud server using the smartphone's network communication function.

[0618] Server side

[0619] 3. Generating the proposal:

[0620] The cloud server uses a generative artificial intelligence model to generate the most suitable electronic payment method for the user based on the received lifestyle data. This model dynamically generates suggestions based on the input information.

[0621] For example, if you provide a scenario where "a user in their 30s buys a magazine at a train station kiosk on their way to work," the generative AI will suggest the most suitable electronic payment method for that scenario.

[0622] As a concrete example, consider the following prompt as input to a generative artificial intelligence model:

[0623] Prompt: "User information: Age 30, Lifestyle: Purchasing a magazine at a train station kiosk during commute. Please suggest an appropriate electronic payment method."

[0624] Presentation to the user

[0625] 4. Presentation of the proposal:

[0626] The generated suggestions are sent back to the smartphone from the cloud server and presented through the user's application. Users can review the specific suggestions and understand how they should utilize electronic payment methods in their daily lives.

[0627] This system enhances user convenience and contributes to the widespread adoption of electronic payments by dynamically suggesting electronic payment methods based on information entered by the user. The problem-solving means provided by the invention are realized through the specific operation flow described above.

[0628] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0629] Step 1:

[0630] The user opens the smartphone application and enters information about their age and daily life. For example, the user might enter information such as "in their 30s, buys a magazine at a station kiosk on their way to work." The entered information is then structured by the application as JSON data.

[0631] Step 2:

[0632] The device (smartphone) sends structured JSON data to a cloud server. This data is securely transmitted using network communication (e.g., the HTTPS protocol). It receives data containing age and lifestyle information as input and sends it to the cloud server as output.

[0633] Step 3:

[0634] The server parses the received JSON data and extracts the necessary information. Specifically, it stores the user's age and lifestyle information in a database and generates prompts to input into a generative artificial intelligence model. For example, it might generate a prompt like, "User information: Age 30, Lifestyle: Buying a magazine at a station kiosk on the way to work. Please suggest an appropriate electronic payment method."

[0635] Step 4:

[0636] A generative artificial intelligence model is input with prompt text, and it generates suggestions for the most suitable electronic payment method for the user. Using the generated prompt text as input, the AI ​​model performs data calculations and outputs suggestions, including electronic payment methods, that are appropriate for the user's lifestyle.

[0637] Step 5:

[0638] The server converts the generated suggestions back into JSON format and sends them to the user's smartphone over the network. It receives output data from the AI ​​model as input and converts it into an appropriate data format for sending to the smartphone as output.

[0639] Step 6:

[0640] The terminal displays suggestions received from the server via an application. For example, a specific suggestion such as, "When purchasing magazines at a station kiosk on your commute, QR code payment is convenient," might be displayed on the screen. This allows users to intuitively understand how to utilize electronic payment methods in their daily lives.

[0641] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0642] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function where the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user. Furthermore, the system incorporates an emotion engine to recognize the user's emotions and adds a function to adjust the suggestions according to the user's feelings.

[0643] System Configuration

[0644] 1. Input method

[0645] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[0646] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[0647] 2. Transmission method

[0648] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[0649] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[0650] 3. Generation means

[0651] The server uses generative artificial intelligence (AI) based on the received information to generate appropriate suggestions. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[0652] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0653] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[0654] Use electronic payment methods when making small purchases at convenience stores.

[0655] I use electronic payment methods for regular tea and cafe visits.

[0656] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[0657] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[0658] 4. Emotional Engine

[0659] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice, facial expressions, and physiological data to recognize emotions.

[0660] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[0661] 5. Emotion-based adjustment

[0662] The server modifies the tone and expression of suggestions based on the user's emotions as recognized by the emotion engine. For example, if the user is interested, it will provide detailed and proactive suggestions, while if they are confused, it will provide simpler and easier-to-understand suggestions.

[0663] Example: If you recognize that the user is confused, briefly explain "the procedure for purchasing groceries at a supermarket."

[0664] 6. Presentation means

[0665] The server sends information to the terminal, adjusted based on the generated suggested scenes and emotions, and the terminal presents this information to the user. The user can then view the specific suggestions on the screen.

[0666] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[0667] Specific example

[0668] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[0669] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[0670] 2. Use electronic payment methods when making small purchases at convenience stores.

[0671] 3. Use electronic payment methods for regular tea or cafe visits.

[0672] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[0673] Simultaneously, the emotion engine analyzes the user's reactions, reading their emotions from their facial expressions and voice. For example, if the user indicates "confusion," the server adjusts the suggestions to make them clearer and more concise. Finally, the device displays these suggestions on the screen, presenting them in a format that is easy for the user to understand.

[0674] In this way, users can more easily understand how to use electronic payment methods in relation to specific everyday situations, and further promotion of their use can be expected through adjustments based on their emotions.

[0675] The following describes the processing flow.

[0676] Step 1:

[0677] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[0678] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[0679] Step 2:

[0680] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[0681] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[0682] Step 3:

[0683] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[0684] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[0685] Step 4:

[0686] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[0687] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[0688] Step 5:

[0689] During the process of generating suggested scenes, the server uses an emotion engine to recognize the user's emotions. The emotion engine recognizes emotions by analyzing the user's voice, facial expressions, and physiological data.

[0690] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[0691] Step 6:

[0692] The server adjusts its suggestions based on the emotions recognized by the emotion engine. For example, if the user shows interest, it provides detailed and proactive suggestions; if they are confused, it changes to simpler and easier-to-understand suggestions.

[0693] For example, if it is recognized that the user is confused, the content will be adjusted to briefly explain "the procedure for purchasing groceries at a supermarket."

[0694] Step 7:

[0695] The server sends the generated list of suggested scenes and information adjusted based on emotions to the terminal. An internet connection is required for transmission.

[0696] Example: Send the generated list of suggested scenes to the terminal.

[0697] Step 8:

[0698] The terminal displays a list of suggested scenes received from the server on its screen. The user can review the suggested scenes through this screen.

[0699] Example: A list of suggested scenarios is displayed on the screen, and it is presented with the message, "You can use electronic payment methods like this when purchasing groceries at the supermarket on a daily basis."

[0700] Step 9:

[0701] If a user needs more detailed information about a specific suggested scenario, they can re-enter that information and request it from the server. This is a way to obtain additional suggestions and information.

[0702] Example: The user re-enters "detailed instructions on how to use the service when purchasing groceries at the supermarket" and sends them to the server.

[0703] Step 10:

[0704] The server generates further information based on the additional request and sends it back to the terminal.

[0705] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[0706] Step 11:

[0707] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[0708] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[0709] In this way, the system can provide users with specific and practical suggestions through multiple steps. By utilizing the emotion engine, optimal suggestions are made according to the user's emotions, which is expected to further promote its use.

[0710] (Example 2)

[0711] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0712] Conventional suggestion systems have struggled to flexibly provide electronic payment methods suited to users' emotions and specific life situations. Furthermore, they lacked adjustments to account for diverse user emotional states, resulting in a uniform and inefficient user experience. Additionally, suggestions based on pre-set templates were insufficient to meet individual user needs.

[0713] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting information from the input means, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the user's emotions, and an adjustment means for adjusting the information based on the emotions recognized by the emotion recognition means. This enables flexible suggestions tailored to the individual needs of the user, and further, by adjusting the content of the suggestions according to the user's emotional state, it becomes possible to provide a more personalized and efficient user experience.

[0714] "Input means" refers to a device or interface used by a user to input their own information or requests.

[0715] "Transmission means" refers to a device or protocol that has a communication function for transmitting information obtained from input means to a server.

[0716] "Generation means" refers to a function or system that uses a generation AI model to generate appropriate suggestions or information based on the information received by the server.

[0717] "Presentation means" refers to a device or interface for presenting information generated by a generation means to a user visually or audibly.

[0718] An "emotion recognition tool" is a system or algorithm that analyzes data such as a user's facial expressions and voice to recognize the user's emotional state.

[0719] "Adjustment means" refers to a function or system for adjusting the generated suggestion content based on the user's emotions recognized by the emotion recognition means.

[0720] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system is composed of a combination of multiple hardware and software elements.

[0721] First, the user inputs information using an input device. A smartphone or tablet is preferred as the input device. For example, the user might input information such as "How people in their 30s use electronic payment methods in their daily lives." In this case, text input can be done using the device's touchscreen.

[0722] Next, the terminal uses a transmission method to send the information entered by the user to the server. This transmission utilizes network communication, and typically, data is sent to the server using an HTTP POST request. The transmitted data is in a common data format such as JSON.

[0723] The server generates suggestions based on the information received using a generation mechanism. The generation mechanism utilizes a generative AI model, such as OpenAI's GPT-4. The server generates specific electronic payment scenarios based on the conditions entered by the user. Examples of generated suggestions include:

[0724] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[0725] Use electronic payment methods when making small purchases at convenience stores.

[0726] I use electronic payment methods for regular tea and cafe visits.

[0727] Furthermore, the server uses emotion recognition tools to recognize the user's emotions. This utilizes emotion recognition engines such as Microsoft Azure Cognitive Services and Google Cloud Vision. These engines analyze data acquired from the camera and microphone to determine emotions such as "interest," "dissatisfaction," and "confusion" from the user's facial expressions and voice tone.

[0728] Based on the emotions determined by the emotion recognition system, the server adjusts the suggested content using an adjustment system. For example, if the user is confused, the suggested content is adjusted to be more concise and easier to understand. This adjustment improves the likelihood of the suggested content being accepted.

[0729] Finally, the terminal uses a presentation mechanism to display the adjusted suggestions to the user. The suggestions are displayed on the terminal screen, and the user can review and use them.

[0730] Examples of specific prompt messages include the following:

[0731] "Generate specific suggestions on how people in their 30s can use electronic payment methods in their daily lives. Consider the following scenarios: buying groceries at a supermarket, shopping at a convenience store, and paying at a cafe. If the user is confused, provide a brief explanation."

[0732] Thus, this invention proposes an electronic payment method suitable for the user's specific lifestyle and can be further adjusted according to the user's emotional state. This can improve the user experience.

[0733] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0734] Step 1:

[0735] The user inputs information using a device. The user uses input devices such as smartphones or tablets to input information such as their age, lifestyle, and various other conditions in text format. This input information becomes data transmitted to the server via the device's transmission method.

[0736] Specific actions:

[0737] The user enters text into an input form displayed on the device screen.

[0738] The user confirms the information by pressing the "Submit" button.

[0739] Input: Detailed information about the user's age and lifestyle.

[0740] Output: Text data entered into the terminal

[0741] Step 2:

[0742] The terminal sends information entered by the user to the server. The terminal sends data to the server via the network using a transmission method.

[0743] Specific actions:

[0744] The terminal converts the entered text data into JSON format or another format.

[0745] The device sends data to the server using an HTTP POST request.

[0746] Input: Text data of user information entered in the input form.

[0747] Output: User information in JSON format sent to the server

[0748] Step 3:

[0749] Based on the data received by the server, an AI model is used to generate appropriate suggestions. The server generates prompt sentences based on the user's age and lifestyle, and inputs them into the AI ​​model.

[0750] Specific actions:

[0751] The server generates prompt messages based on the user's age and lifestyle.

[0752] The server sends a prompt message to the AI ​​model that generates the response, and receives the generated response.

[0753] Input: User information in JSON format received by the server

[0754] Output: Text data of the proposed content generated based on the generative AI model.

[0755] Step 4:

[0756] The server uses an emotion recognition engine to recognize the user's emotions. The emotion recognition means analyzes audio and video data acquired from the camera and microphone to determine the user's emotional state.

[0757] Specific actions:

[0758] The server acquires the user's facial expressions and voice data through the camera and microphone.

[0759] The server uses an emotion recognition algorithm to determine the emotional state (e.g., "interested," "dissatisfied," "confused").

[0760] Input: User's facial expressions and voice data obtained from the device.

[0761] Output: Analyzed user emotional state data

[0762] Step 5:

[0763] The server adjusts the suggestions based on the recognized emotions. The adjustment mechanism changes the tone of the suggestions and reconstructs the information according to the user's emotional state.

[0764] Specific actions:

[0765] The server analyzes the user's emotional state data and regenerates the suggested content as needed.

[0766] If it is determined that the person is confused, the proposal will be changed to a simpler and easier-to-understand format.

[0767] Input: Generated suggestions, analyzed user emotional state data

[0768] Output: Text data of the adjusted proposal.

[0769] Step 6:

[0770] The server sends the adjusted proposal to the terminal, and the terminal presents it to the user. The adjusted proposal is displayed on the screen using the presentation method.

[0771] Specific actions:

[0772] The server sends the adjusted proposal to the terminal.

[0773] The device displays the data it has received and presents it to the user.

[0774] Input: Adjusted proposal sent from the server

[0775] Output: Screen display of the suggested content presented to the user.

[0776] The above outlines the specific processing flow of this system's program. This allows users to receive suggestions for electronic payment methods suitable for their lifestyle, and these suggestions are adjusted according to the user's feelings, enabling more appropriate and effective use.

[0777] (Application Example 2)

[0778] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0779] In modern society, users increasingly rely on electronic payment methods in various aspects of their daily lives. However, systems that automatically provide suggestions tailored to the user's age and lifestyle are not yet widespread, often leading to confusion in actual use. Furthermore, there is a lack of consideration for user emotions in the approach to suggesting electronic payment methods, resulting in a lack of suggestions that users find satisfactory.

[0780] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for the user to input information, a transmission means for sending the information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the user's emotions, and an adjustment means for adjusting the format of information representation based on the emotions recognized by the emotion recognition means. As a result, the user can receive suggestions for electronic payment methods that are suitable for them, and furthermore, because adjustments are made according to the user's emotions, they can receive suggestions that are more intuitive and convincing.

[0781] An "input method" is a means by which a user can input information such as their age and details of their lifestyle.

[0782] "Transmission means" refers to means for transmitting information obtained from the input means to the server.

[0783] "Generation means" refers to means for generating information using generative artificial intelligence based on information received from the transmission means.

[0784] "Presentation means" refers to means for presenting the information generated by the generation means to the user.

[0785] "Emotion recognition means" are methods for recognizing a user's emotions, and involve analyzing facial expressions, voice tone, and physiological data using cameras and microphones.

[0786] "Adjustment means" refers to means for adjusting the expression format and tone of information based on the emotions recognized by the emotion recognition means.

[0787] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. To realize this system, a program configured as follows is required.

[0788] The system includes input means, transmission means, generation means, presentation means, emotion recognition means, and adjustment means.

[0789] 1. Input method

[0790] Users enter details about their age and lifestyle using devices such as smartphones and tablets. This information is registered in the system as a user profile.

[0791] 2. Transmission method

[0792] The entered user information is transmitted to the server via network communication. Here, the data entered by the user is encrypted and transmitted securely.

[0793] 3. Generation means

[0794] The server uses generative artificial intelligence (generative AI model) based on the received user information to generate suggestions for the most suitable electronic payment method. This generative AI model has the ability to automatically generate suggestions tailored to the user's age and lifestyle. Furthermore, the suggestions are easy for the user to understand and are relevant to specific daily life situations.

[0795] 4. Emotion recognition means

[0796] In addition to user input, the system monitors the user's facial expressions and voice using a camera and microphone, and analyzes the user's emotions using an emotion engine. This analysis data is then sent to a server.

[0797] 5. Adjustment means

[0798] The server adjusts the tone and expression of the generated suggestions based on the emotion data obtained from the emotion recognition system. For example, if the server recognizes that the user is confused, the suggestions will be made simpler and more specific.

[0799] 6. Presentation means

[0800] Finally, the adjusted proposal is sent back to the user's device and displayed on the screen. The user can then see this and understand how to utilize electronic payment methods in specific scenarios.

[0801] Specific example

[0802] This system considers the scenario where a businessman in his 30s wants to know how to use electronic payment methods at a train station kiosk during his commute. First, the user uses a terminal to input information about his age and specific daily life.

[0803] Please begin entering your user information. Enter your age, and then provide detailed information about how you use electronic payment methods in specific daily life situations. For example, "As a businessman in his 30s, how do I use electronic payment methods at a train station kiosk during my commute?"

[0804] Next, the server uses generative artificial intelligence to generate suggestions. For example, "a method of electronic payment using a QR code when purchasing magazines at a train station kiosk" or "an electronic payment method that can be used for regular beverage purchases."

[0805] Simultaneously, emotion recognition analyzes the user's facial expressions and voice, and if the user appears confused, adjusts the suggestions to be clearer and more concise. Finally, the adjusted suggestions are displayed on the user's device, allowing the user to understand how to effectively use electronic payment methods in specific scenarios.

[0806] In this way, users can receive suggestions for the most suitable electronic payment method tailored to their lifestyle, and because these suggestions are adjusted based on the user's feelings, they become easier to understand.

[0807] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0808] Step 1:

[0809] The user enters information using a terminal.

[0810] Input: The user enters details such as age and lifestyle (e.g., a businessman in his 30s wants to know "how to use electronic payment methods at a train station kiosk during his commute").

[0811] Processing: The terminal collects the input data and formats it for transmission to the server.

[0812] Output: Formatted user information is generated and ready for transmission.

[0813] Step 2:

[0814] The device sends user information to the server.

[0815] Input: Formalized user information.

[0816] Processing: The terminal encrypts information over the network and securely transmits it to the server.

[0817] Output: The server receives encrypted user information and decrypts it.

[0818] Step 3:

[0819] The server uses generative artificial intelligence to generate proposals.

[0820] Input: Decoded user information (e.g., a businessman in his 30s, and his electronic payment method at a train station kiosk during his commute).

[0821] Processing: The AI ​​model on the server generates suggestions for the most suitable electronic payment method based on user information.

[0822] Output: Specific suggestions (e.g., how to purchase magazines at station kiosks using QR codes) are generated.

[0823] Step 4:

[0824] The server uses emotion recognition means to recognize the user's emotions.

[0825] Input: User voice and facial expression data obtained using a camera and microphone.

[0826] Processing: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state (e.g., interest, confusion).

[0827] Output: Emotion recognition results are generated.

[0828] Step 5:

[0829] The server adjusts the tone and expression of the suggestions based on the emotions it recognizes.

[0830] Input: Generated suggestions and sentiment recognition results.

[0831] Processing: The server adjusts the proposed content to be clear and concise based on the emotion recognition result (e.g., confusion).

[0832] Output: A revised proposal (e.g., a QR code payment method with detailed steps) is generated.

[0833] Step 6:

[0834] The server sends the adjusted proposal to the terminal.

[0835] Input: Adjusted proposal content.

[0836] Processing: The server encrypts the adjusted proposal and sends it to the terminal over the network.

[0837] Output: The terminal securely receives and decodes the adjusted proposal.

[0838] Step 7:

[0839] The device presents suggestions to the user.

[0840] Input: Decoded and adjusted proposal content.

[0841] Processing: The terminal displays the suggested content and presents it in a way that is easy for the user to understand.

[0842] Output: Users can view and actually use electronic payment methods in specific everyday situations through the screen.

[0843] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0844] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0845] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0846] [Third Embodiment]

[0847] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0848] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0849] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0850] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0851] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0852] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0853] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0854] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0855] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0856] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0857] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0858] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0859] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[0860] System Configuration

[0861] 1. Input method

[0862] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[0863] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[0864] 2. Transmission method

[0865] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[0866] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[0867] 3. Generation means

[0868] The server uses generative artificial intelligence (AI) based on the received information to generate appropriate suggestions. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[0869] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0870] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[0871] Use electronic payment methods when making small purchases at convenience stores.

[0872] I use electronic payment methods for regular tea and cafe visits.

[0873] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[0874] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[0875] 4. Presentation means

[0876] The server sends the generated suggestions back to the terminal, which then presents the information to the user. The user can then view the specific suggestions on the screen.

[0877] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[0878] Specific example

[0879] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[0880] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[0881] 2. Use electronic payment methods when making small purchases at convenience stores.

[0882] 3. Use electronic payment methods for regular tea or cafe visits.

[0883] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[0884] Users can review these specific suggestions and understand, for example, how to scan a QR code and complete payment when purchasing groceries at a supermarket. In this way, it becomes clear how users can specifically utilize electronic payment methods.

[0885] This system makes it easier for users to understand not only the details of the service, but also how they can utilize electronic payment methods in specific everyday situations. Furthermore, because the suggestions are concrete, it is expected to promote user understanding and adoption.

[0886] The following describes the processing flow.

[0887] Step 1:

[0888] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[0889] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[0890] Step 2:

[0891] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[0892] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[0893] Step 3:

[0894] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[0895] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[0896] Step 4:

[0897] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[0898] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[0899] Step 5:

[0900] The server sends the generated list of suggested scenes to the terminal. An internet connection is required for this transmission.

[0901] Example: Send the generated list of suggested scenes to the terminal.

[0902] Step 6:

[0903] The terminal displays a list of suggested scenes received from the server on its screen. The user can review the suggested scenes through this screen.

[0904] Example: A list of suggested scenarios is displayed on the screen, and it is presented with the message, "You can use electronic payment methods like this when purchasing groceries at the supermarket."

[0905] Step 7:

[0906] If a user needs more detailed information about a specific suggested scenario, they can re-enter that information and request it from the server. This is a way to obtain additional suggestions and information.

[0907] Example: The user re-enters "detailed instructions on how to use the service when purchasing groceries at the supermarket" and sends them to the server.

[0908] Step 8:

[0909] The server generates further information based on the additional request and sends it back to the terminal.

[0910] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[0911] Step 9:

[0912] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[0913] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[0914] In this way, the system can provide users with specific and practical suggestions through multiple steps. This allows users to concretely understand how to use electronic payment methods in a way that suits their daily lives and to utilize them effectively.

[0915] (Example 1)

[0916] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0917] Conventional systems had a problem in that it was difficult for users to receive suggestions for appropriate electronic payment methods based on their specific lifestyles. As a result, users had difficulty finding the optimal electronic payment method for their own lifestyles, which hindered the promotion of electronic payment usage.

[0918] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0919] In this invention, the server includes an input means for the user to input information, a transmission means for sending information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, a means for analyzing the information generated by the generation means, a means for using a generative artificial intelligence system to generate suggestions based on the information, and a means for sending the suggestions to the user's terminal. As a result, the user can receive suggestions for the most suitable electronic payment method according to specific life situations, and it is expected that the use of electronic payment methods will be promoted.

[0920] "Input means" refers to a device or system used by a user to input information. This typically includes smartphones and tablets.

[0921] "Transmission means" refers to a device or system for transmitting information from the input means to the server. Typically, data transmission is performed via network communication.

[0922] The "generation means" is a device or system for generating information based on the information received from the transmission means. In this case, it has the function of making suggestions based on user-specified conditions using generative artificial intelligence.

[0923] "Presentation means" refers to a device or system for presenting information generated by the generation means to the user. Typically, this means provides information to the user visually through a terminal screen.

[0924] "Generative artificial intelligence" refers to systems that use artificial intelligence technology to generate information and suggestions based on user-specified conditions. It primarily includes natural language processing and machine learning algorithms.

[0925] "Analysis means" refers to a device or system for analyzing the information generated by the generation means. It performs data format verification and data analysis using an analysis algorithm.

[0926] A "suggestion" is information that indicates the optimal way to use electronic payment methods in specific everyday situations, generated based on the user's input information.

[0927] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[0928] System Configuration

[0929] 1. Input method

[0930] Users input information using their devices (smartphones or tablets). This input includes details such as the user's age and specific aspects of their daily life.

[0931] Specific example: A user uses a terminal to input information about "how people in their 30s use electronic payment methods in their daily lives."

[0932] 2. Transmission method

[0933] The terminal sends the entered information to the server via network communication. The HTTP request protocol is typically used for transmission.

[0934] Specific example: The device sends data about "how people in their 30s use electronic payment methods in their daily lives" to the server as a POST request.

[0935] 3. Generation means

[0936] The server generates appropriate suggestions using generative artificial intelligence (e.g., GPT-4) based on the received information. This generation process utilizes natural language processing and machine learning algorithms. The server first analyzes the received data and then inputs it into the generative artificial intelligence.

[0937] Specific example: The generation AI model automatically generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[0938] I use electronic payment for everyday grocery shopping.

[0939] I use electronic payment to pay at convenience stores.

[0940] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0941] 4. Presentation means

[0942] The server sends the generated suggestions back to the terminal. An HTTP request is used again for this transmission. The terminal then visually displays the received suggestions to the user.

[0943] Specific example: The application displays a list of suggestions received by the terminal from the server on the application screen, and presents to the user with a message such as, "You can use electronic payment in this way for everyday purchases at the supermarket."

[0944] Specific example

[0945] 1. Enter user information:

[0946] The user uses a terminal to input and submit information about "how people in their 30s use electronic payment methods in their daily lives."

[0947] 2. Data transmission:

[0948] The terminal sends the entered data to the server as a POST request.

[0949] 3. Information reception and analysis:

[0950] The server receives the POST request and verifies the data format (such as JSON) using a parsing tool.

[0951] 4. Proposal generation:

[0952] Using generative artificial intelligence (GPT-4), the following proposals will be automatically generated:

[0953] I use electronic payment for everyday grocery shopping.

[0954] I use electronic payment to pay at convenience stores.

[0955] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0956] 5. Submit your proposal:

[0957] The server sends the generated suggestions to the terminal in JSON format.

[0958] 6. Display of proposed content:

[0959] The device displays the suggested content received from the server on the app screen, informing the user, "You can use electronic payment in this way for everyday supermarket purchases."

[0960] Example of a prompt

[0961] "Please suggest ways in which people in their 30s use electronic payment methods in their daily lives."

[0962] This system allows users to receive suggestions for the most suitable electronic payment method tailored to their specific daily life, which is expected to promote the use of electronic payments.

[0963] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0964] Step 1:

[0965] The user enters information using a device. This information includes the user's age and details of specific daily life situations.

[0966] Input: [User information (age, details of lifestyle)]

[0967] Output: [User information entered into the terminal]

[0968] Specific action: The user enters information about "how people in their 30s use electronic payment methods in their daily lives" into an input form on their smartphone or tablet.

[0969] Step 2:

[0970] The terminal sends the entered information to the server via network communication. HTTP requests are used as the transmission protocol.

[0971] Input: [User information entered on the terminal]

[0972] Output: [User information sent to the server]

[0973] Specific operation: The terminal uses an HTTP POST request to send the entered data to the server.

[0974] Step 3:

[0975] The server analyzes the received information. It verifies the data format and uses analysis algorithms to confirm the data's content.

[0976] Input: [User information sent to the server]

[0977] Output: [Analyzed user information]

[0978] Specific operation: The server receives data in JSON format and verifies the data format. Then, it uses an analysis tool to check the contents.

[0979] Step 4:

[0980] The server generates appropriate suggestions using a generative artificial intelligence model (e.g., GPT-4) based on the analyzed information. The suggestions are automatically generated based on the user's age and lifestyle.

[0981] Input: [Analyzed user information]

[0982] Output: [Generated proposal content]

[0983] Specific operation: The server inputs the analysis results into a generative artificial intelligence model and generates suggestions such as the following:

[0984] I use electronic payment for everyday grocery shopping.

[0985] I use electronic payment to pay at convenience stores.

[0986] I used electronic payment when purchasing items at a station kiosk on my way to work.

[0987] Step 5:

[0988] The server then sends the generated suggestions back to the terminal. The transmission protocol uses HTTP requests.

[0989] Input: [Generated proposal content]

[0990] Output: [Suggestions sent to the terminal]

[0991] Specific operation: The server sends the generated proposal to the terminal in JSON format using an HTTP POST request.

[0992] Step 6:

[0993] The terminal visually displays the suggestions received from the server to the user. The application's GUI is used for this display.

[0994] Input: [Suggestion sent to the device]

[0995] Output: [Suggestions displayed visually to the user]

[0996] Specific operation: The application screen displays the list of suggestions received by the terminal, and the user is shown, "You can use electronic payment in this way for everyday supermarket purchases."

[0997] Through these steps, users can receive suggestions for the most suitable electronic payment method tailored to their specific lifestyle.

[0998] (Application Example 1)

[0999] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1000] While various electronic payment methods are widespread in modern life, it can be difficult for users to choose the most suitable method for their specific needs and understand how to use it effectively. Furthermore, there are insufficient means for users to receive appropriate suggestions tailored to their age and lifestyle, preventing them from fully realizing the convenience of electronic payments.

[1001] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1002] In this invention, the server includes an input means for the user to input information about their daily life, a transmission means for sending the information from the input means to the server, a generation means for generating suggested content based on the information received from the transmission means, and a presentation means for presenting the suggested content generated by the generation means to the user. This makes it possible to provide suggestions that clearly show the user how to understand the most suitable electronic payment method for their daily life and how to use it effectively.

[1003] A "user" refers to an individual who uses the system to input information based on their own life circumstances and conditions.

[1004] "Lifestyle scene information" refers to information that shows specific scenes and situations in the user's daily life.

[1005] "Input method" refers to the interface that allows users to input information about their daily lives into the system.

[1006] "Transmission means" refers to a function for transmitting information input from the input means to the server.

[1007] "Generation means" refers to the function that generates suitable suggestions for the user using generative artificial intelligence based on the information received by the server.

[1008] "Proposed content" refers to specific recommendations regarding the optimal electronic payment method for a user's daily life, as generated by the generation method.

[1009] "Presentation means" refers to a function that displays the proposed content generated by the generation means on the user's terminal and presents it to the user.

[1010] "Generative artificial intelligence" refers to artificial intelligence technology that generates optimal suggestions based on user input.

[1011] "Electronic payment methods" refer to all payment methods that utilize digital technology.

[1012] A system for implementing this invention is built primarily using the following hardware and software.

[1013] Hardware to use

[1014] 1. Devices such as smartphones and tablets

[1015] 2. Cloud server or physical server

[1016] Software to use

[1017] 1. An application (smartphone app) for users to input information about their daily life.

[1018] 2. Network communication function for sending and receiving data

[1019] 3. Server-side software for operating generative artificial intelligence models

[1020] 4. Applications (smartphone apps) for presenting information to users.

[1021] System Operation Overview

[1022] User side

[1023] 1. Inputting information about daily life scenes:

[1024] Users use their smartphones to input information about their daily lives (e.g., grocery shopping, payments made during their commute) through the application. The application is designed to allow users to easily input information.

[1025] Transmission method

[1026] 2. Sending data:

[1027] Lifestyle information is sent to a cloud server using the smartphone's network communication function.

[1028] Server side

[1029] 3. Generating the proposal:

[1030] The cloud server uses a generative artificial intelligence model to generate the most suitable electronic payment method for the user based on the received lifestyle data. This model dynamically generates suggestions based on the input information.

[1031] For example, if you provide a scenario where "a user in their 30s buys a magazine at a train station kiosk on their way to work," the generative AI will suggest the most suitable electronic payment method for that scenario.

[1032] As a concrete example, consider the following prompt as input to a generative artificial intelligence model:

[1033] Prompt: "User information: Age 30, Lifestyle: Purchasing a magazine at a train station kiosk during commute. Please suggest an appropriate electronic payment method."

[1034] Presentation to the user

[1035] 4. Presentation of the proposal:

[1036] The generated suggestions are sent back to the smartphone from the cloud server and presented through the user's application. Users can review the specific suggestions and understand how they should utilize electronic payment methods in their daily lives.

[1037] This system enhances user convenience and contributes to the widespread adoption of electronic payments by dynamically suggesting electronic payment methods based on information entered by the user. The problem-solving means provided by the invention are realized through the specific operation flow described above.

[1038] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1039] Step 1:

[1040] The user opens the smartphone application and enters information about their age and daily life. For example, the user might enter information such as "in their 30s, buys a magazine at a station kiosk on their way to work." The entered information is then structured by the application as JSON data.

[1041] Step 2:

[1042] The device (smartphone) sends structured JSON data to a cloud server. This data is securely transmitted using network communication (e.g., the HTTPS protocol). It receives data containing age and lifestyle information as input and sends it to the cloud server as output.

[1043] Step 3:

[1044] The server parses the received JSON data and extracts the necessary information. Specifically, it stores the user's age and lifestyle information in a database and generates prompts to input into a generative artificial intelligence model. For example, it might generate a prompt like, "User information: Age 30, Lifestyle: Buying a magazine at a station kiosk on the way to work. Please suggest an appropriate electronic payment method."

[1045] Step 4:

[1046] A generative artificial intelligence model is input with prompt text, and it generates suggestions for the most suitable electronic payment method for the user. Using the generated prompt text as input, the AI ​​model performs data calculations and outputs suggestions, including electronic payment methods, that are appropriate for the user's lifestyle.

[1047] Step 5:

[1048] The server converts the generated suggestions back into JSON format and sends them to the user's smartphone over the network. It receives output data from the AI ​​model as input and converts it into an appropriate data format for sending to the smartphone as output.

[1049] Step 6:

[1050] The terminal displays suggestions received from the server via an application. For example, a specific suggestion such as, "When purchasing magazines at a station kiosk on your commute, QR code payment is convenient," might be displayed on the screen. This allows users to intuitively understand how to utilize electronic payment methods in their daily lives.

[1051] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1052] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function where the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user. Furthermore, the system incorporates an emotion engine to recognize the user's emotions and adds a function to adjust the suggestions according to the user's feelings.

[1053] System Configuration

[1054] 1. Input method

[1055] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[1056] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[1057] 2. Transmission method

[1058] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[1059] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[1060] 3. Generation means

[1061] The server uses generative artificial intelligence (AI) based on the received information to generate appropriate suggestions. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[1062] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[1063] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[1064] Use electronic payment methods when making small purchases at convenience stores.

[1065] I use electronic payment methods for regular tea and cafe visits.

[1066] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[1067] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[1068] 4. Emotional Engine

[1069] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice, facial expressions, and physiological data to recognize emotions.

[1070] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[1071] 5. Emotion-based adjustment

[1072] The server modifies the tone and expression of suggestions based on the user's emotions as recognized by the emotion engine. For example, if the user is interested, it will provide detailed and proactive suggestions, while if they are confused, it will provide simpler and easier-to-understand suggestions.

[1073] Example: If you recognize that the user is confused, briefly explain "the procedure for purchasing groceries at a supermarket."

[1074] 6. Presentation means

[1075] The server sends information to the terminal, adjusted based on the generated suggested scenes and emotions, and the terminal presents this information to the user. The user can then view the specific suggestions on the screen.

[1076] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[1077] Specific example

[1078] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[1079] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[1080] 2. Use electronic payment methods when making small purchases at convenience stores.

[1081] 3. Use electronic payment methods for regular tea or cafe visits.

[1082] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[1083] Simultaneously, the emotion engine analyzes the user's reactions, reading their emotions from their facial expressions and voice. For example, if the user indicates "confusion," the server adjusts the suggestions to make them clearer and more concise. Finally, the device displays these suggestions on the screen, presenting them in a format that is easy for the user to understand.

[1084] In this way, users can more easily understand how to use electronic payment methods in relation to specific everyday situations, and further promotion of their use can be expected through adjustments based on their emotions.

[1085] The following describes the processing flow.

[1086] Step 1:

[1087] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[1088] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[1089] Step 2:

[1090] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[1091] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[1092] Step 3:

[1093] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[1094] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[1095] Step 4:

[1096] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[1097] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[1098] Step 5:

[1099] During the process of generating suggested scenes, the server uses an emotion engine to recognize the user's emotions. The emotion engine recognizes emotions by analyzing the user's voice, facial expressions, and physiological data.

[1100] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[1101] Step 6:

[1102] The server adjusts its suggestions based on the emotions recognized by the emotion engine. For example, if the user shows interest, it provides detailed and proactive suggestions; if they are confused, it changes to simpler and easier-to-understand suggestions.

[1103] For example, if it is recognized that the user is confused, the content will be adjusted to briefly explain "the procedure for purchasing groceries at a supermarket."

[1104] Step 7:

[1105] The server sends the generated list of suggested scenes and information adjusted based on emotions to the terminal. An internet connection is required for transmission.

[1106] Example: Send the generated list of suggested scenes to the terminal.

[1107] Step 8:

[1108] The terminal displays a list of suggested scenes received from the server on its screen. The user can review the suggested scenes through this screen.

[1109] Example: A list of suggested scenarios is displayed on the screen, and it is presented with the message, "You can use electronic payment methods like this when purchasing groceries at the supermarket on a daily basis."

[1110] Step 9:

[1111] If a user needs more detailed information about a specific suggested scenario, they can re-enter that information and request it from the server. This is a way to obtain additional suggestions and information.

[1112] Example: The user re-enters "detailed instructions on how to use the service when purchasing groceries at the supermarket" and sends them to the server.

[1113] Step 10:

[1114] The server generates further information based on the additional request and sends it back to the terminal.

[1115] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[1116] Step 11:

[1117] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[1118] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[1119] In this way, the system can provide users with specific and practical suggestions through multiple steps. By utilizing the emotion engine, optimal suggestions are made according to the user's emotions, which is expected to further promote its use.

[1120] (Example 2)

[1121] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1122] Conventional suggestion systems have struggled to flexibly provide electronic payment methods suited to users' emotions and specific life situations. Furthermore, they lacked adjustments to account for diverse user emotional states, resulting in a uniform and inefficient user experience. Additionally, suggestions based on pre-set templates were insufficient to meet individual user needs.

[1123] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting information from the input means, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the user's emotions, and an adjustment means for adjusting the information based on the emotions recognized by the emotion recognition means. This enables flexible suggestions tailored to the individual needs of the user, and further, by adjusting the content of the suggestions according to the user's emotional state, it becomes possible to provide a more personalized and efficient user experience.

[1124] "Input means" refers to a device or interface used by a user to input their own information or requests.

[1125] "Transmission means" refers to a device or protocol that has a communication function for transmitting information obtained from input means to a server.

[1126] "Generation means" refers to a function or system that uses a generation AI model to generate appropriate suggestions or information based on the information received by the server.

[1127] "Presentation means" refers to a device or interface for presenting information generated by a generation means to a user visually or audibly.

[1128] An "emotion recognition tool" is a system or algorithm that analyzes data such as a user's facial expressions and voice to recognize the user's emotional state.

[1129] "Adjustment means" refers to a function or system for adjusting the generated suggestion content based on the user's emotions recognized by the emotion recognition means.

[1130] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system is composed of a combination of multiple hardware and software elements.

[1131] First, the user inputs information using an input device. A smartphone or tablet is preferred as the input device. For example, the user might input information such as "How people in their 30s use electronic payment methods in their daily lives." In this case, text input can be done using the device's touchscreen.

[1132] Next, the terminal uses a transmission method to send the information entered by the user to the server. This transmission utilizes network communication, and typically, data is sent to the server using an HTTP POST request. The transmitted data is in a common data format such as JSON.

[1133] The server generates suggestions based on the information received using a generation mechanism. The generation mechanism utilizes a generative AI model, such as OpenAI's GPT-4. The server generates specific electronic payment scenarios based on the conditions entered by the user. Examples of generated suggestions include:

[1134] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[1135] Use electronic payment methods when making small purchases at convenience stores.

[1136] I use electronic payment methods for regular tea and cafe visits.

[1137] Furthermore, the server uses emotion recognition tools to recognize the user's emotions. This utilizes emotion recognition engines such as Microsoft Azure Cognitive Services and Google Cloud Vision. These engines analyze data acquired from the camera and microphone to determine emotions such as "interest," "dissatisfaction," and "confusion" from the user's facial expressions and voice tone.

[1138] Based on the emotions determined by the emotion recognition system, the server adjusts the suggested content using an adjustment system. For example, if the user is confused, the suggested content is adjusted to be more concise and easier to understand. This adjustment improves the likelihood of the suggested content being accepted.

[1139] Finally, the terminal uses a presentation mechanism to display the adjusted suggestions to the user. The suggestions are displayed on the terminal screen, and the user can review and use them.

[1140] Examples of specific prompt messages include the following:

[1141] "Generate specific suggestions on how people in their 30s can use electronic payment methods in their daily lives. Consider the following scenarios: buying groceries at a supermarket, shopping at a convenience store, and paying at a cafe. If the user is confused, provide a brief explanation."

[1142] Thus, this invention proposes an electronic payment method suitable for the user's specific lifestyle and can be further adjusted according to the user's emotional state. This can improve the user experience.

[1143] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1144] Step 1:

[1145] The user inputs information using a device. The user uses input devices such as smartphones or tablets to input information such as their age, lifestyle, and various other conditions in text format. This input information becomes data transmitted to the server via the device's transmission method.

[1146] Specific actions:

[1147] The user enters text into an input form displayed on the device screen.

[1148] The user confirms the information by pressing the "Submit" button.

[1149] Input: Detailed information about the user's age and lifestyle.

[1150] Output: Text data entered into the terminal

[1151] Step 2:

[1152] The terminal sends information entered by the user to the server. The terminal sends data to the server via the network using a transmission method.

[1153] Specific actions:

[1154] The terminal converts the entered text data into JSON format or another format.

[1155] The device sends data to the server using an HTTP POST request.

[1156] Input: Text data of user information entered in the input form.

[1157] Output: User information in JSON format sent to the server

[1158] Step 3:

[1159] Based on the data received by the server, an AI model is used to generate appropriate suggestions. The server generates prompt sentences based on the user's age and lifestyle, and inputs them into the AI ​​model.

[1160] Specific actions:

[1161] The server generates prompt messages based on the user's age and lifestyle.

[1162] The server sends a prompt message to the AI ​​model that generates the response, and receives the generated response.

[1163] Input: User information in JSON format received by the server

[1164] Output: Text data of the proposed content generated based on the generative AI model.

[1165] Step 4:

[1166] The server uses an emotion recognition engine to recognize the user's emotions. The emotion recognition means analyzes audio and video data acquired from the camera and microphone to determine the user's emotional state.

[1167] Specific actions:

[1168] The server acquires the user's facial expressions and voice data through the camera and microphone.

[1169] The server uses an emotion recognition algorithm to determine the emotional state (e.g., "interested," "dissatisfied," "confused").

[1170] Input: User's facial expressions and voice data obtained from the device.

[1171] Output: Analyzed user emotional state data

[1172] Step 5:

[1173] The server adjusts the suggestions based on the recognized emotions. The adjustment mechanism changes the tone of the suggestions and reconstructs the information according to the user's emotional state.

[1174] Specific actions:

[1175] The server analyzes the user's emotional state data and regenerates the suggested content as needed.

[1176] If it is determined that the person is confused, the proposal will be changed to a simpler and easier-to-understand format.

[1177] Input: Generated suggestions, analyzed user emotional state data

[1178] Output: Text data of the adjusted proposal.

[1179] Step 6:

[1180] The server sends the adjusted proposal to the terminal, and the terminal presents it to the user. The adjusted proposal is displayed on the screen using the presentation method.

[1181] Specific actions:

[1182] The server sends the adjusted proposal to the terminal.

[1183] The device displays the data it has received and presents it to the user.

[1184] Input: Adjusted proposal sent from the server

[1185] Output: Screen display of the suggested content presented to the user.

[1186] The above outlines the specific processing flow of this system's program. This allows users to receive suggestions for electronic payment methods suitable for their lifestyle, and these suggestions are adjusted according to the user's feelings, enabling more appropriate and effective use.

[1187] (Application Example 2)

[1188] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1189] In modern society, users increasingly rely on electronic payment methods in various aspects of their daily lives. However, systems that automatically provide suggestions tailored to the user's age and lifestyle are not yet widespread, often leading to confusion in actual use. Furthermore, there is a lack of consideration for user emotions in the approach to suggesting electronic payment methods, resulting in a lack of suggestions that users find satisfactory.

[1190] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for the user to input information, a transmission means for sending the information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the user's emotions, and an adjustment means for adjusting the format of information representation based on the emotions recognized by the emotion recognition means. As a result, the user can receive suggestions for electronic payment methods that are suitable for them, and furthermore, because adjustments are made according to the user's emotions, they can receive suggestions that are more intuitive and convincing.

[1191] An "input method" is a means by which a user can input information such as their age and details of their lifestyle.

[1192] "Transmission means" refers to means for transmitting information obtained from the input means to the server.

[1193] "Generation means" refers to means for generating information using generative artificial intelligence based on information received from the transmission means.

[1194] "Presentation means" refers to means for presenting the information generated by the generation means to the user.

[1195] "Emotion recognition means" are methods for recognizing a user's emotions, and involve analyzing facial expressions, voice tone, and physiological data using cameras and microphones.

[1196] "Adjustment means" refers to means for adjusting the expression format and tone of information based on the emotions recognized by the emotion recognition means.

[1197] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. To realize this system, a program configured as follows is required.

[1198] The system includes input means, transmission means, generation means, presentation means, emotion recognition means, and adjustment means.

[1199] 1. Input method

[1200] Users enter details about their age and lifestyle using devices such as smartphones and tablets. This information is registered in the system as a user profile.

[1201] 2. Transmission method

[1202] The entered user information is transmitted to the server via network communication. Here, the data entered by the user is encrypted and transmitted securely.

[1203] 3. Generation means

[1204] The server uses generative artificial intelligence (generative AI model) based on the received user information to generate suggestions for the most suitable electronic payment method. This generative AI model has the ability to automatically generate suggestions tailored to the user's age and lifestyle. Furthermore, the suggestions are easy for the user to understand and are relevant to specific daily life situations.

[1205] 4. Emotion recognition means

[1206] In addition to user input, the system monitors the user's facial expressions and voice using a camera and microphone, and analyzes the user's emotions using an emotion engine. This analysis data is then sent to a server.

[1207] 5. Adjustment means

[1208] The server adjusts the tone and expression of the generated suggestions based on the emotion data obtained from the emotion recognition system. For example, if the server recognizes that the user is confused, the suggestions will be made simpler and more specific.

[1209] 6. Presentation means

[1210] Finally, the adjusted proposal is sent back to the user's device and displayed on the screen. The user can then see this and understand how to utilize electronic payment methods in specific scenarios.

[1211] Specific example

[1212] This system considers the scenario where a businessman in his 30s wants to know how to use electronic payment methods at a train station kiosk during his commute. First, the user uses a terminal to input information about his age and specific daily life.

[1213] Please begin entering your user information. Enter your age, and then provide detailed information about how you use electronic payment methods in specific daily life situations. For example, "As a businessman in his 30s, how do I use electronic payment methods at a train station kiosk during my commute?"

[1214] Next, the server uses generative artificial intelligence to generate suggestions. For example, "a method of electronic payment using a QR code when purchasing magazines at a train station kiosk" or "an electronic payment method that can be used for regular beverage purchases."

[1215] Simultaneously, emotion recognition analyzes the user's facial expressions and voice, and if the user appears confused, adjusts the suggestions to be clearer and more concise. Finally, the adjusted suggestions are displayed on the user's device, allowing the user to understand how to effectively use electronic payment methods in specific scenarios.

[1216] In this way, users can receive suggestions for the most suitable electronic payment method tailored to their lifestyle, and because these suggestions are adjusted based on the user's feelings, they become easier to understand.

[1217] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1218] Step 1:

[1219] The user enters information using a terminal.

[1220] Input: The user enters details such as age and lifestyle (e.g., a businessman in his 30s wants to know "how to use electronic payment methods at a train station kiosk during his commute").

[1221] Processing: The terminal collects the input data and formats it for transmission to the server.

[1222] Output: Formatted user information is generated and ready for transmission.

[1223] Step 2:

[1224] The device sends user information to the server.

[1225] Input: Formalized user information.

[1226] Processing: The terminal encrypts information over the network and securely transmits it to the server.

[1227] Output: The server receives encrypted user information and decrypts it.

[1228] Step 3:

[1229] The server uses generative artificial intelligence to generate proposals.

[1230] Input: Decoded user information (e.g., a businessman in his 30s, and his electronic payment method at a train station kiosk during his commute).

[1231] Processing: The AI ​​model on the server generates suggestions for the most suitable electronic payment method based on user information.

[1232] Output: Specific suggestions (e.g., how to purchase magazines at station kiosks using QR codes) are generated.

[1233] Step 4:

[1234] The server uses emotion recognition means to recognize the user's emotions.

[1235] Input: User voice and facial expression data obtained using a camera and microphone.

[1236] Processing: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state (e.g., interest, confusion).

[1237] Output: Emotion recognition results are generated.

[1238] Step 5:

[1239] The server adjusts the tone and expression of the suggestions based on the emotions it recognizes.

[1240] Input: Generated suggestions and sentiment recognition results.

[1241] Processing: The server adjusts the proposed content to be clear and concise based on the emotion recognition result (e.g., confusion).

[1242] Output: A revised proposal (e.g., a QR code payment method with detailed steps) is generated.

[1243] Step 6:

[1244] The server sends the adjusted proposal to the terminal.

[1245] Input: Adjusted proposal content.

[1246] Processing: The server encrypts the adjusted proposal and sends it to the terminal over the network.

[1247] Output: The terminal securely receives and decodes the adjusted proposal.

[1248] Step 7:

[1249] The device presents suggestions to the user.

[1250] Input: Decoded and adjusted proposal content.

[1251] Processing: The terminal displays the suggested content and presents it in a way that is easy for the user to understand.

[1252] Output: Users can view and actually use electronic payment methods in specific everyday situations through the screen.

[1253] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1254] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1255] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1256] [Fourth Embodiment]

[1257] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1258] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1259] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1260] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1261] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1262] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1263] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1264] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1265] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1266] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1267] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1268] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1269] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1270] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[1271] System Configuration

[1272] 1. Input method

[1273] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[1274] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[1275] 2. Transmission method

[1276] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[1277] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[1278] 3. Generation means

[1279] The server uses generative artificial intelligence (AI) based on the received information to generate appropriate suggestions. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[1280] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[1281] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[1282] Use electronic payment methods when making small purchases at convenience stores.

[1283] I use electronic payment methods for regular tea and cafe visits.

[1284] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[1285] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[1286] 4. Presentation means

[1287] The server sends the generated suggestions back to the terminal, which then presents the information to the user. The user can then view the specific suggestions on the screen.

[1288] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[1289] Specific example

[1290] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[1291] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[1292] 2. Use electronic payment methods when making small purchases at convenience stores.

[1293] 3. Use electronic payment methods for regular tea or cafe visits.

[1294] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[1295] Users can review these specific suggestions and understand, for example, how to scan a QR code and complete payment when purchasing groceries at a supermarket. In this way, it becomes clear how users can specifically utilize electronic payment methods.

[1296] This system makes it easier for users to understand not only the details of the service, but also how they can utilize electronic payment methods in specific everyday situations. Furthermore, because the suggestions are concrete, it is expected to promote user understanding and adoption.

[1297] The following describes the processing flow.

[1298] Step 1:

[1299] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[1300] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[1301] Step 2:

[1302] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[1303] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[1304] Step 3:

[1305] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[1306] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[1307] Step 4:

[1308] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[1309] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[1310] Step 5:

[1311] The server sends the generated list of suggested scenes to the terminal. An internet connection is required for this transmission.

[1312] Example: Send the generated list of suggested scenes to the terminal.

[1313] Step 6:

[1314] The terminal displays a list of suggested scenes received from the server on its screen. The user can review the suggested scenes through this screen.

[1315] Example: A list of suggested scenarios is displayed on the screen, and it is presented with the message, "You can use electronic payment methods like this when purchasing groceries at the supermarket."

[1316] Step 7:

[1317] If a user needs more detailed information about a specific suggested scenario, they can re-enter that information and request it from the server. This is a way to obtain additional suggestions and information.

[1318] Example: The user re-enters "detailed instructions on how to use the service when purchasing groceries at the supermarket" and sends them to the server.

[1319] Step 8:

[1320] The server generates further information based on the additional request and sends it back to the terminal.

[1321] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[1322] Step 9:

[1323] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[1324] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[1325] In this way, the system can provide users with specific and practical suggestions through multiple steps. This allows users to concretely understand how to use electronic payment methods in a way that suits their daily lives and to utilize them effectively.

[1326] (Example 1)

[1327] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1328] Conventional systems had a problem in that it was difficult for users to receive suggestions for appropriate electronic payment methods based on their specific lifestyles. As a result, users had difficulty finding the optimal electronic payment method for their own lifestyles, which hindered the promotion of electronic payment usage.

[1329] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1330] In this invention, the server includes an input means for the user to input information, a transmission means for sending information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, a means for analyzing the information generated by the generation means, a means for using a generative artificial intelligence system to generate suggestions based on the information, and a means for sending the suggestions to the user's terminal. As a result, the user can receive suggestions for the most suitable electronic payment method according to specific life situations, and it is expected that the use of electronic payment methods will be promoted.

[1331] "Input means" refers to a device or system used by a user to input information. This typically includes smartphones and tablets.

[1332] "Transmission means" refers to a device or system for transmitting information from the input means to the server. Typically, data transmission is performed via network communication.

[1333] The "generation means" is a device or system for generating information based on the information received from the transmission means. In this case, it has the function of making suggestions based on user-specified conditions using generative artificial intelligence.

[1334] "Presentation means" refers to a device or system for presenting information generated by the generation means to the user. Typically, this means provides information to the user visually through a terminal screen.

[1335] "Generative artificial intelligence" refers to systems that use artificial intelligence technology to generate information and suggestions based on user-specified conditions. It primarily includes natural language processing and machine learning algorithms.

[1336] "Analysis means" refers to a device or system for analyzing the information generated by the generation means. It performs data format verification and data analysis using an analysis algorithm.

[1337] A "suggestion" is information that indicates the optimal way to use electronic payment methods in specific everyday situations, generated based on the user's input information.

[1338] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function in which the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user.

[1339] System Configuration

[1340] 1. Input method

[1341] Users input information using their devices (smartphones or tablets). This input includes details such as the user's age and specific aspects of their daily life.

[1342] Specific example: A user uses a terminal to input information about "how people in their 30s use electronic payment methods in their daily lives."

[1343] 2. Transmission method

[1344] The terminal sends the entered information to the server via network communication. The HTTP request protocol is typically used for transmission.

[1345] Specific example: The device sends data about "how people in their 30s use electronic payment methods in their daily lives" to the server as a POST request.

[1346] 3. Generation means

[1347] The server generates appropriate suggestions using generative artificial intelligence (e.g., GPT-4) based on the received information. This generation process utilizes natural language processing and machine learning algorithms. The server first analyzes the received data and then inputs it into the generative artificial intelligence.

[1348] Specific example: The generation AI model automatically generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[1349] I use electronic payment for everyday grocery shopping.

[1350] I use electronic payment to pay at convenience stores.

[1351] I used electronic payment when purchasing items at a station kiosk on my way to work.

[1352] 4. Presentation means

[1353] The server sends the generated suggestions back to the terminal. An HTTP request is used again for this transmission. The terminal then visually displays the received suggestions to the user.

[1354] Specific example: The application displays a list of suggestions received by the terminal from the server on the application screen, and presents to the user with a message such as, "You can use electronic payment in this way for everyday purchases at the supermarket."

[1355] Specific example

[1356] 1. Enter user information:

[1357] The user uses a terminal to input and submit information about "how people in their 30s use electronic payment methods in their daily lives."

[1358] 2. Data transmission:

[1359] The terminal sends the entered data to the server as a POST request.

[1360] 3. Information reception and analysis:

[1361] The server receives the POST request and verifies the data format (such as JSON) using a parsing tool.

[1362] 4. Proposal generation:

[1363] Using generative artificial intelligence (GPT-4), the following proposals will be automatically generated:

[1364] I use electronic payment for everyday grocery shopping.

[1365] I use electronic payment to pay at convenience stores.

[1366] I used electronic payment when purchasing items at a station kiosk on my way to work.

[1367] 5. Submit your proposal:

[1368] The server sends the generated suggestions to the terminal in JSON format.

[1369] 6. Display of proposed content:

[1370] The device displays the suggested content received from the server on the app screen, informing the user, "You can use electronic payment in this way for everyday supermarket purchases."

[1371] Example of a prompt

[1372] "Please suggest ways in which people in their 30s use electronic payment methods in their daily lives."

[1373] This system allows users to receive suggestions for the most suitable electronic payment method tailored to their specific daily life, which is expected to promote the use of electronic payments.

[1374] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1375] Step 1:

[1376] The user enters information using a device. This information includes the user's age and details of specific daily life situations.

[1377] Input: [User information (age, details of lifestyle)]

[1378] Output: [User information entered into the terminal]

[1379] Specific action: The user enters information about "how people in their 30s use electronic payment methods in their daily lives" into an input form on their smartphone or tablet.

[1380] Step 2:

[1381] The terminal sends the entered information to the server via network communication. HTTP requests are used as the transmission protocol.

[1382] Input: [User information entered on the terminal]

[1383] Output: [User information sent to the server]

[1384] Specific operation: The terminal uses an HTTP POST request to send the entered data to the server.

[1385] Step 3:

[1386] The server analyzes the received information. It verifies the data format and uses analysis algorithms to confirm the data's content.

[1387] Input: [User information sent to the server]

[1388] Output: [Analyzed user information]

[1389] Specific operation: The server receives data in JSON format and verifies the data format. Then, it uses an analysis tool to check the contents.

[1390] Step 4:

[1391] The server generates appropriate suggestions using a generative artificial intelligence model (e.g., GPT-4) based on the analyzed information. The suggestions are automatically generated based on the user's age and lifestyle.

[1392] Input: [Analyzed user information]

[1393] Output: [Generated proposal content]

[1394] Specific operation: The server inputs the analysis results into a generative artificial intelligence model and generates suggestions such as the following:

[1395] I use electronic payment for everyday grocery shopping.

[1396] I use electronic payment to pay at convenience stores.

[1397] I used electronic payment when purchasing items at a station kiosk on my way to work.

[1398] Step 5:

[1399] The server then sends the generated suggestions back to the terminal. The transmission protocol uses HTTP requests.

[1400] Input: [Generated proposal content]

[1401] Output: [Suggestions sent to the terminal]

[1402] Specific operation: The server sends the generated proposal to the terminal in JSON format using an HTTP POST request.

[1403] Step 6:

[1404] The terminal visually displays the suggestions received from the server to the user. The application's GUI is used for this display.

[1405] Input: [Suggestion sent to the device]

[1406] Output: [Suggestions displayed visually to the user]

[1407] Specific operation: The application screen displays the list of suggestions received by the terminal, and the user is shown, "You can use electronic payment in this way for everyday supermarket purchases."

[1408] Through these steps, users can receive suggestions for the most suitable electronic payment method tailored to their specific lifestyle.

[1409] (Application Example 1)

[1410] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1411] While various electronic payment methods are widespread in modern life, it can be difficult for users to choose the most suitable method for their specific needs and understand how to use it effectively. Furthermore, there are insufficient means for users to receive appropriate suggestions tailored to their age and lifestyle, preventing them from fully realizing the convenience of electronic payments.

[1412] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1413] In this invention, the server includes an input means for the user to input information about their daily life, a transmission means for sending the information from the input means to the server, a generation means for generating suggested content based on the information received from the transmission means, and a presentation means for presenting the suggested content generated by the generation means to the user. This makes it possible to provide suggestions that clearly show the user how to understand the most suitable electronic payment method for their daily life and how to use it effectively.

[1414] A "user" refers to an individual who uses the system to input information based on their own life circumstances and conditions.

[1415] "Lifestyle scene information" refers to information that shows specific scenes and situations in the user's daily life.

[1416] "Input method" refers to the interface that allows users to input information about their daily lives into the system.

[1417] "Transmission means" refers to a function for transmitting information input from the input means to the server.

[1418] "Generation means" refers to the function that generates suitable suggestions for the user using generative artificial intelligence based on the information received by the server.

[1419] "Proposed content" refers to specific recommendations regarding the optimal electronic payment method for a user's daily life, as generated by the generation method.

[1420] "Presentation means" refers to a function that displays the proposed content generated by the generation means on the user's terminal and presents it to the user.

[1421] "Generative artificial intelligence" refers to artificial intelligence technology that generates optimal suggestions based on user input.

[1422] "Electronic payment methods" refer to all payment methods that utilize digital technology.

[1423] A system for implementing this invention is built primarily using the following hardware and software.

[1424] Hardware to use

[1425] 1. Devices such as smartphones and tablets

[1426] 2. Cloud server or physical server

[1427] Software to use

[1428] 1. An application (smartphone app) for users to input information about their daily life.

[1429] 2. Network communication function for sending and receiving data

[1430] 3. Server-side software for operating generative artificial intelligence models

[1431] 4. Applications (smartphone apps) for presenting information to users.

[1432] System Operation Overview

[1433] User side

[1434] 1. Inputting information about daily life scenes:

[1435] Users use their smartphones to input information about their daily lives (e.g., grocery shopping, payments made during their commute) through the application. The application is designed to allow users to easily input information.

[1436] Transmission method

[1437] 2. Sending data:

[1438] Lifestyle information is sent to a cloud server using the smartphone's network communication function.

[1439] Server side

[1440] 3. Generating the proposal:

[1441] The cloud server uses a generative artificial intelligence model to generate the most suitable electronic payment method for the user based on the received lifestyle data. This model dynamically generates suggestions based on the input information.

[1442] For example, if you provide a scenario where "a user in their 30s buys a magazine at a train station kiosk on their way to work," the generative AI will suggest the most suitable electronic payment method for that scenario.

[1443] As a concrete example, consider the following prompt as input to a generative artificial intelligence model:

[1444] Prompt: "User information: Age 30, Lifestyle: Purchasing a magazine at a train station kiosk during commute. Please suggest an appropriate electronic payment method."

[1445] Presentation to the user

[1446] 4. Presentation of the proposal:

[1447] The generated suggestions are sent back to the smartphone from the cloud server and presented through the user's application. Users can review the specific suggestions and understand how they should utilize electronic payment methods in their daily lives.

[1448] This system enhances user convenience and contributes to the widespread adoption of electronic payments by dynamically suggesting electronic payment methods based on information entered by the user. The problem-solving means provided by the invention are realized through the specific operation flow described above.

[1449] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1450] Step 1:

[1451] The user opens the smartphone application and enters information about their age and daily life. For example, the user might enter information such as "in their 30s, buys a magazine at a station kiosk on their way to work." The entered information is then structured by the application as JSON data.

[1452] Step 2:

[1453] The device (smartphone) sends structured JSON data to a cloud server. This data is securely transmitted using network communication (e.g., the HTTPS protocol). It receives data containing age and lifestyle information as input and sends it to the cloud server as output.

[1454] Step 3:

[1455] The server parses the received JSON data and extracts the necessary information. Specifically, it stores the user's age and lifestyle information in a database and generates prompts to input into a generative artificial intelligence model. For example, it might generate a prompt like, "User information: Age 30, Lifestyle: Buying a magazine at a station kiosk on the way to work. Please suggest an appropriate electronic payment method."

[1456] Step 4:

[1457] A generative artificial intelligence model is input with prompt text, and it generates suggestions for the most suitable electronic payment method for the user. Using the generated prompt text as input, the AI ​​model performs data calculations and outputs suggestions, including electronic payment methods, that are appropriate for the user's lifestyle.

[1458] Step 5:

[1459] The server converts the generated suggestions back into JSON format and sends them to the user's smartphone over the network. It receives output data from the AI ​​model as input and converts it into an appropriate data format for sending to the smartphone as output.

[1460] Step 6:

[1461] The terminal displays suggestions received from the server via an application. For example, a specific suggestion such as, "When purchasing magazines at a station kiosk on your commute, QR code payment is convenient," might be displayed on the screen. This allows users to intuitively understand how to utilize electronic payment methods in their daily lives.

[1462] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1463] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. The system includes a function where the user inputs information, a server generates suggestions using generative artificial intelligence based on that information, and finally presents them to the user. Furthermore, the system incorporates an emotion engine to recognize the user's emotions and adds a function to adjust the suggestions according to the user's feelings.

[1464] System Configuration

[1465] 1. Input method

[1466] Users input information using a device (e.g., a smartphone or tablet). This input information includes details about the user's age and lifestyle.

[1467] Example: The user enters information requesting "How electronic payment methods are used in the daily lives of people in their 30s."

[1468] 2. Transmission method

[1469] The terminal sends information entered by the user to the server. This typically involves data transmission via network communication.

[1470] Example: The device sends data to the server regarding "how people in their 30s use electronic payment methods in their daily lives."

[1471] 3. Generation means

[1472] The server uses generative artificial intelligence (AI) based on the received information to generate appropriate suggestions. The generative AI automatically creates suggestion scenes suitable for the user based on the input conditions (e.g., age and specific scene requirements).

[1473] Example: The server generates the following suggestions regarding "how people in their 30s use electronic payment methods in their daily lives."

[1474] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[1475] Use electronic payment methods when making small purchases at convenience stores.

[1476] I use electronic payment methods for regular tea and cafe visits.

[1477] I use electronic payment methods to buy magazines at station kiosks on my way to work.

[1478] Use electronic payment methods for weekend leisure activities and purchasing movie tickets.

[1479] 4. Emotional Engine

[1480] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice, facial expressions, and physiological data to recognize emotions.

[1481] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[1482] 5. Emotion-based adjustment

[1483] The server modifies the tone and expression of suggestions based on the user's emotions as recognized by the emotion engine. For example, if the user is interested, it will provide detailed and proactive suggestions, while if they are confused, it will provide simpler and easier-to-understand suggestions.

[1484] Example: If you recognize that the user is confused, briefly explain "the procedure for purchasing groceries at a supermarket."

[1485] 6. Presentation means

[1486] The server sends information to the terminal, adjusted based on the generated suggested scenes and emotions, and the terminal presents this information to the user. The user can then view the specific suggestions on the screen.

[1487] Example: The terminal displays a list of suggested scenes received from the server and presents the user with a message such as, "You can use electronic payment methods like this when buying groceries at the supermarket."

[1488] Specific example

[1489] This system specifically proposes scenarios in which users in their 30s typically use electronic payment methods. Users input and submit "how they use electronic payment methods in their daily lives" using a terminal. The server uses generative artificial intelligence to generate the following usage scenarios based on this request:

[1490] 1. Use electronic payment methods when purchasing groceries at the supermarket on a daily basis.

[1491] 2. Use electronic payment methods when making small purchases at convenience stores.

[1492] 3. Use electronic payment methods for regular tea or cafe visits.

[1493] 4. Using electronic payment methods to purchase magazines at station kiosks during commutes.

[1494] Simultaneously, the emotion engine analyzes the user's reactions, reading their emotions from their facial expressions and voice. For example, if the user indicates "confusion," the server adjusts the suggestions to make them clearer and more concise. Finally, the device displays these suggestions on the screen, presenting them in a format that is easy for the user to understand.

[1495] In this way, users can more easily understand how to use electronic payment methods in relation to specific everyday situations, and further promotion of their use can be expected through adjustments based on their emotions.

[1496] The following describes the processing flow.

[1497] Step 1:

[1498] The user launches the application on their device and enters information. This information includes details about the user's age and lifestyle.

[1499] Example: Enter "How people in their 30s use electronic payment methods in their daily lives."

[1500] Step 2:

[1501] The terminal sends information entered by the user to the server. An internet connection is used for this transmission.

[1502] Example: Send the entered data regarding "how people in their 30s use electronic payment methods in their daily lives" to the server.

[1503] Step 3:

[1504] The server receives information sent by the user and analyzes the received data. Generative artificial intelligence is used for the analysis.

[1505] Example: The server analyzes data on "how people in their 30s use electronic payment methods in their daily lives."

[1506] Step 4:

[1507] The generative artificial intelligence generates suggested scenes that meet specific conditions based on the information it receives.

[1508] Example: Generative artificial intelligence generates suggested scenarios such as "using electronic payment methods when purchasing groceries at the supermarket."

[1509] Step 5:

[1510] During the process of generating suggested scenes, the server uses an emotion engine to recognize the user's emotions. The emotion engine recognizes emotions by analyzing the user's voice, facial expressions, and physiological data.

[1511] Example: Using a camera and microphone, the system analyzes the user's facial expressions and voice tone to recognize emotions such as "interest," "dissatisfaction," and "confusion."

[1512] Step 6:

[1513] The server adjusts its suggestions based on the emotions recognized by the emotion engine. For example, if the user shows interest, it provides detailed and proactive suggestions; if they are confused, it changes to simpler and easier-to-understand suggestions.

[1514] For example, if it is recognized that the user is confused, the content will be adjusted to briefly explain "the procedure for purchasing groceries at a supermarket."

[1515] Step 7:

[1516] The server sends the generated list of suggested scenes and information adjusted based on emotions to the terminal. An internet connection is required for transmission.

[1517] Example: Send the generated list of suggested scenes to the terminal.

[1518] Step 8:

[1519] The terminal displays a list of suggested scenes received from the server on its screen. The user can review the suggested scenes through this screen.

[1520] Example: A list of suggested scenarios is displayed on the screen, and it is presented with the message, "You can use electronic payment methods like this when purchasing groceries at the supermarket on a daily basis."

[1521] Step 9:

[1522] If a user needs more detailed information about a specific suggested scenario, they can re-enter that information and request it from the server. This is a way to obtain additional suggestions and information.

[1523] Example: The user re-enters "detailed instructions on how to use the service when purchasing groceries at the supermarket" and sends them to the server.

[1524] Step 10:

[1525] The server generates further information based on the additional request and sends it back to the terminal.

[1526] Example: The server generates detailed information such as "specific instructions on how to read QR codes at supermarkets" and sends it to the terminal.

[1527] Step 11:

[1528] The terminal receives the information again and presents the user with detailed information. The user confirms the specific usage instructions and understands how to use the electronic payment method.

[1529] Example: The device displays instructions such as "How to read the QR code," which the user then confirms.

[1530] In this way, the system can provide users with specific and practical suggestions through multiple steps. By utilizing the emotion engine, optimal suggestions are made according to the user's emotions, which is expected to further promote its use.

[1531] (Example 2)

[1532] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1533] Conventional suggestion systems have struggled to flexibly provide electronic payment methods suited to users' emotions and specific life situations. Furthermore, they lacked adjustments to account for diverse user emotional states, resulting in a uniform and inefficient user experience. Additionally, suggestions based on pre-set templates were insufficient to meet individual user needs.

[1534] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting information from the input means, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the user's emotions, and an adjustment means for adjusting the information based on the emotions recognized by the emotion recognition means. This enables flexible suggestions tailored to the individual needs of the user, and further, by adjusting the content of the suggestions according to the user's emotional state, it becomes possible to provide a more personalized and efficient user experience.

[1535] "Input means" refers to a device or interface used by a user to input their own information or requests.

[1536] "Transmission means" refers to a device or protocol that has a communication function for transmitting information obtained from input means to a server.

[1537] "Generation means" refers to a function or system that uses a generation AI model to generate appropriate suggestions or information based on the information received by the server.

[1538] "Presentation means" refers to a device or interface for presenting information generated by a generation means to a user visually or audibly.

[1539] An "emotion recognition tool" is a system or algorithm that analyzes data such as a user's facial expressions and voice to recognize the user's emotional state.

[1540] "Adjustment means" refers to a function or system for adjusting the generated suggestion content based on the user's emotions recognized by the emotion recognition means.

[1541] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. This system is composed of a combination of multiple hardware and software elements.

[1542] First, the user inputs information using an input device. A smartphone or tablet is preferred as the input device. For example, the user might input information such as "How people in their 30s use electronic payment methods in their daily lives." In this case, text input can be done using the device's touchscreen.

[1543] Next, the terminal uses a transmission method to send the information entered by the user to the server. This transmission utilizes network communication, and typically, data is sent to the server using an HTTP POST request. The transmitted data is in a common data format such as JSON.

[1544] The server generates suggestions based on the information received using a generation mechanism. The generation mechanism utilizes a generative AI model, such as OpenAI's GPT-4. The server generates specific electronic payment scenarios based on the conditions entered by the user. Examples of generated suggestions include:

[1545] I use electronic payment methods when buying groceries at the supermarket on a daily basis.

[1546] Use electronic payment methods when making small purchases at convenience stores.

[1547] I use electronic payment methods for regular tea and cafe visits.

[1548] Furthermore, the server uses emotion recognition tools to recognize the user's emotions. This utilizes emotion recognition engines such as Microsoft Azure Cognitive Services and Google Cloud Vision. These engines analyze data acquired from the camera and microphone to determine emotions such as "interest," "dissatisfaction," and "confusion" from the user's facial expressions and voice tone.

[1549] Based on the emotions determined by the emotion recognition system, the server adjusts the suggested content using an adjustment system. For example, if the user is confused, the suggested content is adjusted to be more concise and easier to understand. This adjustment improves the likelihood of the suggested content being accepted.

[1550] Finally, the terminal uses a presentation mechanism to display the adjusted suggestions to the user. The suggestions are displayed on the terminal screen, and the user can review and use them.

[1551] Examples of specific prompt messages include the following:

[1552] "Generate specific suggestions on how people in their 30s can use electronic payment methods in their daily lives. Consider the following scenarios: buying groceries at a supermarket, shopping at a convenience store, and paying at a cafe. If the user is confused, provide a brief explanation."

[1553] Thus, this invention proposes an electronic payment method suitable for the user's specific lifestyle and can be further adjusted according to the user's emotional state. This can improve the user experience.

[1554] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1555] Step 1:

[1556] The user inputs information using a device. The user uses input devices such as smartphones or tablets to input information such as their age, lifestyle, and various other conditions in text format. This input information becomes data transmitted to the server via the device's transmission method.

[1557] Specific actions:

[1558] The user enters text into an input form displayed on the device screen.

[1559] The user confirms the information by pressing the "Submit" button.

[1560] Input: Detailed information about the user's age and lifestyle.

[1561] Output: Text data entered into the terminal

[1562] Step 2:

[1563] The terminal sends information entered by the user to the server. The terminal sends data to the server via the network using a transmission method.

[1564] Specific actions:

[1565] The terminal converts the entered text data into JSON format or another format.

[1566] The device sends data to the server using an HTTP POST request.

[1567] Input: Text data of user information entered in the input form.

[1568] Output: User information in JSON format sent to the server

[1569] Step 3:

[1570] Based on the data received by the server, an AI model is used to generate appropriate suggestions. The server generates prompt sentences based on the user's age and lifestyle, and inputs them into the AI ​​model.

[1571] Specific actions:

[1572] The server generates prompt messages based on the user's age and lifestyle.

[1573] The server sends a prompt message to the AI ​​model that generates the response, and receives the generated response.

[1574] Input: User information in JSON format received by the server

[1575] Output: Text data of the proposed content generated based on the generative AI model.

[1576] Step 4:

[1577] The server uses an emotion recognition engine to recognize the user's emotions. The emotion recognition means analyzes audio and video data acquired from the camera and microphone to determine the user's emotional state.

[1578] Specific actions:

[1579] The server acquires the user's facial expressions and voice data through the camera and microphone.

[1580] The server uses an emotion recognition algorithm to determine the emotional state (e.g., "interested," "dissatisfied," "confused").

[1581] Input: User's facial expressions and voice data obtained from the device.

[1582] Output: Analyzed user emotional state data

[1583] Step 5:

[1584] The server adjusts the suggestions based on the recognized emotions. The adjustment mechanism changes the tone of the suggestions and reconstructs the information according to the user's emotional state.

[1585] Specific actions:

[1586] The server analyzes the user's emotional state data and regenerates the suggested content as needed.

[1587] If it is determined that the person is confused, the proposal will be changed to a simpler and easier-to-understand format.

[1588] Input: Generated suggestions, analyzed user emotional state data

[1589] Output: Text data of the adjusted proposal.

[1590] Step 6:

[1591] The server sends the adjusted proposal to the terminal, and the terminal presents it to the user. The adjusted proposal is displayed on the screen using the presentation method.

[1592] Specific actions:

[1593] The server sends the adjusted proposal to the terminal.

[1594] The device displays the data it has received and presents it to the user.

[1595] Input: Adjusted proposal sent from the server

[1596] Output: Screen display of the suggested content presented to the user.

[1597] The above outlines the specific processing flow of this system's program. This allows users to receive suggestions for electronic payment methods suitable for their lifestyle, and these suggestions are adjusted according to the user's feelings, enabling more appropriate and effective use.

[1598] (Application Example 2)

[1599] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1600] In modern society, users increasingly rely on electronic payment methods in various aspects of their daily lives. However, systems that automatically provide suggestions tailored to the user's age and lifestyle are not yet widespread, often leading to confusion in actual use. Furthermore, there is a lack of consideration for user emotions in the approach to suggesting electronic payment methods, resulting in a lack of suggestions that users find satisfactory.

[1601] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for the user to input information, a transmission means for sending the information from the input means to the server, a generation means for generating information based on the information received from the transmission means, a presentation means for presenting the information generated by the generation means to the user, an emotion recognition means for recognizing the user's emotions, and an adjustment means for adjusting the format of information representation based on the emotions recognized by the emotion recognition means. As a result, the user can receive suggestions for electronic payment methods that are suitable for them, and furthermore, because adjustments are made according to the user's emotions, they can receive suggestions that are more intuitive and convincing.

[1602] An "input method" is a means by which a user can input information such as their age and details of their lifestyle.

[1603] "Transmission means" refers to means for transmitting information obtained from the input means to the server.

[1604] "Generation means" refers to means for generating information using generative artificial intelligence based on information received from the transmission means.

[1605] "Presentation means" refers to means for presenting the information generated by the generation means to the user.

[1606] "Emotion recognition means" are methods for recognizing a user's emotions, and involve analyzing facial expressions, voice tone, and physiological data using cameras and microphones.

[1607] "Adjustment means" refers to means for adjusting the expression format and tone of information based on the emotions recognized by the emotion recognition means.

[1608] This invention relates to a system that allows users to receive suggestions for electronic payment methods based on specific life scenarios. To realize this system, a program configured as follows is required.

[1609] The system includes input means, transmission means, generation means, presentation means, emotion recognition means, and adjustment means.

[1610] 1. Input method

[1611] Users enter details about their age and lifestyle using devices such as smartphones and tablets. This information is registered in the system as a user profile.

[1612] 2. Transmission method

[1613] The entered user information is transmitted to the server via network communication. Here, the data entered by the user is encrypted and transmitted securely.

[1614] 3. Generation means

[1615] The server uses generative artificial intelligence (generative AI model) based on the received user information to generate suggestions for the most suitable electronic payment method. This generative AI model has the ability to automatically generate suggestions tailored to the user's age and lifestyle. Furthermore, the suggestions are easy for the user to understand and are relevant to specific daily life situations.

[1616] 4. Emotion recognition means

[1617] In addition to user input, the system monitors the user's facial expressions and voice using a camera and microphone, and analyzes the user's emotions using an emotion engine. This analysis data is then sent to a server.

[1618] 5. Adjustment means

[1619] The server adjusts the tone and expression of the generated suggestions based on the emotion data obtained from the emotion recognition system. For example, if the server recognizes that the user is confused, the suggestions will be made simpler and more specific.

[1620] 6. Presentation means

[1621] Finally, the adjusted proposal is sent back to the user's device and displayed on the screen. The user can then see this and understand how to utilize electronic payment methods in specific scenarios.

[1622] Specific example

[1623] This system considers the scenario where a businessman in his 30s wants to know how to use electronic payment methods at a train station kiosk during his commute. First, the user uses a terminal to input information about his age and specific daily life.

[1624] Please begin entering your user information. Enter your age, and then provide detailed information about how you use electronic payment methods in specific daily life situations. For example, "As a businessman in his 30s, how do I use electronic payment methods at a train station kiosk during my commute?"

[1625] Next, the server uses generative artificial intelligence to generate suggestions. For example, "a method of electronic payment using a QR code when purchasing magazines at a train station kiosk" or "an electronic payment method that can be used for regular beverage purchases."

[1626] Simultaneously, emotion recognition analyzes the user's facial expressions and voice, and if the user appears confused, adjusts the suggestions to be clearer and more concise. Finally, the adjusted suggestions are displayed on the user's device, allowing the user to understand how to effectively use electronic payment methods in specific scenarios.

[1627] In this way, users can receive suggestions for the most suitable electronic payment method tailored to their lifestyle, and because these suggestions are adjusted based on the user's feelings, they become easier to understand.

[1628] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1629] Step 1:

[1630] The user enters information using a terminal.

[1631] Input: The user enters details such as age and lifestyle (e.g., a businessman in his 30s wants to know "how to use electronic payment methods at a train station kiosk during his commute").

[1632] Processing: The terminal collects the input data and formats it for transmission to the server.

[1633] Output: Formatted user information is generated and ready for transmission.

[1634] Step 2:

[1635] The device sends user information to the server.

[1636] Input: Formalized user information.

[1637] Processing: The terminal encrypts information over the network and securely transmits it to the server.

[1638] Output: The server receives encrypted user information and decrypts it.

[1639] Step 3:

[1640] The server uses generative artificial intelligence to generate proposals.

[1641] Input: Decoded user information (e.g., a businessman in his 30s, and his electronic payment method at a train station kiosk during his commute).

[1642] Processing: The AI ​​model on the server generates suggestions for the most suitable electronic payment method based on user information.

[1643] Output: Specific suggestions (e.g., how to purchase magazines at station kiosks using QR codes) are generated.

[1644] Step 4:

[1645] The server uses emotion recognition means to recognize the user's emotions.

[1646] Input: User voice and facial expression data obtained using a camera and microphone.

[1647] Processing: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state (e.g., interest, confusion).

[1648] Output: Emotion recognition results are generated.

[1649] Step 5:

[1650] The server adjusts the tone and expression of the suggestions based on the emotions it recognizes.

[1651] Input: Generated suggestions and sentiment recognition results.

[1652] Processing: The server adjusts the proposed content to be clear and concise based on the emotion recognition result (e.g., confusion).

[1653] Output: A revised proposal (e.g., a QR code payment method with detailed steps) is generated.

[1654] Step 6:

[1655] The server sends the adjusted proposal to the terminal.

[1656] Input: Adjusted proposal content.

[1657] Processing: The server encrypts the adjusted proposal and sends it to the terminal over the network.

[1658] Output: The terminal securely receives and decodes the adjusted proposal.

[1659] Step 7:

[1660] The device presents suggestions to the user.

[1661] Input: Decoded and adjusted proposal content.

[1662] Processing: The terminal displays the suggested content and presents it in a way that is easy for the user to understand.

[1663] Output: Users can view and actually use electronic payment methods in specific everyday situations through the screen.

[1664] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1665] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1666] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1667] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1668] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1669] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1670] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1671] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1672] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1673] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1674] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1675] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1676] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1677] 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.

[1678] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1679] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1680] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1681] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1682] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1683] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1684] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1685] The following is further disclosed regarding the embodiments described above.

[1686] (Claim 1)

[1687] An input method for the user to enter information,

[1688] A transmission means for sending information from the input means to a server,

[1689] A generation means that generates information based on the information received from the transmission means,

[1690] A presentation means for presenting the information generated by the generation means to the user,

[1691] A system that includes this.

[1692] (Claim 2)

[1693] The system according to claim 1, characterized in that the generation means generates information based on user-specified conditions using a generative artificial intelligence.

[1694] (Claim 3)

[1695] The system according to claim 1, characterized in that the information generated by the generation means makes suggestions to users of a specific age group to utilize a specific electronic payment method in their daily lives.

[1696] "Example 1"

[1697] (Claim 1)

[1698] An input method for the user to enter information,

[1699] A transmission means for sending information from the input means to a server,

[1700] A generation means that generates information based on the information received from the transmission means,

[1701] A presentation means for presenting the information generated by the generation means to the user,

[1702] The generation means includes means for analyzing the information,

[1703] A means of using a generative artificial intelligence system to generate proposals based on the aforementioned information,

[1704] Means for transmitting the above proposal to the user's terminal,

[1705] A system that includes this.

[1706] (Claim 2)

[1707] The system according to claim 1, characterized in that the generation means generates information based on user-specified conditions using a generative artificial intelligence.

[1708] (Claim 3)

[1709] The system according to claim 1, characterized in that the information generated by the generation means makes suggestions to users of a specific age group to utilize a specific electronic payment method in their daily lives.

[1710] "Application Example 1"

[1711] (Claim 1)

[1712] An input method for users to input information about their daily life,

[1713] A transmission means for sending information from the input means to a server,

[1714] A generation means that generates proposal content based on the information received from the transmission means,

[1715] A presentation means for presenting the proposed content generated by the generation means to the user,

[1716] A system that includes this.

[1717] (Claim 2)

[1718] The system according to claim 1, characterized in that the generation means generates suggested content based on user-specified conditions using a generative artificial intelligence.

[1719] (Claim 3)

[1720] The system according to claim 1, characterized in that the proposed content generated by the generation means makes a proposal to users of a specific age group to utilize a specific electronic payment method in their daily lives.

[1721] "Example 2 of combining an emotion engine"

[1722] (Claim 1)

[1723] An input method for the user to enter information,

[1724] A transmission means for sending information from the input means to a server,

[1725] A generation means that generates information based on the information received from the transmission means,

[1726] A presentation means for presenting the information generated by the generation means to the user,

[1727] A means of recognizing user emotions,

[1728] An adjustment means for adjusting information based on the emotions recognized by the emotion recognition means,

[1729] A system that includes this.

[1730] (Claim 2)

[1731] The system according to claim 1, characterized in that the generation means generates information based on user-specified conditions using a generation AI model.

[1732] (Claim 3)

[1733] The system according to claim 1, characterized in that the information generated by the generation means makes suggestions to users of a specific age group to utilize a specific electronic payment method in their daily lives.

[1734] "Application example 2 when combining with an emotional engine"

[1735] (Claim 1)

[1736] An input method for the user to enter information,

[1737] A transmission means for sending information from the input means to a server,

[1738] A generation means that generates information based on the information received from the transmission means,

[1739] A presentation means for presenting the information generated by the generation means to the user,

[1740] A means of recognizing user emotions,

[1741] An adjustment means for adjusting the format of information representation based on the emotion recognized by the emotion recognition means,

[1742] A system that includes this.

[1743] (Claim 2)

[1744] The system according to claim 1, characterized in that the generation means generates information based on user-specified conditions using a generative artificial intelligence.

[1745] (Claim 3)

[1746] The system according to claim 1, characterized in that the information generated by the generation means makes suggestions to users of a specific age group to utilize a specific electronic payment method in their daily lives. [Explanation of symbols]

[1747] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for the user to enter information, A transmission means for sending information from the input means to a server, A generation means that generates information based on the information received from the transmission means, A presentation means for presenting the information generated by the generation means to the user, A system that includes this.

2. The system according to claim 1, characterized in that the generation means generates information based on user-specified conditions using a generative artificial intelligence.

3. The system according to claim 1, characterized in that the information generated by the generation means makes suggestions to users of a specific age group to utilize a specific electronic payment method in their daily lives.

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